[ { "path": "LICENSE", "content": "Copyright (c) 2021 SAMSUNG\n\nPermission is hereby granted, free of charge, to any person obtaining a copy \nof this software and associated documentation files (the \"Software\"), to deal \nin the Software without restriction, including without limitation the rights \nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell \ncopies of the Software, and to permit persons to whom the Software is \nfurnished to do so, subject to the following conditions: \n\nThe above copyright notice and this permission notice shall be included in all \ncopies or substantial portions of the Software. \n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR \nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, \nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE \nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER \nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, \nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE \nSOFTWARE.\n" }, { "path": "README.md", "content": "# CredSweeper\n\n[![GitHub release (latestSemVer)](https://img.shields.io/github/v/release/Samsung/CredSweeper)](https://github.com/Samsung/CredSweeper/releases)\n[![Documentation Status](https://readthedocs.org/projects/credsweeper/badge/?version=latest)](https://credsweeper.readthedocs.io/en/latest/?badge=latest)\n[![License](https://img.shields.io/badge/licence-MIT-green.svg?style=flat)](LICENSE)\n[![PyPI](https://img.shields.io/pypi/v/credsweeper)](https://pypi.org/project/credsweeper/)\n[![Python](https://img.shields.io/pypi/pyversions/credsweeper.svg)](https://badge.fury.io/py/credsweeper)\n[![Test](https://github.com/Samsung/CredSweeper/actions/workflows/test.yml/badge.svg)](https://github.com/Samsung/CredSweeper/actions/workflows/test.yml)\n[![codecov](https://codecov.io/gh/Samsung/CredSweeper/branch/main/graph/badge.svg)](https://codecov.io/gh/Samsung/CredSweeper)\n[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/6055/badge)](https://bestpractices.coreinfrastructure.org/projects/6055)\n[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/Samsung/CredSweeper/badge)](https://api.securityscorecards.dev/projects/github.com/Samsung/CredSweeper)\n\n\n\n- [CredSweeper](#credsweeper)\n - [Introduction](#introduction)\n - [How To Use](#how-to-use)\n - [Main Requirements](#main-requirements)\n - [Installation](#installation)\n - [Run](#run)\n - [Config](#config)\n - [Develop](#develop)\n - [Tests](#tests)\n - [Benchmark](#benchmark)\n - [Overall Architecture](#overall-architecture)\n - [Retrain Model](#retrain-model)\n - [License](#license)\n - [How to Get Involved](#how-to-get-involved)\n - [Project Roles](#project-roles)\n - [Contributor](#contributor)\n - [Maintainer](#maintainer)\n - [How to Contact](#how-to-contact)\n\n## Introduction\n\nCredSweeper is an advanced credential detection tool designed to identify exposed\ncredentials such as passwords, API keys, tokens, and other sensitive information\nacross source code, configuration files, documents, and binary assets.\nCredSweeper scans regular files, embedded data in containers, and files added in Git commits.\nThe tool combines pattern-based detection, machine learning–based validation, and\ndeep file inspection to deliver comprehensive and accurate security scanning for\nmodern codebases and repositories.\n\n**Key Capabilities:**\n- Credential detection in source code, configuration files, documents, and archives\n- False positive reduction using algorithmic filters and machine learning\n- Scanning of compressed files, documents, and binary formats\n- Git repository analysis and diff scanning\n\nFull documentation can be found here: \n\n## How To Use\n\n### Main Requirements\n\n- Python 3.10, 3.11, 3.12, 3.13, 3.14\n\n### Installation\n\nDetails [here](https://credsweeper.readthedocs.io/en/latest/install.html).\n\n```bash\npip install credsweeper\n```\n\n### Run\n\n[How to use](https://credsweeper.readthedocs.io/en/latest/guide.html).\n\nRun CredSweeper:\n\n```bash\npython -m credsweeper --path tests/samples/password.gradle --save-json output.json\n```\n\n### JSON Output\n\n```json\n[\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"cackle!\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.gradle\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n }\n]\n```\n\n### Config\n\n[credsweeper/secret/config.json](credsweeper/secret/config.json) - Configuration file for pre-processing of CredSweeper. For more details please check [here](https://credsweeper.readthedocs.io/en/latest/overall_architecture.html#pre-processing).\n\nYou can set the `pattern`, `extension` and `path` you want to exclude from scanning as below.\n\n```json\n{\n \"exclude\": {\n \"pattern\": [\n \"AKIA[0-9A-Z]{9}EXAMPLE\",\n ...\n ],\n \"extension\": [\n \"gif\",\n \"jpg\",\n ...\n ],\n \"path\": [\n \"/.git/\",\n \"/openssl/\",\n ...\n ]\n },\n ...\n}\n```\n\nAnd you can also set `source_ext`, `source_quote_ext`, `find_by_ext_list`, `check_for_literals`, `line_data_output`, and `candidate_output` as below.\n\n- `source_ext`: List of extensions for scanning categorized as source files.\n- `source_quote_ext`: List of extensions for scanning categorized as source files that use quotes.\n- `find_by_ext_list`: List of extensions to detect only extensions.\n- `check_for_literals`: Bool value for whether to check line has string literal declaration or not.\n- `line_data_output`: List of attributes of [line_data](credsweeper/credentials/line_data.py) for output.\n- `candidate_output`: List of attributes of [candidate](credsweeper/credentials/candidate.py) for output.\n\n```json\n{\n ...\n \"source_ext\": [\n \".py\",\n \".cpp\",\n ...\n ],\n \"source_quote_ext\": [\n \".py\",\n \".cpp\",\n ...\n ],\n \"find_by_ext_list\": [\n \".pem\",\n \".cer\",\n ...\n ],\n \"check_for_literals\": true,\n \"line_data_output\": [\n \"line\",\n \"line_num\",\n ...\n ],\n \"candidate_output\": [\n \"rule\",\n \"severity\",\n ...\n ]\n}\n```\n\n[credsweeper/rules/config.yaml](credsweeper/rules/config.yaml) - Configuration file for setting Rule. For more details please check [here](https://credsweeper.readthedocs.io/en/latest/overall_architecture.html#rule).\n\n```yaml\n- name: Credential\n severity: medium\n confidence: moderate\n type: keyword\n values:\n - credential\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 18\n required_substrings:\n - credential\n target:\n - code\n```\n\n## Develop\n\n### Tests\n\nRun all tests with random order:\n\n```bash\npython -m pytest --cov=credsweeper --cov-report=term-missing --random-order --random-order-bucket=global -s tests/\n```\n\n### Benchmark\n\nWe have a dataset for testing credential scanners called [CredData](https://github.com/Samsung/CredData).\nIf you want to test CredSweeper with this dataset please check [here](https://github.com/Samsung/CredData/blob/main/README.md#benchmark).\n\n## Overall Architecture\n\nTo check overall architecture of CredSweeper please check [here](https://credsweeper.readthedocs.io/en/latest/overall_architecture.html).\n\n## Retrain Model\n\nIf you want to check how model was trained or retrain it on your own data, please refer to the [experiment](experiment/README.md) folder\n\n## License\n\nThe CredSweeper is an Open Source project released under the terms of [MIT License](https://opensource.org/licenses/mit-license.php).\n\n## How to Get Involved\n\nIn addition to developing under an Open Source license, the project follows an Open Source Development approach,\nwelcoming everyone to participate, contribute, and engage with each other through the project.\n\n### Project Roles\n\nThe project recognizes the following formal roles: Contributor and Maintainer.\nInformally, the community may organize itself and grant additional rights and responsibilities to the necessary people to achieve its goals.\n\n#### Contributor\n\nA Contributor is anyone who wishes to contribute to the project, at any level. Contributors are granted the following rights to:\n\n- Contribute code, documentation, translations, artwork, samples, etc.\n- Report defects (bugs) and suggestions for enhancement.\n- Participate in the process of reviewing contributions by others.\n\nIf you want to participate in the project development, check out the [how to contribute guideline](./docs/howto/how-to-contribute.md) in advance.\n\nContributors who show dedication and skill are rewarded with additional rights and responsibilities.\nTheir opinions weigh more when decisions are made, in a fully meritocratic fashion.\n\n#### Maintainer\n\nA Maintainer is a Contributor who is also responsible for knowing, directing and anticipating the needs of a given Module.\nAs such, Maintainers have the right to set the overall organization of the source code in the Module,\nand the right to participate in the decision-making. Maintainers are required to review the contributor’s requests and decide whether to accept or not.\n\n| Name | E-Mail |\n|------------------------------------------------|------------------------|\n| [Jaeku Yun](https://github.com/silentearth) | jk0113.yun@samsung.com |\n| [Shinhyung Choi](https://github.com/csh519) | sh519.choi@samsung.com |\n| [Roman Babenko](https://github.com/babenek) | r.babenko@samsung.com |\n| [Yuliia Tatarinova](https://github.com/Yullia) | yuliia.t@samsung.com |\n\n## How to Contact\n\nPlease post questions, [issues, or suggestions in issues](https://github.com/Samsung/CredSweeper/issues). This is the best way to communicate with the developers.\n" }, { "path": "SECURITY.md", "content": "# Security Policy\n\n## Supported Versions\n\n| Version | Supported |\n|---------|--------------------|\n| 1.15.x | :white_check_mark: |\n| <1.15.x | :x: |\n\n## Reporting a Vulnerability\n\nPlease use [issues](https://github.com/Samsung/CredSweeper/issues) to report about any security issue.\n" }, { "path": "action.yml", "content": "name: \"CredSweeper action\"\ndescription: \"CredSweeper checks files\"\nauthor: \"r.babenko@samsung.com\"\nbranding:\n icon: \"terminal\"\n color: \"gray-dark\"\ninputs:\n python_version:\n description: \"Python Version. 3.10 - default\"\n default: \"3.10\"\n required: false\n path:\n description: \"Path to scan\"\n required: true\n report:\n description: \"CredSweeper report in JSON format\"\n default: \"output.json\"\n required: false\n hashed:\n description: \"Report output is hashed by default\"\n default: \"--hashed\"\n required: false\n error:\n description: \"Exit with an error code if credentials are detected\"\n default: \"--error\"\n required: false\nruns:\n using: \"composite\"\n steps:\n - name: DEBUG\n shell: bash\n env:\n path: ${{ inputs.path }}\n report: ${{ inputs.report }}\n error: ${{ inputs.error }}\n hashed: ${{ inputs.hashed }}\n run: echo \"print ('@@@ $error @@@ $report @@@ $path @@@ $PATH @@@')\"\n\n - name: Setup Python\n uses: actions/setup-python@42375524e23c412d93fb67b49958b491fce71c38 # v5.4.0 - 2025.01.28\n with:\n python-version: ${{ inputs.python_version }}\n\n - name: Install CredSweeper\n shell: bash\n run: python -m pip install credsweeper\n\n - name: Run CredSweeper\n shell: bash\n env:\n path: ${{ inputs.path }}\n report: ${{ inputs.report }}\n error: ${{ inputs.error }}\n hashed: ${{ inputs.hashed }}\n run: python -m credsweeper --banner --log INFO --no-color --no-stdout \"$error\" \"$hashed\" --save-json \"$report\" --path \"$path\"\n" }, { "path": "credsweeper/__init__.py", "content": "from credsweeper.app import CredSweeper\nfrom credsweeper.common.constants import ThresholdPreset, Severity, Confidence\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.diff_content_provider import DiffContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.file_handler.text_content_provider import TextContentProvider\n\nfrom credsweeper.ml_model.ml_validator import MlValidator\n\n__all__ = [\n \"ByteContentProvider\", #\n \"Confidence\", #\n \"ContentProvider\", #\n \"CredSweeper\", #\n \"DataContentProvider\", #\n \"DiffContentProvider\", #\n \"MlValidator\", #\n \"Severity\", #\n \"StringContentProvider\", #\n \"TextContentProvider\", #\n \"ThresholdPreset\", #\n \"__version__\"\n]\n\n__version__ = \"1.15.7\"\n" }, { "path": "credsweeper/__main__.py", "content": "import sys\n\nfrom credsweeper.main import main\n\nif __name__ == \"__main__\":\n sys.exit(main())\n" }, { "path": "credsweeper/app.py", "content": "import json\nimport logging\nimport multiprocessing\nimport signal\nfrom pathlib import Path\nfrom typing import Any, List, Optional, Union, Dict, Sequence, Tuple\n\nimport pandas as pd\nfrom colorama import Style\n\n# Directory of credsweeper sources MUST be placed before imports to avoid circular import error\nAPP_PATH = Path(__file__).resolve().parent\n\nfrom credsweeper.scanner.scanner import Scanner\nfrom credsweeper.common.constants import Severity, ThresholdPreset, DiffRowType, DEFAULT_ENCODING\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.candidate_key import CandidateKey\nfrom credsweeper.credentials.credential_manager import CredentialManager\nfrom credsweeper.deep_scanner.deep_scanner import DeepScanner\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.ml_model.ml_validator import MlValidator\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass CredSweeper:\n \"\"\"Advanced credential analyzer base class.\n\n Parameters:\n credential_manager: CredSweeper credential manager object\n scanner: CredSweeper scanner object\n pool_count: number of pools used to run multiprocessing scanning\n config: dictionary variable, stores analyzer features\n json_filename: string variable, credential candidates export filename\n\n \"\"\"\n\n def __init__(self,\n rule_path: Union[None, str, Path] = None,\n config_path: Optional[str] = None,\n json_filename: Union[None, str, Path] = None,\n xlsx_filename: Union[None, str, Path] = None,\n stdout: bool = False,\n color: bool = False,\n hashed: bool = False,\n subtext: bool = False,\n sort_output: bool = False,\n use_filters: bool = True,\n pool_count: int = 1,\n ml_batch_size: Optional[int] = None,\n ml_threshold: Union[int, float, ThresholdPreset] = ThresholdPreset.medium,\n ml_config: Union[None, str, Path] = None,\n ml_model: Union[None, str, Path] = None,\n ml_providers: Optional[str] = None,\n find_by_ext: bool = False,\n pedantic: bool = False,\n depth: int = 0,\n doc: bool = False,\n severity: Union[Severity, str] = Severity.INFO,\n size_limit: Optional[str] = None,\n exclude_lines: Optional[List[str]] = None,\n exclude_values: Optional[List[str]] = None,\n thrifty: bool = False,\n log_level: Optional[str] = None) -> None:\n \"\"\"Initialize Advanced credential scanner.\n\n Args:\n rule_path: optional str variable, path of rule config file\n validation was the grained candidate model on machine learning\n config_path: optional str variable, path of CredSweeper config file\n default built-in config is used if None\n json_filename: optional string variable, path to save result to json\n xlsx_filename: optional string variable, path to save result to xlsx\n stdout: print results to stdout\n color: print concise results to stdout with colorization\n hashed: use hash of line, value and variable instead plain text\n subtext: use subtext of line near variable-value like it performed in ML\n use_filters: boolean variable, specifying the need of rule filters\n pool_count: int value, number of parallel processes to use\n ml_batch_size: int value, size of the batch for model inference\n ml_threshold: float or string value to specify threshold for the ml model\n ml_config: str or Path to set custom config of ml model\n ml_model: str or Path to set custom ml model\n ml_providers: str - comma separated list with providers\n find_by_ext: boolean - files will be reported by extension\n pedantic: boolean - scan all files\n depth: int - how deep container files will be scanned\n doc: boolean - document-specific scanning\n severity: Severity - minimum severity level of rule\n size_limit: optional string integer or human-readable format to skip oversize files\n exclude_lines: lines to omit in scan. Will be added to the lines already in config\n exclude_values: values to omit in scan. Will be added to the values already in config\n thrifty: free provider resources after scan to reduce memory consumption\n log_level: str - level for pool initializer according logging levels (UPPERCASE)\n\n \"\"\"\n self.pool_count: int = max(1, int(pool_count))\n if not (_severity := Severity.get(severity)):\n raise RuntimeError(f\"Severity level provided: {severity}\"\n f\" -- must be one of: {' | '.join([i.value for i in Severity])}\")\n config_dict = self._get_config_dict(config_path=config_path,\n use_filters=use_filters,\n find_by_ext=find_by_ext,\n pedantic=pedantic,\n depth=depth,\n doc=doc,\n severity=_severity,\n size_limit=size_limit,\n exclude_lines=exclude_lines,\n exclude_values=exclude_values)\n self.config = Config(config_dict)\n self.scanner = Scanner(self.config, rule_path)\n self.deep_scanner = DeepScanner(self.config, self.scanner)\n self.credential_manager = CredentialManager()\n self.json_filename: Union[None, str, Path] = json_filename\n self.xlsx_filename: Union[None, str, Path] = xlsx_filename\n self.stdout = stdout\n self.color = color\n self.hashed = hashed\n self.subtext = subtext\n self.sort_output = sort_output\n self.ml_batch_size = ml_batch_size if ml_batch_size and 0 < ml_batch_size else 16\n self.ml_threshold = ml_threshold\n self.ml_config = ml_config\n self.ml_model = ml_model\n self.ml_providers = ml_providers\n self.__thrifty = thrifty\n self.__log_level = log_level\n self.__ml_validator: Optional[MlValidator] = None\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @staticmethod\n def _get_config_path(config_path: Optional[str]) -> Path:\n if config_path:\n return Path(config_path)\n return APP_PATH / \"secret\" / \"config.json\"\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def _get_config_dict(\n self, #\n config_path: Optional[str], #\n use_filters: bool, #\n find_by_ext: bool, #\n pedantic: bool, #\n depth: int, #\n doc: bool, #\n severity: Severity, #\n size_limit: Optional[str], #\n exclude_lines: Optional[List[str]], #\n exclude_values: Optional[List[str]]) -> Dict[str, Any]:\n config_dict = Util.json_load(self._get_config_path(config_path))\n config_dict[\"use_filters\"] = use_filters\n config_dict[\"find_by_ext\"] = find_by_ext\n config_dict[\"size_limit\"] = size_limit\n config_dict[\"pedantic\"] = pedantic\n config_dict[\"depth\"] = depth\n config_dict[\"doc\"] = doc\n config_dict[\"severity\"] = severity.value\n\n if exclude_lines is not None:\n config_dict[\"exclude\"][\"lines\"] = config_dict[\"exclude\"].get(\"lines\", []) + exclude_lines\n if exclude_values is not None:\n config_dict[\"exclude\"][\"values\"] = config_dict[\"exclude\"].get(\"values\", []) + exclude_values\n\n return config_dict # type: ignore\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def _use_ml_validation(self) -> bool:\n if isinstance(self.ml_threshold, int) and 0 == self.ml_threshold:\n logger.info(\"ML validation is disabled\")\n return False\n if not self.credential_manager.candidates:\n logger.info(\"Skip ML validation because no candidates were found\")\n return False\n for i in self.credential_manager.candidates:\n if i.use_ml:\n # any() or all() is not used to speedup\n return True\n logger.info(\"Skip ML validation because no candidates support it\")\n return False\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @property\n def ml_validator(self) -> MlValidator:\n \"\"\"ml_validator getter\"\"\"\n if not self.__ml_validator:\n self.__ml_validator = MlValidator(\n threshold=self.ml_threshold, #\n ml_config=self.ml_config, #\n ml_model=self.ml_model, #\n ml_providers=self.ml_providers, #\n )\n if not self.__ml_validator:\n raise RuntimeError(\"MlValidator was not initialized!\")\n return self.__ml_validator\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @staticmethod\n def pool_initializer(log_kwargs) -> None:\n \"\"\"Ignore SIGINT in child processes.\"\"\"\n logging.basicConfig(**log_kwargs)\n signal.signal(signal.SIGINT, signal.SIG_IGN)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def run(self, content_provider: AbstractProvider) -> int:\n \"\"\"Run an analysis of 'content_provider' object.\n\n Args:\n content_provider: path objects to scan\n\n \"\"\"\n _empty_list: Sequence[ContentProvider] = []\n file_extractors = content_provider.get_scannable_files(self.config) if content_provider else _empty_list\n if not file_extractors:\n logger.info(\"No scannable targets for %s paths\", len(content_provider.paths))\n return 0\n self.scan(file_extractors)\n self.post_processing()\n # PatchesProvider has the attribute. Circular import error appears with using the isinstance\n change_type = content_provider.change_type if hasattr(content_provider, \"change_type\") else None\n self.export_results(change_type)\n return self.credential_manager.len_credentials()\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def scan(self, content_providers: Sequence[ContentProvider]) -> None:\n \"\"\"Run scanning of files from an argument \"content_providers\".\n\n Args:\n content_providers: file objects to scan\n\n \"\"\"\n if 1 < self.pool_count and 1 < len(content_providers):\n self.__multi_jobs_scan(content_providers)\n else:\n self.__single_job_scan(content_providers)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def __single_job_scan(self, content_providers: Sequence[ContentProvider]) -> None:\n \"\"\"Performs scan in main thread\"\"\"\n logger.info(\"Scan for %s providers\", len(content_providers))\n all_cred = self.files_scan(content_providers)\n self.credential_manager.set_credentials(all_cred)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def __multi_jobs_scan(self, content_providers: Sequence[ContentProvider]) -> None:\n \"\"\"Performs scan with multiple jobs\"\"\"\n # use this separation to satisfy YAPF formatter\n yapfix = \"%(asctime)s | %(levelname)s | %(processName)s:%(threadName)s | %(filename)s:%(lineno)s | %(message)s\"\n log_kwargs = {\"format\": yapfix}\n if isinstance(self.__log_level, str):\n # is not None\n if \"SILENCE\" == self.__log_level:\n logging.addLevelName(60, \"SILENCE\")\n log_kwargs[\"level\"] = self.__log_level\n pool_count = min(self.pool_count, len(content_providers))\n logger.info(\"Scan in %s processes for %s providers\", pool_count, len(content_providers))\n with multiprocessing.get_context(\"spawn\").Pool(processes=pool_count,\n initializer=CredSweeper.pool_initializer,\n initargs=(log_kwargs,)) as pool: # yapf: disable\n try:\n for scan_results in pool.imap_unordered(self.files_scan,\n (content_providers[x::pool_count] for x in range(pool_count))):\n for cred in scan_results:\n self.credential_manager.add_credential(cred)\n except KeyboardInterrupt:\n pool.terminate()\n pool.join()\n raise\n pool.close()\n pool.join()\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def files_scan(self, content_providers: Sequence[ContentProvider]) -> List[Candidate]:\n \"\"\"Auxiliary method for scan one sequence\"\"\"\n all_cred: List[Candidate] = []\n for provider in content_providers:\n candidates = self.file_scan(provider)\n if self.__thrifty:\n provider.free()\n all_cred.extend(candidates)\n logger.info(\"Completed: processed %s providers with %s candidates\", len(content_providers), len(all_cred))\n return all_cred\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def file_scan(self, content_provider: ContentProvider) -> List[Candidate]:\n \"\"\"Run scanning of file from 'file_provider'.\n\n Args:\n content_provider: content provider object to scan\n\n Return:\n list of credential candidates from scanned file\n\n \"\"\"\n candidates: List[Candidate] = []\n logger.debug(\"Start scan file: %s %s\", content_provider.file_path, content_provider.info)\n\n if FilePathExtractor.is_find_by_ext_file(self.config, content_provider.file_type):\n # Skip the file scanning and create fake candidate because the extension is suspicious\n dummy_candidate = Candidate.get_dummy_candidate(self.config, content_provider.file_path,\n content_provider.file_type, content_provider.info,\n FilePathExtractor.FIND_BY_EXT_RULE)\n candidates.append(dummy_candidate)\n\n else:\n if self.config.depth or self.config.doc:\n # deep scan with possible data representation\n candidates = self.deep_scanner.scan(content_provider, self.config.depth, self.config.size_limit)\n else:\n if content_provider.file_type not in self.config.exclude_containers:\n # Regular file scanning\n candidates = self.scanner.scan(content_provider)\n\n # finally return result from 'file_scan'\n return candidates\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def post_processing(self) -> None:\n \"\"\"Machine learning validation for received credential candidates.\"\"\"\n if purged := self.credential_manager.purge_duplicates():\n logger.info(\"Purged %s duplicates\", purged)\n if self._use_ml_validation():\n logger.info(\"Grouping %s candidates\", len(self.credential_manager.candidates))\n new_cred_list: List[Candidate] = []\n cred_groups = self.credential_manager.group_credentials()\n ml_cred_groups: List[Tuple[CandidateKey, List[Candidate]]] = []\n for group_key, group_candidates in cred_groups.items():\n # Analyze with ML if any candidate in group require ML\n for candidate in group_candidates:\n if candidate.use_ml:\n ml_cred_groups.append((group_key, group_candidates))\n break\n else:\n # all candidates do not require ML\n new_cred_list.extend(group_candidates)\n\n # prevent extra ml_validator creation if ml_cred_groups is empty\n if ml_cred_groups:\n logger.info(\"Run ML Validation for %s groups\", len(ml_cred_groups))\n is_cred, probability = self.ml_validator.validate_groups(ml_cred_groups, self.ml_batch_size)\n for i, (_, group_candidates) in enumerate(ml_cred_groups):\n for candidate in group_candidates:\n if candidate.use_ml:\n if is_cred[i]:\n candidate.ml_probability = probability[i]\n new_cred_list.append(candidate)\n else:\n new_cred_list.append(candidate)\n else:\n logger.info(\"Skipping ML validation due not applicable\")\n\n self.credential_manager.set_credentials(new_cred_list)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def export_results(self, change_type: Optional[DiffRowType] = None) -> None:\n \"\"\"\n Save credential candidates to json file or print them to a console.\n\n Args:\n change_type: flag to know which file should be created for a patch\n \"\"\"\n\n credentials = self.credential_manager.get_credentials()\n\n logger.info(\"Exporting %s credentials\", len(credentials))\n\n if self.sort_output:\n credentials.sort(key=lambda x: ( #\n x.line_data_list[0].path, #\n x.line_data_list[0].line_num, #\n x.severity, #\n x.rule_name, #\n x.line_data_list[0].value_start, #\n x.line_data_list[0].value_end #\n ))\n\n if self.json_filename:\n json_path = Path(self.json_filename)\n if isinstance(change_type, DiffRowType):\n # add suffix for appropriated reports to create two files for the patch scan\n json_path = json_path.with_suffix(f\".{change_type.value}{json_path.suffix}\")\n with open(json_path, 'w', encoding=DEFAULT_ENCODING) as f:\n # use the approach to reduce total memory usage in case of huge data\n first_item = True\n f.write('[\\n')\n for credential in credentials:\n if first_item:\n first_item = False\n else:\n f.write(\",\\n\")\n f.write(json.dumps(credential.to_json(hashed=self.hashed, subtext=self.subtext), indent=4))\n f.write(\"\\n]\")\n\n if self.xlsx_filename:\n data_list = []\n for credential in credentials:\n data_list.extend(credential.to_dict_list(hashed=self.hashed, subtext=self.subtext))\n df = pd.DataFrame(data=data_list)\n if isinstance(change_type, DiffRowType):\n if Path(self.xlsx_filename).exists():\n with pd.ExcelWriter(self.xlsx_filename, mode='a', engine=\"openpyxl\",\n if_sheet_exists=\"replace\") as writer:\n df.to_excel(writer, sheet_name=change_type.value, index=False)\n else:\n df.to_excel(self.xlsx_filename, sheet_name=change_type.value, index=False)\n else:\n df.to_excel(self.xlsx_filename, sheet_name=\"report\", index=False)\n\n if self.color:\n for credential in credentials:\n for line_data in credential.line_data_list:\n # bright rule name and path or info\n if isinstance(credential.ml_probability, float):\n ml_probability_info = f\" {credential.ml_probability:.6f}\"\n else:\n ml_probability_info = \"\"\n print(Style.BRIGHT + credential.rule_name +\n f\" {line_data.info or line_data.path}:{line_data.line_num}{ml_probability_info}\" +\n Style.RESET_ALL)\n print(line_data.get_colored_line(hashed=self.hashed, subtext=self.subtext))\n\n if self.stdout:\n for credential in credentials:\n print(credential.to_str(hashed=self.hashed, subtext=self.subtext))\n" }, { "path": "credsweeper/common/__init__.py", "content": "from credsweeper.common.keyword_checklist import KeywordChecklist\n\n# use the variable to avoid singleton creation and make testing easier\nstatic_keyword_checklist = KeywordChecklist()\n" }, { "path": "credsweeper/common/constants.py", "content": "import string\nimport typing\nfrom enum import Enum\nfrom typing import Optional, Union\n\n\nclass Severity(Enum):\n \"\"\"Severity of candidate\"\"\"\n CRITICAL = \"critical\"\n HIGH = \"high\"\n MEDIUM = \"medium\"\n LOW = \"low\"\n INFO = \"info\"\n\n def __lt__(self, other) -> bool:\n if Severity.INFO == self:\n return other is not Severity.INFO\n if Severity.LOW == self:\n return other in [Severity.MEDIUM, Severity.HIGH, Severity.CRITICAL]\n if Severity.MEDIUM == self:\n return other in [Severity.HIGH, Severity.CRITICAL]\n if Severity.HIGH == self:\n return other is Severity.CRITICAL\n return False\n\n @staticmethod\n def get(severity: Union[str, \"Severity\"]) -> Optional[\"Severity\"]:\n \"\"\"returns Severity value from string or None\"\"\"\n if isinstance(severity, Severity):\n return severity\n if isinstance(severity, str):\n value = getattr(Severity, severity.strip().upper(), None)\n if isinstance(value, Severity):\n return value\n return None\n\n\nclass Confidence(Enum):\n \"\"\"Confidence of candidate\"\"\"\n STRONG = \"strong\"\n MODERATE = \"moderate\"\n WEAK = \"weak\"\n\n def __lt__(self, other) -> bool:\n if Confidence.WEAK == self:\n return other is not Confidence.WEAK\n if Confidence.MODERATE == self:\n return other is Confidence.STRONG\n return False\n\n @staticmethod\n def get(confidence: Union[str, \"Confidence\"]) -> Optional[\"Confidence\"]:\n \"\"\"returns Confidence value from string or None\"\"\"\n if isinstance(confidence, Confidence):\n return confidence\n if isinstance(confidence, str):\n value = getattr(Confidence, confidence.strip().upper(), None)\n if isinstance(value, Confidence):\n return value\n return None\n\n\nBASE64COMMON = string.ascii_uppercase + string.ascii_lowercase + string.digits\n\n\nclass Chars(Enum):\n \"\"\"Stores enumeration of characters sets of encoding dictionaries\"\"\"\n\n # set of characters, hexadecimal numeral system (Base16). Upper- and lowercase\n HEX_CHARS = string.digits + \"ABCDEFabcdef\"\n # UUID charset in uppercase\n UUID_UPPER_CHARS = string.digits + \"ABCDEF-\"\n # UUID charset in lowercase\n UUID_LOWER_CHARS = string.digits + \"abcdef-\"\n # set of characters, hexadecimal numeral system (Base16). Uppercase\n BASE16UPPER = string.digits + \"ABCDEF\"\n # set of characters, hexadecimal numeral system (Base16). Lowercase\n BASE16LOWER = string.digits + \"abcdef\"\n # set of 32 characters, used in Base32 encoding\n BASE32_CHARS = string.ascii_uppercase + \"234567\"\n # set of 36 characters, used in Base36 encoding\n BASE36_CHARS = string.digits + string.ascii_lowercase\n # base62 set https://en.wikipedia.org/wiki/Base62\n BASE62_CHARS = string.digits + string.ascii_uppercase + string.ascii_lowercase\n # URL- and filename-safe standard\n BASE64URL_CHARS = BASE64COMMON + \"-_\"\n # URL- and filename-safe standard plus padding sign\n BASE64URLPAD_CHARS = BASE64COMMON + \"-_=\"\n # standard base64 charset\n BASE64STD_CHARS = BASE64COMMON + \"+/\"\n # standard base64 plus padding sign\n BASE64STDPAD_CHARS = BASE64COMMON + \"+/=\"\n # except whitespaces\n ASCII_VISIBLE = string.digits + string.ascii_letters + string.punctuation\n # all printable symbols\n ASCII_PRINTABLE = string.printable\n\n\nclass GroupType(Enum):\n \"\"\"Group type - used in Group constructor for load predefined set of filters\"\"\"\n KEYWORD = \"keyword\"\n PATTERN = \"pattern\"\n # for empty filter set\n DEFAULT = \"default\"\n\n\nclass RuleType(Enum):\n \"\"\"Rule type\"\"\"\n # combine pattern with predefined structure\n KEYWORD = \"keyword\"\n # use patterns as-is. all patterns must be found in target (line)\n PATTERN = \"pattern\"\n # single value to detect pem format with specific scanner\n PEM_KEY = \"pem_key\"\n # When first pattern found - second will be searched in adjoining lines\n MULTI = \"multi\"\n\n\nclass ThresholdPreset(Enum):\n \"\"\"Preset threshold to simplify precision/recall selection for the user.\"\"\"\n lowest = \"lowest\"\n low = \"low\"\n medium = \"medium\"\n high = \"high\"\n highest = \"highest\"\n\n\nclass DiffRowType(Enum):\n \"\"\"Diff type of row\"\"\"\n ADDED = \"added\"\n DELETED = \"deleted\"\n\n\nStartEnd = typing.NamedTuple(\"StartEnd\", [(\"start\", int), (\"end\", int)])\n\nMIN_VARIABLE_LENGTH = 1\nMIN_SEPARATOR_LENGTH = 1\nMIN_VALUE_LENGTH = 4\n# if the line is oversize - it will be scanned by chunks with overlapping\nMAX_LINE_LENGTH = 8000\n# the size for overlapping chunks must be less than MAX_LINE_LENGTH\nCHUNK_SIZE = 4000\nOVERLAP_SIZE = 1000\nCHUNK_STEP_SIZE = CHUNK_SIZE - OVERLAP_SIZE\n# ML hunk size to limit of variable or value size and get substring near value\nML_HUNK = 64\n\n# values according https://docs.python.org/3/library/codecs.html\nUTF_8 = \"utf_8\"\nLATIN_1 = \"latin_1\"\nASCII = \"ascii\"\n# 16-bits codecs may be detected during decoding\nUTF_16_LE = \"utf_16_le\"\nUTF_16_BE = \"utf_16_be\"\n\nDEFAULT_ENCODING = UTF_8\n\n# LATIN_1 has to be placed at end to apply binary file detection\nAVAILABLE_ENCODINGS = [UTF_8, LATIN_1]\n\n# to limit memory usage in case of recursive scan\nRECURSIVE_SCAN_LIMITATION = 1 << 30\n\n# default value for config and ValuePatternCheck\nDEFAULT_PATTERN_LEN = 4\n\n# PEM x509 patterns\nPEM_BEGIN_PATTERN = \"-----BEGIN\"\nPEM_END_PATTERN = \"-----END\"\n\n# similar min_line_len in rule_template - no real credential in data less than 8 bytes\nMIN_DATA_LEN = 8\n" }, { "path": "credsweeper/common/keyword_checklist.py", "content": "from functools import cached_property\nfrom typing import Set, List\n\nfrom credsweeper.app import APP_PATH\n\n\nclass KeywordChecklist:\n \"\"\"KeywordsChecklist contains words 3 or more letters length\"\"\"\n __keyword_set: Set[str]\n __morpheme_set: Set[str]\n KEYWORD_PATH = APP_PATH / \"common\" / \"keyword_checklist.txt\"\n MORPHEME_PATH = APP_PATH / \"common\" / \"morpheme_checklist.txt\"\n\n def __init__(self) -> None:\n # used suggested text read style. split() is preferred because it strips 0x0A on end the file\n self.__keyword_list = self.KEYWORD_PATH.read_text().split()\n self.__keyword_list.sort(key=str.__len__, reverse=True)\n self.__keyword_set = set(self.KEYWORD_PATH.read_text().split())\n # The list of morphemes can be combined to form words.\n # The value is considered a variable if at least two exist.\n self.__morpheme_set = set(self.MORPHEME_PATH.read_text().split())\n\n @cached_property\n def keyword_set(self) -> Set[str]:\n \"\"\"Get set with keywords\"\"\"\n return self.__keyword_set\n\n @cached_property\n def keyword_list(self) -> List[str]:\n \"\"\"Get list with keywords in descended order of length\"\"\"\n return self.__keyword_list\n\n @cached_property\n def keyword_len(self) -> int:\n \"\"\"Length of keyword_set\"\"\"\n return len(self.__keyword_set)\n\n @cached_property\n def morpheme_set(self) -> Set[str]:\n \"\"\"Get extended set with keywords.\n\n Return:\n Extended set of strings\n\n \"\"\"\n return self.__morpheme_set\n\n @cached_property\n def morpheme_len(self) -> int:\n \"\"\"Length of morpheme_set\"\"\"\n return len(self.__morpheme_set)\n\n def check_morphemes(self, line_lower: str, threshold: int) -> bool:\n \"\"\"Checks limit of morphemes limit in line.\n\n Args:\n line_lower: input line - MUST be in lower\n threshold: number of minimal morphemes\n\n Return:\n True - if number of morphemes exceeds the threshold\n \"\"\"\n matches = 0\n for keyword in self.morpheme_set:\n if keyword in line_lower:\n matches += 1\n if threshold < matches:\n return True\n return False\n" }, { "path": "credsweeper/common/keyword_checklist.txt", "content": "1234\nabort\nabout\nabove\nabsolute\nabstract\naccent\naccept\naccess\naccount\naction\nactive\nactivity\nactor\nactual\nadded\nadding\nadditional\naddress\nadjust\nadvise\nafter\nagain\nagent\nalert\nalias\nalgori\nallow\nalpha\nalready\nalways\namount\nanalyses\nanalyze\nanchor\nandroid\nanimated\nanimation\nanother\nanony\napache\napi\nappearance\napple\napplication\napply\nare\nargc\nargs\nargv\nargument\narray\narrow\narticle\nascii\naside\nassembly\nasset\nassert\nassign\nassociated\nassociation\natomic\nattachment\nattribute\naudio\nauthor\nauthen\nautomatically\navailable\navatar\navoid\nawait\nawesome\naws\nbackdrop\nbackground\nbackward\nbadge\nbanner\nbased\nbasic\nbeans\nbecause\nbefore\nbegin\nbehind\nbeing\nbelow\nbetween\nbeware\nbinary\nbinding\nbinds\nblah\nblack\nblank\nbless\nblock\nboost\nbool\nborder\nbottle\nbottom\nbound\nbrain\nbranch\nbrand\nbreak\nbreeze\nbrief\nbroker\nbrowse\nbuffer\nbuild\nbundle\nbutton\nbyte\ncache\ncalendar\ncallback\ncalled\ncaller\ncalls\ncamel\ncancel\ncannot\ncanvas\ncapacity\ncapab\ncarat\ncarousel\ncascade\ncases\ncatalog\ncatch\ncategories\ncategory\ncause\ncenter\ncertificate\nchain\nchange\nchannel\nchapter\ncharacter\nchart\ncheck\nchevron\nchild\nchoices\nchomp\nchoose\nchosen\nchrome\nchunk\ncircle\nclang\nclass\nclean\nclear\nclick\nclient\nclock\nclone\nclose\nclosure\ncloud\ncocoa\ncoding\ncollapse\ncollect\ncolor\ncolumn\ncommand\ncomment\ncommit\ncommon\ncompact\ncompare\ncompilation\ncomplete\ncompletion\ncomponent\ncomponents\ncompute\ncondensed\ncondition\nconfig\nconfirm\nconnect\nconsists\nconsole\nconstant\nconstraints\nconsumer\ncontact\ncontain\ncontent\ncontext\ncontinue\ncontrol\nconvenience\nconvert\ncopy\ncookie\ncoordinator\ncorner\ncorrect\ncould\ncount\ncourse\ncover\ncreate\ncreature\ncredential\ncron\ncriteria\ncroak\ncross\ncubic\ncurl\ncurrent\ncustom\ndanger\ndarken\ndashboard\ndashed\ndata\ndeclaration\ndeclared\ndecod\ndecoration\ndefault\ndeferred\ndefine\ndefinition\ndelay\ndelegate\ndelete\ndelivery\ndelta\ndemo\ndependency\ndependent\ndepth\ndescribe\ndescription\ndesigner\ndesktop\ndestination\ndestroy\ndetail\ndevelopment\ndevice\ndevise\ndiagnostic\ndictionary\ndifferent\ndigest\ndirect\ndisable\ndismiss\ndispatch\ndisplay\ndisposable\ndispose\ndisposing\ndistance\ndistribute\ndistribution\ndoctrine\ndocument\ndomain\ndotted\ndouble\ndownload\ndraft\ndriver\ndumps\nduration\nduring\ndword\ndynamic\neasing\neclipse\nediting\neditor\neffect\neither\nelastic\nelement\nemail\nempty\nenable\nencod\nencrypt\nengine\nenrollment\nensure\nentity\nentries\nentry\nenvironment\nequal\nequals\nerase\nerror\nevent\nexample\nexcept\nexclude\nexecute\nexist\nexpand\nexpect\nexplode\nexpir\nexport\nexposed\nexpression\nextend\nextension\nexternal\nextra\nfaces\nfactory\nfailed\nfailure\nfalse\nfamily\nfeature\nfederate\nfeedback\nfetch\nfield\nfigure\nfile\nfiles\nfilename\nfilter\nfinagle\nfinal\nfinish\nfirst\nfixed\nfixture\nflags\nflash\nfloat\nfloor\nfluid\nflush\nfocus\nfolder\nfollow\nfooter\nforce\nformat\nforms\nformula\nforum\nforward\nfound\nfragment\nframe\nfreeze\nfriend\nfulfill\nfunction\nfurnished\nfuture\ngallery\ngateway\ngenerate\ngenerator\ngeneric\ngeometry\ngetter\nget(\ngiven\ngithub\ngitlab\nglobal\ngraphics\ngreen\ngroup\ngrunt\nguard\nhandle\nheader\nheading\nheight\nhello\nhelper\nhidden\nhighlight\nhistory\nholders\nhooks\nhorizontal\nhours\nhover\nhttp\nhtml\nicons\nignore\nimage\nimmediately\nimmutable\nimplemented\nimport\ninclude\nindex\nindicator\ninference\ninfinite\ninfo\ninherit\ninherited\ninitial\ninject\ninner\ninput\ninsert\ninside\ninspect\ninstall\ninstance\ninstead\nintent\ninteraction\nintercept\ninterface\ninternal\ninterrupt\nintro\ninvalid\ninverted\ninvoke\nisolate\nissue\nitem\niterat\nitself\njava\njustified\njustify\nkey\nlabel\nlabels\nlambda\nlanguage\nlarge\nlaunch\nlayer\nlayout\nleader\nleast\nlegend\nlength\nletter\nlevel\nlibrary\nlight\nlimit\nlinear\nlines\nlinks\nlinux\nlistener\nlittle\nloaded\nloading\nloads\nlocal\nlocation\nlogger\nlogin\nlogon\nloose\nlower\nmachine\nmakes\nmanage\nmapping\nmarathon\nmargin\nmark\nmaster\nmatch\nmaterial\nmatrix\nmaximum\nmeans\nmeasure\nmedia\nmedium\nmember\nmemory\nmessage\nmeteor\nmethod\nmethods\nmetro\nmiddle\nmight\nminus\nminutes\nmissing\nmixed\nmobile\nmodel\nmodified\nmodule\nmoment\nmonth\nmount\nmouse\nmultiple\nmutating\nname\nnative\nnavigation\nneeded\nneeds\nnetwork\nneutral\nneutron\nnever\nnexus\nnodes\nnone\nnormal\nnotes\nnothing\nnotice\nnotification\nnull\nnumber\noauth\nobject\noblique\nobserve\nobserver\noccurs\noffline\noffset\noften\nopenssl\noperation\noperator\noption\noracle\norange\norbit\norder\norientation\norigin\norganis\nother\nouter\noutline\noverflow\noverride\noverview\nowner\npackage\npacket\npadding\npager\npages\npalette\npanel\npaper\nparam\nparent\nparse\npartial\nparts\npassed\npassing\npasscode\npassphrase\npassword\npatch\npaths\npattern\npause\npeer\npayload\npayment\npending\npeople\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}, { "path": "credsweeper/common/keyword_pattern.py", "content": "import re\n\n\nclass KeywordPattern:\n \"\"\"Pattern set of keyword types\"\"\"\n directive = r\"(?P(?:\" \\\n r\"(?:[#%]define|define(?=(\\s|\\\\{1,8}[tnr])*\\()|%global)\" \\\n r\"(?:\\s?\\(|\\s|\\\\{1,8}[tnr]){1,8}|\\bset(?=\\b|\\w*(\\s|\\\\{1,8}[tnr])*\\()\" \\\n r\"))?\"\n key_left = r\"(?:\\\\[nrt]|(\\\\\\\\*u00|%)[0-9a-f]{2}|\\s)*\" \\\n r\"(?P(([\\\"'`]{1,8}[^:=\\\"'`}<>\\\\/&?]*|[^:=\\\"'`}<>\\s()\\\\/&?;,%]*)\"\n # keyword will be inserted here\n key_right = r\"[^%:=\\\"'`<>({?!&;\\n]{0,80}\" \\\n r\")\" \\\n r\"(&(quot|apos|#3[49]);|(\\\\\\\\*u00|%)[0-9a-f]{2}|[\\\"'`])*\" \\\n r\")\" # \n separator = r\"(?(directive)|(\\s|\\\\{1,8}[tnr])*\\]?(\\s|\\\\{1,8}[tnr])*)\" \\\n r\"(?P:(\\s[a-z]{3,9}[?]?\\s)?=|:(?!:)|=(>|>|(\\\\\\\\*u00|%)26gt;)|!==|!=|===|==|=~|=\" \\\n r\"|(?(directive)(,|\\\\t|\\s|\\((?!\\))){1,80}|%3d))\" \\\n r\"(\\s|\\\\{1,8}[tnr])*\"\n # might be curly, square or parenthesis with words before\n wrap = r\"(?P(\" \\\n r\"((\\s|\\\\{1,8}[tnr]|new|byte|char|string|\\[\\]){1,8})?\" \\\n r\"(?P([_a-z][0-9a-z_.\\[\\]]*\\.)get|(os\\.)?getenv)?\" \\\n r\"([0-9a-z_.]|::|-(>|>))*\" \\\n r\"\\s*\" \\\n r\"(\\[(?!\\])|\\((?!\\))|\\{(?!\\}))\" \\\n r\"(\\s|\\\\{1,8}[tnr])*\" \\\n r\"(?(get)('[^']{1,31}'|\\\"[^\\\"]{1,31}\\\")\\s*(,|\\)\\s*or)\\s*|)\" \\\n r\"([0-9a-z_]{1,32}\\s*[:=]\\s*)?\" \\\n r\"){1,8})?\"\n string_prefix = r\"(((b|r|br|rb|u|t|f|rf|fr|l|@)(?=(\\\\*[\\\"'`])))?\"\n left_quote = r\"(?P((?P\\\\{1,8})?([\\\"'`]|&(quot|apos|#3[49]);)){1,4}))?\"\n # Authentication scheme ( oauth | basic | bearer | apikey ) precedes to credential\n auth_keywords = r\"(\\s?(oauth|bot|basic|bearer|apikey|accesskey|ssws|ntlm|token)\\s)?\"\n value = r\"(?P\" \\\n r\"(?(value_leftquote)\" \\\n r\"(\" \\\n r\"(?!(?P=value_leftquote))\" \\\n r\"(?(esq)((?!(?P=esq)([\\\"'`]|&(quot|apos|#3[49]);)).)|((?!(?P=value_leftquote)).)))\" \\\n r\"|\" \\\n r\"(?!&(quot|apos|#3[49]);)\" \\\n r\"(\\\\{1,8}([ tnr]|[^\\s\\\"'`])\" \\\n r\"|\" \\\n r\"(?P%[0-9a-f]{2})\" \\\n r\"|\" \\\n r\"(?(url_esc)[^\\s\\\"'`,;\\\\&]|[^\\s\\\"'`,;\\\\])\" \\\n r\")\" \\\n r\"){4,8000}\" \\\n r\"|\" \\\n r\"(<[^>]{4,8000}>)\" \\\n r\"|\" \\\n r\"(\\$?\\({1,3}[^)]{4,8000}\\){1,3})\" \\\n r\"|\" \\\n r\"(\\$?\\{{1,3}[^}]{4,8000}\\}{1,3})\" \\\n r\"|\" \\\n r\"(?(wrap)(?(value_leftquote)(?!\\\\(?P=value_leftquote))|[^\\]\\)\\}]){16,8000})\" \\\n r\")\" # \n right_quote = r\"(?(value_leftquote)\" \\\n r\"(?P(? re.Pattern:\n \"\"\"Returns compiled regex pattern\"\"\"\n expression = ''.join([ #\n cls.directive, #\n cls.key_left, #\n fr\"(?P{keyword})\", # named group required\n cls.key_right, #\n cls.separator, #\n cls.wrap, #\n cls.string_prefix, #\n cls.left_quote, #\n cls.auth_keywords, #\n cls.value, #\n cls.right_quote, #\n ])\n return re.compile(expression, flags=re.IGNORECASE | re.DOTALL)\n" }, { "path": "credsweeper/common/morpheme_checklist.txt", "content": "../\n.com\n.org\n/bin\n/dev\n/etc\n/lib\n/mnt\n/opt\n/sbin\n/srv\n/tmp\n/usr\n/var\n000\n111\n14159265\n18284590\n222\n333\n444\n555\n65358979\n666\n71828182\n777\n80211\n888\n999\n_ack_\n_arg\n_cbc\n_cfg\n_clk\n_con\n_cpu\n_dbg_\n_dev\n_dir\n_div\n_dma\n_drv_\n_env\n_err\n_eth\n_ext\n_fig\n_fmt_\n_ghz\n_i2c_\n_id_\n_if\n_in\n_io_\n_irq\n_is\n_it\n_jpg\n_khz\n_lan\n_led_\n_mem\n_mhz\n_mux\n_num\n_on\n_op_\n_or_\n_pcm_\n_pin\n_pre\n_pro\n_pwr\n_ram\n_reg\n_req\n_ret\n_rev\n_rgb\n_rsa_\n_rw_\n_rx_\n_sdr_\n_src\n_to\n_tx_\n_un\n_up\n_val\n_vol\n_wap\n_wep\n_wpa\n_x64\nabel\nabilit\nable\nably\nabort\nabove\nabsolut\nabstra\nacadem\nacce\nacon\nactiv\nactor\nactual\nactur\nadapt\nadd\nader\nadjust\nadmi\nadver\nadvise\nadvisor\naes256\naffect\nafter\naggre\nagno\naight\naign\nakeup\nalert\nalgo\nalias\nalice\nalign\naling\nall\nalpha\nalter\naltit\namazon\nample\nanali\nanaly\nance\nanchor\nanci\nancy\nand\nanguage\nangular\nanima\nanomaly\nantenna\nanth\nanti\nany\napache\napi\napp\naram\narch\nare\narg_\nargc\nargs\nargv\narian\narker\narpa\narray\narro\nart\nascii\nash\nasia\nasic\nask\nassembl\nassert\nassoc\nasure\nasyn\nately\nathon\natic\natil\nating\natlas\natomic\nator\nattach\nattack\nattend\nattr\natus\naudio\naudit\nauri\nauten\nauth\nauto\naux\navail\navatar\naver\nawesom\naxis\nazure\nback\nbadge\nbalanc\nbank\nbann\nbar\nbas\nbatch\nbatt\nbeac\nbeans\nbeat\nbeef\nbegin\nbehav\nbehind\nbeing\nbelo\nbenutz\nbest\nbias\nbig\nbill\nbin/\nbinar\nbind\nbio\nbipol\nbit\nbixby\nblack\nblan\nbless\nblic\nblish\nblob\nblood\nblue\nboard\nbob\nbody\nbook\nbool\nboost\nboot\nboss\nbot\nboun\nbox\nbranch\nbreak\nbreeze\nbridge\nbrief\nbrit\nbro\nbssid\nbuck\nbuf\nbugs\nbuild\nbuiltin\nbular\nbulk\nbull\nbund\nburst\nbus\nbutor\nbutton\nbyte\ncache\ncalen\ncamel\ncamp\ncan\ncapab\ncapac\ncape\ncaptu\ncarat\ncard\ncarri\ncarry\ncascade\ncase\ncast\ncatch\ncategor\ncative\ncbc_\nccele\nccept\nccess\nceed\ncelebr\ncell\ncenar\ncense\ncent\ncert\ncessor\ncfg_\nchacha\nchain\nchange\nchannel\nchant\nchapter\nchar\ncheck\nchevron\nchild\nchin\nchip\nchoices\nchomp\nchoose\nchosen\nchrom\nchron\nchunk\nciat\ncilla\ncinema\ncircle\ncirrus\ncity\ncket\nclaims\nclan\nclass\nclean\nclear\nclick\nclien\nclip\nclk_\nclose\nclosure\ncloud\nclud\nclus\ncmd\ncocoa\ncode\ncodi\ncogn\ncollaps\ncollect\ncolor\ncolumn\ncomb\ncomi\ncomm\ncompa\ncompet\ncompil\ncompl\ncompo\ncompr\nconc\nconden\nconf\nconnect\nconsist\nconsole\nconst\ncontact\ncontai\nconten\ncontinu\ncontra\ncontri\ncontro\nconven\nconver\ncookie\ncoord\ncopy\ncore\ncorn\ncorrect\ncorrel\ncorres\ncorru\ncost\ncould\ncount\ncourse\ncourt\ncove\ncpu_\ncrac\ncreat\ncred\ncript\ncrit\ncroak\ncron\ncross\ncrypt\ncrystal\nctive\nctrl\ncubic\ncue\ncultur\ncumulat\ncurr\ncurs\ncustom\ncut\ncyan\ncycle\ndaily\ndanger\ndarken\ndarwin\ndas\ndata\ndate\ndavinci\nday\ndead\ndebug\ndecimal\ndecod\ndef\ndelay\ndele\ndeliv\ndelta\ndemo\ndenc\ndens\ndent\ndepen\ndeploy\ndepo\ndepth\nderive\ndesc\ndesired\ndesktop\ndest\ndetach\ndetai\ndetect\ndev/\ndev_\ndevelop\ndevice\ndevise\ndiag\ndial\ndicat\ndict\ndid\ndif\ndig\ndimen\nding\ndiod\ndir_\ndirect\ndisab\ndisc\ndisk\ndismi\ndispos\ndissoc\ndist\nditor\ndity\ndiv_\ndivid\ndma_\ndock\ndocs\ndoct\ndoes\ndog\ndot\ndouble\ndoubt\ndraft\ndragon\ndrift\ndrive\ndroid\ndrop\ndul\ndummy\ndump\ndup\ndurin\ndust\ndvb\ndynamic\ndynamo\neadbee\neasin\neasy\necdhe\necdsa\necret\nected\nector\nectron\neded\nedge\nedit\nedium\neeprom\neffect\negory\nelect\neless\nemai\nemi\nempty\nenabl\nence\nenclave\nencod\nencryp\nency\nende\neness\nengine\nength\nenhanc\nensure\nente\nentit\nentr\nenum\nenv_\nequal\nerase\nerial\nericsson\nerr_\nerror\nerse\nersi\nertise\nesam\nesses\nestima\nesult\netc/\neth_\netic\neting\neutron\neval\nevan\nevent\nexam\nexcee\nexcept\nexclu\nexist\nexit\nexpan\nexpe\nexpir\nexpl\nexpo\nexpr\next_\nexten\nexter\nextra\nexynos\nface\nfact\nfail\nfalse\nfamil\nfar\nfast\nfault\nfavor\nfeatu\nfee\nferr\nfetch\nfied\nfield\nfifo\nfig_\nfigur\nfile\nfill\nfilter\nfinagle\nfinal\nfind\nfine\nfire\nfirm\nfirst\nfix\nflas\nflat\nfleet\nflick\nflix\nfloat\nflood\nfloor\nfluent\nfluid\nflush\nfocus\nfoo\nfor\nfossil\nfoun\nfpga\nfrac\nframe\nfree\nfreq\nfriend\nfrom\nfront\nfrozen\nfujitsu\nfulf\nfull\nfunc\nfurn\nfutu\ngain\ngame\ngang\ngate\ngative\ngauss\ngen\ngeo\ngest\nget\nghbor\nghz_\ngian\nging\ngit\ngiven\nglobal\ngobble\ngood\ngoogle\ngrab\ngrace\ngram\ngrant\ngraph\ngrave\ngray\ngreater\ngreen\ngregat\ngregor\ngress\ngrid\ngro\ngrpc\nguard\nguest\nguid\nguish\nha1-\nha1_\nha2-\nha256\nha2_\nha394\nha512\nhack\nhalf\nhard\nhas\nhave\nhaving\nhavior\nhdmi\nhead\nhealth\nhear\nheight\nhello\nhelp\nherm\nheroku\nhetero\nhex\nhiber\nhidden\nhierar\nhigh\nhisto\nhola\nhome\nhook\nhorizon\nhost\nhoun\nhours\nhtml\nhttp\nhub\nhuman\nhumid\nhybrid\niabl\nical\nicon\nid_rsa\niden\nidle\nieee\nient\nif_\nificat\nignore\nillega\nilor\nimage\nimated\nimer\nimpact\nimple\nimprove\nin_\ninclu\nincom\nindemni\nindex\nindic\nindiv\niness\ninfo\ninfra\ningle\nings\ningular\ninherit\nini\ninjec\ninn\ninsert\ninsig\ninstead\nint\ninval\ninvent\ninver\ninvoke\nion\nipv4\nipv6\niron\nirq_\nis_\nished\niso_\nisolat\nissue\nit_\nitem\niter\nities\niting\nitiv\nivate\nixed\nixtu\nixup\nized\nizer\njabber\njava\nject\njira\njitsi\njob\njoin\njournal\njpeg\njpg_\njson\njump\njustif\nkafka\nkerberos\nkernel\nkey\nkhz_\nkill\nkind\nkinesis\nkirk\nknow\nknox\nkris\nlab\nlag\nlambda\nlan_\nlang\nlarge\nlarval\nlast\nlate\nlatit\nlative\nlaunch\nlayer\nlazy\nlead\nleaf\nleast\nleek\nleft\nlegacy\nlegal\nlend\nleng\nlens\nlet\nlevel\nlexeme\nlexic\nlianc\nliant\nlib/\nlibrary\nlicens\nlies\nlife\nlift\nlight\nlim\nline\nlingu\nlink\nlinux\nlist\nlite\nlittle\nlity\nlive\nlled\nllup\nlness\nload\nlocal\nlock\nlog\nlong\nlook\nloop\nloose\nlost\nlow\nluate\nlysis\nmac\nmagic\nmail\nmain\nmaker\nmakes\nmanage\nmanual\nmanuf\nmap\nmarat\nmargin\nmark\nmary\nmaster\nmatch\nmater\nmatrix\nmax\nmber\nmbin\nmbler\nmean\nmeasur\nmedi\nmedus\nmeet\nmem_\nmemb\nmemo\nment\nmenu\nmerc\nmerge\nmessag\nmeta\nmeteor\nmethod\nmetr\nmhz_\nmicha\nmicro\nmiddle\nmight\nmigrat\nmillis\nmin\nmirror\nmisc\nmiss\nmit\nmix\nmmon\nmmun\nmnt/\nmobile\nmock\nmode\nmodi\nmodu\nmonitor\nmonth\nmorp\nmory\nmote\nmotor\nmount\nmove\nmpeg\nmulti\nmutat\nmute\nmux_\nnalyz\nname\nnary\nnates\nnativ\nnced\nncept\nncies\nndom\nndow\nned\nneed\nneigh\nneo4j\nner\nnet\nneutr\nnever\nnew\nnext\nnexus\nnielsen\nning\nnipp\nnish\nnism\nnode\nnon\nnope\nnorm\nnot\nnsive\nntal\nnter\nnting\nnull\nnum_\nnumb\nnumer\nnuous\nnvram\nobj\noblique\noccur\nocean\nocess\noder\noff\noften\noken\noker\nold\nolygon\non_\noncat\none\nonfig\nonly\nookup\nopen\nopt/\nopted\nopti\noracle\norbi\norder\nordinar\nores\norgan\nories\norigin\norithm\normat\norph\notorola\nottle\nound\nously\nout\nover\nown\npack\npage\npair\npale\npanel\npar\npass\npatch\npath\npatte\npaw\npci\npcmcia\npeer\npenalt\npend\npeople\nper\npets\nphore\nphoton\nphrase\nphys\npick\npills\nping\npipe\npixel\npkcs1\npkcs8\nplace\nplain\nplan\nplay\nplex\nplic\nplod\nplor\nplug\nplus\npoin\npolar\npolic\npoll\npoly\npond\npons\npool\npoon\npop\nport\npose\nposit\npossib\npost\npoun\npower\npre_\npred\nprefi\nprese\npress\nprev\nprice\nprim\nprincip\nprior\npriv\npro_\nprobe\nproblem\nproc\nprod\nprof\nprog\nproj\npromise\nprompt\nprop\nprote\nproto\nprovi\nprox\npseudo\npster\npsycho\npub\npull\npurcha\npurple\npush\nput\npwr_\npython\nqos\nquantum\nqueri\nquery\nqueue\nquick\nquota\nquote\nrabbi\nrack\nradar\nradeon\nradio\nradius\nrage\nrails\nrain\nraise\nram_\nrammar\nrange\nrank\nransit\nrate\nrati\nraw\nrcept\nrchite\nrchive\nreached\nreact\nread\nreal\nreason\nreceive\nrecipe\nrecog\nrecom\nrecord\nredact\nredir\nredisson\nrefer\nreflect\nrefresh\nreg_\nregexp\nregio\nregist\nregs\nregul\nrejec\nrelat\nrelease\nreli\nremar\nremo\nrend\nrent\nrepeat\nrepl\nrepo\nrepre\nreq_\nrequest\nrequire\nresiz\nresolv\nresp\nresul\nret_\nretai\nretriev\nreturn\nrev_\nrevea\nrevel\nreven\nrever\nrevisio\nrevoke\nrgb_\nrick\nride\nright\nrimar\nrime\nrine\nring\nripple\nrish\nrisk\nritte\nrity\nriver\nrize\nroad\nrole\nroll\nroom\nroot\nropo\nrose\nrotat\nrotocol\nrottl\nrough\nroun\nroup\nrow\nrroga\nrrupt\nrticle\nrudder\nrule\nrun\nrxtx\nsabl\nsage\nsalt\nsame\nsampl\nsams\nsaves\nsavi\nscala\nscale\nscali\nscen\nsched\nschem\nscipl\nscont\nscope\nscram\nscreen\nscret\nscri\nscro\nseal\nsearc\nseccomp\nsecond\nsecre\nsect\nsecur\nseed\nseek\nseen\nsegue\nsein\nself\nsema\nsend\nsens\nsent\nseque\nseria\nseries\nserv\nsessio\nset\nsever\nsex\nsha1\nsha2\nsha3\nsha5\nshadow\nshape\nshift\nship\nshoot\nshort\nshot\nshould\nshow\nshut\nsian\nsible\nside\nsight\nsign\nsimilar\nsimpl\nsimul\nsince\nsine\nsing\nsip\nsites\nsize\nsizi\nskip\nslack\nslas\nslave\nsleep\nslice\nslick\nslide\nslot\nsmar\nsmooth\nsnap\nsness\nsniff\nsnip\nsocial\nsock\nsoft\nsolid\nsolve\nsome\nsony\nsort\nsoun\nsource\nspace\nspacing\nspeak\nspec\nspeed\nspell\nspent\nspin\nsplit\nspot\nspray\nsql\nsrc_\nsrv/\nssh\nssl\nstack\nstan\nstar\nstas\nstat\nstdin\nsteer\nstem\nsten\nstep\nstic\nsting\nston\nstop\nstor\nstrai\nstream\nstren\nstretch\nstrob\nstroke\nstrong\nstruct\nstubs\nstude\nstudio\nstuff\nstyle\nsub\nsuccee\nsucces\nsuch\nsuffi\nsuite\nsum\nsun\nsupe\nsupp\nsurro\nsuspe\nswap\nswift\nswing\nswitch\nswizz\nsymbol\nsync\nsynth\nsys\ntabl\ntag\ntail\ntain\ntape\ntate\ntative\nteacher\nteams\ntech\ntele\ntell\ntemp\ntent\ntera\nterm\nternal\ntery\ntest\ntext\nthan\nthat\nthe\nthick\nthing\nthis\nthor\nthose\nthreat\nthree\nthrift\nthro\nthumb\ntial\ntick\ntics\ntifier\ntime\ntimi\ntio\ntish\ntitle\ntitud\ntizen\ntmp/\nto_\ntod\ntoke\ntolera\ntomcat\ntoo\ntopic\ntory\ntorial\ntotal\ntouch\ntour\ntrace\ntract\ntraffic\ntrait\ntral\ntrans\ntreat\ntrial\ntriang\ntribut\ntric\ntries\ntrigger\ntrip\ntrol\ntrouble\ntroy\ntrue\ntrust\ntry\ntter\ntune\ntuni\ntunnel\nture\ntween\ntwenty\ntwitt\ntxrx\ntxt\ntype\ntypo\nultima\nunder\nunfo\nunic\nunio\nunique\nunit\nuniv\nunless\nunpre\nuntil\nunzip\nup_\nupdat\nupgrade\nurl\nusa\nusb\nuse\nusin\nusr/\nuster\nutil\nval_\nvalid\nvalu\nvar/\nvari\nvault\nvect\nveeva\nvendor\nverbose\nverify\nvers\nvert\nvery\nvideo\nview\nviol\nvirtual\nvisibl\nvisit\nvisual\nvita\nvocab\nvoice\nvoid\nvol_\nvolat\nvolume\nvuln\nwait\nwake\nwan\nwap_\nward\nwarm\nwarn\nwatch\nwave\nway\nweak\nweb\nweek\nweight\nwell\nwep_\nwhen\nwhere\nwhich\nwhile\nwhite\nwide\nwidge\nwidth\nwill\nwind\nwire\nwith\nwlan\nwood\nword\nwork\nworld\nwort\nwould\nwow\nwpa_\nwrap\nwrit\nwrong\nx64_\nxpect\nxxx\nyear\nyello\nyield\nyou\nzeppelin\nzero\nzigbee\nzing\nzona\nzorro\n" }, { "path": "credsweeper/config/__init__.py", "content": "" }, { "path": "credsweeper/config/config.py", "content": "import re\nfrom typing import Dict, List, Optional, Set, Any\n\nfrom humanfriendly import parse_size\n\nfrom credsweeper.common.constants import Severity, DEFAULT_PATTERN_LEN\nfrom credsweeper.utils.util import Util\n\n\nclass Config:\n \"\"\"Class that contain configs that can be changed by user.\"\"\"\n\n NOT_ALLOWED_PATH = [\n \".*\\\\.min\\\\.js\", \".*message.*\\\\.properties\", \".*locale.*\\\\.properties\", \".*makefile.*\", \".*package-lock\\\\.json\",\n \".*package\\\\.json\", \".*\\\\.css\", \".*\\\\.scss\"\n ]\n\n def __init__(self, config: Dict[str, Any]) -> None:\n self.exclude_patterns: List[re.Pattern] = [re.compile(pattern) for pattern in config[\"exclude\"][\"pattern\"]]\n self.exclude_paths: List[str] = config[\"exclude\"][\"path\"]\n self.exclude_containers: List[str] = config[\"exclude\"][\"containers\"]\n self.exclude_documents: List[str] = config[\"exclude\"][\"documents\"]\n self.exclude_extensions: List[str] = config[\"exclude\"][\"extension\"]\n self.exclude_lines: Set[str] = set(config[\"exclude\"].get(\"lines\", []))\n self.exclude_values: Set[str] = set(config[\"exclude\"].get(\"values\", []))\n self.source_extensions: List[str] = config[\"source_ext\"]\n self.source_quote_ext: List[str] = config[\"source_quote_ext\"]\n self.find_by_ext_list: List[str] = config[\"find_by_ext_list\"]\n self.bruteforce_list: List[str] = config[\"bruteforce_list\"]\n self.check_for_literals: bool = config[\"check_for_literals\"]\n self.not_allowed_path_pattern = re.compile(f\"{Util.get_regex_combine_or(self.NOT_ALLOWED_PATH)}\",\n flags=re.IGNORECASE)\n self.use_filters: bool = config[\"use_filters\"]\n self.line_data_output: List[str] = config[\"line_data_output\"]\n self.candidate_output: List[str] = config[\"candidate_output\"]\n self.find_by_ext: bool = config[\"find_by_ext\"]\n self.size_limit: Optional[int] = parse_size(config[\"size_limit\"]) if config[\"size_limit\"] is not None else None\n self.pedantic: bool = bool(config[\"pedantic\"])\n self.depth: int = int(config[\"depth\"])\n self.doc: bool = config[\"doc\"]\n self.severity: Severity = Severity.get(config.get(\"severity\"))\n\n self.max_url_cred_value_length: int = int(config[\"max_url_cred_value_length\"])\n self.max_password_value_length: int = int(config[\"max_password_value_length\"])\n\n # Trim exclude patterns from space like characters\n self.exclude_lines = set(line.strip() for line in self.exclude_lines)\n self.exclude_values = set(line.strip() for line in self.exclude_values)\n\n self.pattern_len = config.get(\"pattern_len\", DEFAULT_PATTERN_LEN)\n" }, { "path": "credsweeper/credentials/__init__.py", "content": "" }, { "path": "credsweeper/credentials/augment_candidates.py", "content": "from typing import List\n\nfrom credsweeper.credentials.candidate import Candidate\n\n\ndef augment_candidates(candidates: List[Candidate], new_candidates: List[Candidate]):\n \"\"\"\n Augments candidates with new_candidates if value of line data is not present in the candidates\n\n Args:\n candidates: [IN/OUT] list of candidates to be augmented\n new_candidates: [IN] list with new candidates\n\n \"\"\"\n\n if not new_candidates:\n return\n found_values = set(line_data.value for candidate in candidates #\n for line_data in candidate.line_data_list)\n for new_candidate in new_candidates:\n for line_data in new_candidate.line_data_list:\n if line_data.value not in found_values:\n candidates.append(new_candidate)\n break\n" }, { "path": "credsweeper/credentials/candidate.py", "content": "import copy\nimport re\nfrom json.encoder import py_encode_basestring_ascii\nfrom typing import Any, Dict, List, Optional\n\nfrom credsweeper.common.constants import Severity, Confidence\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\n\n\nclass Candidate:\n \"\"\"Candidates that can be credentials.\n\n Class contains list of LineData, some attributes from Rule object, and config\n\n Parameters:\n line_data_list: List of LineData\n patterns: Regular expressions that can be used for detection\n rule_name: Name of Rule\n severity: critical/high/medium/low\n confidence: strong/moderate/weak\n config: user configs\n use_ml: Whether the candidate should be validated with ML. If not - ml_probability is set None\n \"\"\"\n\n DUMMY_PATTERN = re.compile(r\"^\")\n\n def __init__(self,\n line_data_list: List[LineData],\n patterns: List[re.Pattern],\n rule_name: str,\n severity: Severity,\n config: Optional[Config] = None,\n use_ml: bool = False,\n confidence: Confidence = Confidence.MODERATE) -> None:\n self.line_data_list = line_data_list\n self.patterns = patterns\n self.rule_name = rule_name\n self.severity = severity\n self.config = config\n self.use_ml = use_ml\n self.confidence = confidence\n # None - ML is not applicable or not processed yet; float - the ml decision above ml_threshold\n # Note: -1.0 is possible too for some activation functions in ml model, so let avoid negative values\n self.ml_probability: Optional[float] = None\n\n def compare(self, other: 'Candidate') -> bool:\n \"\"\"Comparison method - checks only result of final cred\"\"\"\n if self.rule_name == other.rule_name \\\n and self.severity == other.severity \\\n and self.confidence == other.confidence \\\n and self.use_ml == other.use_ml \\\n and self.ml_probability == other.ml_probability \\\n and len(self.line_data_list) == len(other.line_data_list):\n for i, j in zip(self.line_data_list, other.line_data_list):\n if i.compare(j):\n continue\n break\n else:\n # all line_data are equal\n return True\n return False\n\n @staticmethod\n def _encode(value: Any) -> Any:\n \"\"\"Encode value to the base string ascii\n\n Args:\n value: Any type of value to be encoded\n \"\"\"\n if isinstance(value, str):\n return py_encode_basestring_ascii(value)\n return value\n\n def to_str(self, subtext: bool = False, hashed: bool = False) -> str:\n \"\"\"Represent candidate with subtext or|and hashed values\"\"\"\n return f\"rule: {self.rule_name}\" \\\n f\" | severity: {self.severity.value}\" \\\n f\" | confidence: {self.confidence.value}\" \\\n f\" | ml_probability: {self.ml_probability}\" \\\n f\" | line_data_list: [{', '.join([x.to_str(subtext, hashed) for x in self.line_data_list])}]\"\n\n def __str__(self):\n return self.to_str()\n\n def __repr__(self):\n return self.to_str(subtext=True)\n\n def to_json(self, hashed: bool, subtext: bool) -> Dict:\n \"\"\"Convert credential candidate object to dictionary.\n\n Return:\n Dictionary object generated from current credential candidate\n\n \"\"\"\n full_output = {\n \"patterns\": [pattern.pattern for pattern in self.patterns],\n \"rule\": self.rule_name,\n \"severity\": self.severity.value,\n \"confidence\": self.confidence.value,\n \"use_ml\": self.use_ml,\n \"ml_probability\": self.ml_probability,\n # put the array to end to make json more readable\n \"line_data_list\": [line_data.to_json(hashed, subtext) for line_data in self.line_data_list],\n }\n if self.config is not None:\n reported_output = {k: v for k, v in full_output.items() if k in self.config.candidate_output}\n else:\n reported_output = full_output\n return reported_output\n\n def to_dict_list(self, hashed: bool, subtext: bool) -> List[dict]:\n \"\"\"Convert credential candidate object to List[dict].\n\n Return:\n List[dict] object generated from current credential candidate\n\n \"\"\"\n reported_output = []\n json_output = self.to_json(hashed, subtext)\n refined_data = copy.deepcopy(json_output)\n del refined_data[\"line_data_list\"]\n for line_data in json_output[\"line_data_list\"]:\n line_data.update(refined_data)\n for key in line_data.keys():\n line_data[key] = self._encode(line_data[key])\n reported_output.append(line_data)\n return reported_output\n\n @classmethod\n def get_dummy_candidate(cls, config: Config, file_path: str, file_type: str, info: str, rule_name: str):\n \"\"\"Create dummy instance to use in searching file by extension\"\"\"\n return cls( #\n line_data_list=[LineData(config, '', -1, 0, file_path, file_type, info, cls.DUMMY_PATTERN)],\n patterns=[cls.DUMMY_PATTERN], #\n rule_name=rule_name, #\n severity=Severity.INFO, #\n config=config, #\n confidence=Confidence.WEAK)\n" }, { "path": "credsweeper/credentials/candidate_group_generator.py", "content": "from typing import Dict, List, Tuple\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.candidate_key import CandidateKey\n\n\nclass CandidateGroupGenerator:\n \"\"\"CandidateGroupGenerator\"\"\"\n\n def __init__(self) -> None:\n self.grouped_candidates: Dict[CandidateKey, List[Candidate]] = {}\n\n @property\n def grouped_candidates(self) -> Dict[CandidateKey, List[Candidate]]:\n \"\"\"property getter\"\"\"\n return self._grouped_candidates\n\n @grouped_candidates.setter\n def grouped_candidates(self, grouped_candidates: Dict[CandidateKey, List[Candidate]]) -> None:\n \"\"\"property setter\"\"\"\n self._grouped_candidates = grouped_candidates\n\n def __contains__(self, key: CandidateKey) -> bool:\n return key in self.grouped_candidates\n\n def __getitem__(self, key) -> List[Candidate]:\n return self.grouped_candidates[key]\n\n def __setitem__(self, key: CandidateKey, value: List[Candidate]) -> None:\n self.grouped_candidates[key] = value\n\n def __len__(self) -> int:\n return len(self.grouped_candidates)\n\n def items(self) -> List[Tuple[CandidateKey, List[Candidate]]]:\n \"\"\"getter\"\"\"\n return list(self.grouped_candidates.items())\n" }, { "path": "credsweeper/credentials/candidate_key.py", "content": "from typing import Tuple\n\nfrom credsweeper.credentials.line_data import LineData\n\n\nclass CandidateKey:\n \"\"\"Class used to identify credential candidates.\n\n Candidates that detected same value on same string in a same file would have identical CandidateKey\n \"\"\"\n\n def __init__(self, line_data: LineData):\n self.path: str = line_data.path\n self.line_num: int = line_data.line_num\n self.value_start: int = line_data.value_start\n self.value_end: int = line_data.value_end\n self.key: Tuple[str, int, int, int] = (self.path, self.line_num, self.value_start, self.value_end)\n self.__line = line_data.line\n\n def __hash__(self):\n return hash(self.key)\n\n def __eq__(self, other):\n return self.key == other.key\n\n def __ne__(self, other):\n return not bool(self == other)\n\n def __repr__(self) -> str:\n return f\"{self.key}:{self.__line}\"\n" }, { "path": "credsweeper/credentials/credential_manager.py", "content": "import logging\nfrom multiprocessing import Manager\nfrom typing import List, Dict, Tuple\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.candidate_group_generator import CandidateGroupGenerator, CandidateKey\n\nlogger = logging.getLogger(__name__)\n\n\nclass CredentialManager:\n \"\"\"The manager allows you to store, add and delete separate credit candidates.\"\"\"\n\n def __init__(self) -> None:\n self.candidates: List[Candidate] = list(Manager().list())\n\n def clear_credentials(self) -> None:\n \"\"\"Clear credential candidates stored in the manager.\"\"\"\n self.candidates.clear()\n\n def len_credentials(self) -> int:\n \"\"\"Get number of credential candidates stored in the manager.\n\n Return:\n Non-negative integer\n\n \"\"\"\n return len(self.candidates)\n\n def get_credentials(self) -> List[Candidate]:\n \"\"\"Get all credential candidates stored in the manager.\n\n Return:\n List with all Candidate objects stored in manager\n\n \"\"\"\n return self.candidates\n\n def set_credentials(self, candidates: List[Candidate]) -> None:\n \"\"\"Remove all current credentials candidates from the manager and add new credentials.\n\n Args:\n candidates: List with candidates to replace current candidates in the manager\n\n \"\"\"\n self.candidates = candidates\n\n def add_credential(self, candidate: Candidate) -> None:\n \"\"\"Add credential candidate to the manager.\n\n Args:\n candidate: credential candidate to be added\n\n \"\"\"\n self.candidates.append(candidate)\n\n def remove_credential(self, candidate: Candidate) -> None:\n \"\"\"Remove credential candidate from the manager.\n\n Args:\n candidate: credential candidate to be removed\n\n \"\"\"\n self.candidates.remove(candidate)\n\n def purge_duplicates(self) -> int:\n \"\"\"Purge duplicates candidates which may appear in overlaps during long line scan.\n\n Returns: number of removed duplicates\n \"\"\"\n candidates_dict: Dict[Tuple[str, str, str, int, int, int, int, int, int, int], Candidate] = {}\n before = len(self.candidates)\n for i in self.candidates:\n ld = i.line_data_list[0]\n candidate_key = (\n i.rule_name, #\n ld.path, #\n ld.info, #\n ld.line_pos, #\n ld.variable_start, #\n ld.variable_end, #\n ld.separator_start, #\n ld.separator_end, #\n ld.value_start, #\n ld.value_end)\n if candidate_key in candidates_dict:\n # check precisely - compare with the values\n candidate_dict = candidates_dict[candidate_key]\n if not candidate_dict.compare(i):\n ld_ = candidate_dict.line_data_list[0]\n logger.warning(\"Check %s and %s\", (ld_.variable, ld_.value), (ld.variable, ld.value))\n else:\n candidates_dict[candidate_key] = i\n self.candidates = list(candidates_dict.values())\n after = len(self.candidates)\n return before - after\n\n def group_credentials(self) -> CandidateGroupGenerator:\n \"\"\"Join candidates that reference same secret value in the same line.\n\n Candidate can belong to two groups in the same time if it has more than one LineData object inside\n\n Return:\n Contain dictionary of [path, line_num, value] -> credential candidates list\n\n \"\"\"\n groups = CandidateGroupGenerator()\n for credential_candidate in self.get_credentials():\n for line_data in credential_candidate.line_data_list[:1]:\n # Match by file path+line num+value. Value required so two different credentials still be\n # processed independently\n candidate_key = CandidateKey(line_data)\n if candidate_key in groups:\n groups[candidate_key].append(credential_candidate)\n else:\n groups[candidate_key] = [credential_candidate]\n return groups\n" }, { "path": "credsweeper/credentials/line_data.py", "content": "import contextlib\nimport hashlib\nimport re\nimport string\nfrom functools import cached_property\nfrom typing import Any, Dict, Optional, Tuple\n\nfrom colorama import Fore, Style\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH, UTF_8, StartEnd, ML_HUNK\nfrom credsweeper.config.config import Config\nfrom credsweeper.utils.util import Util\n\n\nclass LineData:\n \"\"\"Object to treat and store scanned line related data.\n\n Parameters:\n key: Optional[str] = None\n line: string variable, line\n line_num: int variable, number of line in file\n path: string variable, path to file\n file_type: string variable, extension of file '.txt'\n info: additional info about how the data was detected\n pattern: regex pattern, detected pattern in line\n separator: optional string variable, separators between variable and value\n separator_start: optional variable, separator position start\n value: optional string variable, detected value in line\n variable: optional string variable, detected variable in line\n\n \"\"\"\n\n quotation_marks = ('\"', \"'\", '`')\n comment_starts = (\"//\", \"* \", \"# \", \"/*\", \"|\\\\w+?\\\\>|\\\\&)\")\n line_endings = re.compile(r\"\\\\{1,8}[nr]\")\n # https://en.wikipedia.org/wiki/Percent-encoding\n url_percent_split = re.compile(r\"%(21|23|24|26|27|28|29|2a|2b|2c|2f|3a|3b|3d|3f|40|5b|5d)\", flags=re.IGNORECASE)\n url_unicode_split = re.compile(r\"\\\\u00(0000)?(21|23|24|26|27|28|29|2a|2b|2c|2f|3a|3b|3d|3f|40|5b|5d)\",\n flags=re.IGNORECASE)\n # some symbols e.g. double quotes cannot be in URL string https://www.ietf.org/rfc/rfc1738.txt\n # \\ - was added for case of url in escaped string \\u0026amp; - means escaped & in HTML\n url_scheme_part_regex = re.compile(r\"[0-9A-Za-z.-]{3}\")\n url_chars_not_allowed_pattern = re.compile(r'[\\s\"<>\\[\\]^~`{|}]')\n url_value_pattern = re.compile(r'[^\\s&;\"<>\\[\\]^~`{|}]+[&;][^\\s=;\"<>\\[\\]^~`{|}]{3,80}=[^\\s;&=\"<>\\[\\]^~`{|}]{1,80}')\n variable_strip_pattern = string.whitespace + \"\"\",'\"-;\"\"\"\n\n INITIAL_WRONG_POSITION = -3\n EXCEPTION_POSITION = -2\n\n def __init__(\n self, #\n config: Config, #\n line: str, #\n line_pos: int, #\n line_num: int, #\n path: str, #\n file_type: str, #\n info: str, #\n pattern: re.Pattern, #\n match_obj: Optional[re.Match] = None) -> None:\n self.config = config\n self.line: str = line\n self.line_pos: int = line_pos\n self.line_num: int = line_num\n self.path: str = path\n self.file_type: str = file_type\n self.info: str = info\n self.pattern: re.Pattern = pattern\n # do not store match object due it cannot be pickled with multiprocessing\n\n # start - end position of matched object\n self.value_start = LineData.INITIAL_WRONG_POSITION\n self.value_end = LineData.INITIAL_WRONG_POSITION\n self.key: Optional[str] = None\n self.separator: Optional[str] = None\n self.separator_start: int = LineData.INITIAL_WRONG_POSITION\n self.separator_end: int = LineData.INITIAL_WRONG_POSITION\n self.value: Optional[str] = None\n self.variable: Optional[str] = None\n self.variable_start = LineData.INITIAL_WRONG_POSITION\n self.variable_end = LineData.INITIAL_WRONG_POSITION\n self.value_leftquote: Optional[str] = None\n self.value_rightquote: Optional[str] = None\n # is set when variable & value are in URL for any source type\n self.url_part = False\n self.wrap = None\n self._3d_escaped_separator = False\n self.initialize(match_obj)\n # the line is very useful for debug breakpoint\n pass # pylint: disable=W0107\n\n def compare(self, other: 'LineData') -> bool:\n \"\"\"Comparison method - skip whole line and checks only when variable and value are the same\"\"\"\n if self.path == other.path \\\n and self.info == other.info \\\n and self.line_num == other.line_num \\\n and self.value_start == other.value_start \\\n and self.variable == other.variable \\\n and self.value == other.value:\n return True\n return False\n\n def initialize(self, match_obj: Optional[re.Match] = None) -> None:\n \"\"\"Apply regex to the candidate line and set internal fields based on match.\"\"\"\n if not isinstance(match_obj, re.Match) and isinstance(self.pattern, re.Pattern):\n match_obj = self.pattern.search(self.line, endpos=MAX_LINE_LENGTH)\n if match_obj is None:\n return\n\n def get_group_from_match_obj(_match_obj: re.Match, group: str) -> Any:\n with contextlib.suppress(Exception):\n return _match_obj.group(group)\n return None\n\n def get_span_from_match_obj(_match_obj: re.Match, group: str) -> Tuple[int, int]:\n with contextlib.suppress(Exception):\n span = _match_obj.span(group)\n return span[0], span[1]\n return LineData.EXCEPTION_POSITION, LineData.EXCEPTION_POSITION\n\n self.key = get_group_from_match_obj(match_obj, \"keyword\")\n self.separator = get_group_from_match_obj(match_obj, \"separator\")\n self.separator_start, self.separator_end = get_span_from_match_obj(match_obj, \"separator\")\n self.value = get_group_from_match_obj(match_obj, \"value\")\n self.value_start, self.value_end = get_span_from_match_obj(match_obj, \"value\")\n self.variable = get_group_from_match_obj(match_obj, \"variable\")\n self.variable_start, self.variable_end = get_span_from_match_obj(match_obj, \"variable\")\n self.value_leftquote = get_group_from_match_obj(match_obj, \"value_leftquote\")\n self.value_rightquote = get_group_from_match_obj(match_obj, \"value_rightquote\")\n self.wrap = get_group_from_match_obj(match_obj, \"wrap\")\n # percent encoded '=' in url\n self._3d_escaped_separator = bool(self.separator) and \"%3D\" == self.separator.upper()\n self.sanitize_value()\n self.sanitize_variable()\n\n def sanitize_value(self):\n \"\"\"Clean found value from extra artifacts. Correct positions if changed.\"\"\"\n # process the quotation workaround before cached properties invocation\n if not self.value_leftquote and not self.value_rightquote:\n while self.value:\n first_symbol_code = ord(self.value[0])\n last_symbol_code = ord(self.value[-1])\n if 0x2018 <= first_symbol_code <= 0x201B and 0x2018 <= last_symbol_code <= 0x201B:\n self.value_leftquote = self.value_rightquote = \"'\"\n self.value = self.value[:-1]\n self.value_end -= 1\n self.value = self.value[1:]\n self.value_start += 1\n elif 0x201C <= first_symbol_code <= 0x201F and 0x201C <= last_symbol_code <= 0x201F:\n self.value_leftquote = self.value_rightquote = '\"'\n self.value = self.value[1:]\n self.value_start += 1\n self.value = self.value[:-1]\n self.value_end -= 1\n else:\n break\n\n if self.variable and self.value and not self.is_well_quoted_value:\n # sanitize is actual step for keyword pattern only\n _value = self.value\n self.clean_url_parameters()\n self.clean_bash_parameters()\n self.clean_toml_parameters()\n self.clean_tag_parameters()\n if 0 <= self.value_start and 0 <= self.value_end and len(self.value) < len(_value):\n start = _value.find(self.value)\n self.value_start += start\n self.value_end = self.value_start + len(self.value)\n\n def check_url_part(self) -> bool:\n \"\"\"Determines whether value is part of url like line\"\"\"\n line_before_value = self.line[:self.value_start]\n url_pos = -1\n find_pos = 0\n while find_pos < self.value_start:\n # find rightmost pattern\n find_pos = line_before_value.find(\"://\", find_pos)\n if -1 == find_pos:\n break\n url_pos = find_pos\n find_pos += 3\n # whether the line has url start pattern\n self.url_part = 3 <= url_pos\n self.url_part &= bool(self.url_scheme_part_regex.match(line_before_value, pos=url_pos - 3, endpos=url_pos))\n self.url_part &= not self.url_chars_not_allowed_pattern.search(line_before_value, pos=url_pos + 3)\n self.url_part |= self.line[self.variable_start - 1] in \"?&\" if 0 < self.variable_start else False\n self.url_part |= bool(self.url_value_pattern.match(self.value))\n self.url_part |= self._3d_escaped_separator\n return self.url_part\n\n def clean_url_parameters(self) -> None:\n \"\"\"Clean url address from 'query parameters'.\n\n If line seem to be a URL - split by & character.\n Variable should be right most value after & or ? ([-1]). And value should be left most before & ([0])\n \"\"\"\n # skip sanitize in case of URL credential rule - the regex is mature enough\n if self.check_url_part() and not self.variable.endswith(\"://\"):\n # all checks have passed - line before the value may be a URL\n self.variable = self.variable.rsplit('&')[-1].rsplit('?')[-1].rsplit(';')[-1]\n self.value = self.value.split('&', maxsplit=1)[0].split(';', maxsplit=1)[0].split('#', maxsplit=1)[0]\n self.value = self.url_unicode_split.split(self.value)[0]\n if self._3d_escaped_separator:\n self.value = self.url_percent_split.split(self.value)[0]\n\n def clean_bash_parameters(self) -> None:\n \"\"\"Split variable and value by bash special characters, if line assumed to be CLI command.\"\"\"\n if self.variable.startswith(\"-\"):\n value_spl = self.bash_param_split.split(self.value)\n # If variable name starts with `-` (usual case for args in CLI)\n # and value can be split by bash special characters\n if len(value_spl) > 1:\n self.value = value_spl[0]\n if ' ' not in self.value and (\"\\\\n\" in self.value or \"\\\\r\" in self.value):\n value_whsp = self.line_endings.split(self.value)\n if len(value_whsp) > 1:\n self.value = value_whsp[0]\n\n def clean_toml_parameters(self) -> None:\n \"\"\"Parenthesis, curly and squared brackets may be caught in TOML format and bash. Simple clearing\"\"\"\n cleaning_required = self.value and self.value[-1] in ['}', ']', ')']\n line_before_value = self.line[:self.value_start] if self.value_start and 0 <= self.value_start else \"\"\n while cleaning_required:\n cleaning_required = False\n for left, right in [('{', '}'), ('[', ']'), ('(', ')')]:\n if self.value.endswith(right) and left not in self.value \\\n and line_before_value.count(left) > line_before_value.count(right):\n # full match does not reasonable to implement due open character may be in other line\n self.value = self.value[:-1]\n cleaning_required = True\n\n def clean_tag_parameters(self) -> None:\n \"\"\"Remove closing tag from value if the opened is somewhere before in line\"\"\"\n cleaning_required = self.value and self.value.endswith('>')\n while cleaning_required:\n closing_tag_pos = self.value.rfind(\"')\n else:\n break\n\n def sanitize_variable(self) -> None:\n \"\"\"Remove trailing spaces, dashes and quotations around the variable. Correct position.\"\"\"\n sanitized_var_len = 0\n variable = self.variable\n while self.variable and sanitized_var_len != len(self.variable):\n sanitized_var_len = len(self.variable)\n self.variable = self.variable.strip(self.variable_strip_pattern)\n if self.variable.endswith('\\\\'):\n self.variable = self.variable[:-1]\n if self.variable.startswith('{') and '}' in self.line[self.variable_end:]:\n # TOML case\n self.variable = self.variable[1:]\n if variable and len(self.variable) < len(variable) and 0 <= self.variable_start and 0 <= self.variable_end:\n start = variable.find(self.variable)\n self.variable_start += start\n self.variable_end = self.variable_start + len(self.variable)\n\n def is_comment(self) -> bool:\n \"\"\"Check if line with credential is a comment.\n\n Return:\n True if line is a comment, False otherwise\n\n \"\"\"\n cleaned_line = self.line.strip()\n for comment_start in self.comment_starts:\n if cleaned_line.startswith(comment_start):\n return True\n return False\n\n @cached_property\n def is_well_quoted_value(self) -> bool:\n \"\"\"Well quoted value - means the value has been quoted or has line wrap\"\"\"\n result = False\n if self.value_leftquote and self.value_rightquote:\n if self.value_leftquote == self.value_rightquote:\n # regex caught well\n return True\n\n if 1 == len(self.value_leftquote):\n leftquote = self.value_leftquote\n else:\n # right side symbol should be a quote\n leftquote = self.value_leftquote[-1]\n if leftquote not in self.quotation_marks:\n leftquote = \"\"\n\n if 1 == len(self.value_rightquote):\n rightquote = self.value_rightquote\n else:\n # clean \\ sign in escaping text\n for q in self.value_rightquote:\n if q in self.quotation_marks:\n rightquote = q\n break\n else:\n rightquote = \"\"\n\n result = bool(leftquote) and ( #\n bool(rightquote) and (leftquote == rightquote) # normal case\n or '\\\\' == self.value_rightquote and '\\\\' == self.line[-1] # line wrap\n )\n\n elif self.value_leftquote:\n result = ( #\n ('\\\\' == self.value_rightquote or '\\\\' == self.value[-1]) and '\\\\' == self.line[-1] # line wrap\n or '.php' == self.file_type # php may use multiline string\n or 3 == self.value_leftquote.count('\"') or 3 == self.value_leftquote.count(\"'\") # python multiline\n )\n\n return result\n\n @cached_property\n def is_quoted(self) -> bool:\n \"\"\"Check if variable and value in a quoted string.\n\n Return:\n True if candidate in a quoted string, False otherwise\n\n \"\"\"\n left_quote = None\n if 0 < self.variable_start:\n for i in self.line[:self.variable_start]:\n if i in ('\"', \"'\", '`'):\n left_quote = i\n break\n right_quote = None\n if len(self.line) > self.value_end:\n for i in self.line[self.value_end:]:\n if i in ('\"', \"'\", '`'):\n right_quote = i\n break\n result = bool(left_quote) and bool(right_quote) and left_quote == right_quote\n return result\n\n def is_source_file(self) -> bool:\n \"\"\"Check if file with credential is a source code file or not (data, log, plain text).\n\n Return:\n True if file is source file, False otherwise\n\n \"\"\"\n if not self.path:\n return False\n if Util.get_extension(self.path) in self.config.source_extensions:\n return True\n return False\n\n def is_source_file_with_quotes(self) -> bool:\n \"\"\"Check if file with credential require quotation for string literals.\n\n Return:\n True if file require quotation, False otherwise\n\n \"\"\"\n file_type = self.file_type or Util.get_extension(self.path)\n return bool(file_type) and file_type in self.config.source_quote_ext\n\n @staticmethod\n def get_hash_or_subtext(\n text: Optional[str], #\n hashed: bool, #\n cut_pos: Optional[StartEnd] = None, #\n ) -> Optional[str]:\n \"\"\"Represent not empty text with hash or a \"beauty\" subtext if required\n\n Args:\n text: str - input string\n hashed: bool - whether the text will be hashed and returned\n cut_pos: Optional[StartEnd] - start, end positions which text must be kept in output\n\n Return:\n sha256 hash in hex representation of input text with UTF-8 encodings\n or\n subtext from start to end, or original text as is\n\n \"\"\"\n if text:\n if hashed:\n text = hashlib.sha256(text.encode(UTF_8, errors=\"strict\")).hexdigest()\n elif cut_pos is not None:\n if 2 * ML_HUNK < cut_pos.end - cut_pos.start:\n # subtext positions exceed the limit\n text = text[cut_pos.start:cut_pos.end]\n else:\n strip_text = text.strip()\n if 2 * ML_HUNK >= len(strip_text):\n # stripped text length meets the limit\n text = strip_text\n else:\n offset = len(text) - len(text.lstrip())\n center = (cut_pos.end + cut_pos.start - offset) >> 1\n text = Util.subtext(strip_text, center, ML_HUNK)\n return text\n\n def to_str(self, subtext: bool = False, hashed: bool = False) -> str:\n \"\"\"Represent line_data with subtext or|and hashed values\"\"\"\n cut_pos = StartEnd(self.variable_start, self.value_end) if subtext else None\n return f\"path: {self.path}\" \\\n f\" | line_num: {self.line_num}\" \\\n f\" | value: '{self.get_hash_or_subtext(self.value, hashed)}'\" \\\n f\" | line: '{self.get_hash_or_subtext(self.line, hashed, cut_pos)}'\"\n\n def __str__(self):\n return self.to_str()\n\n def __repr__(self):\n return self.to_str(subtext=True)\n\n def to_json(self, hashed: bool, subtext: bool) -> Dict:\n \"\"\"Convert line data object to dictionary.\n\n Return:\n Dictionary object generated from current line data\n\n \"\"\"\n cut_pos = StartEnd(self.variable_start if 0 <= self.variable_start else self.value_start,\n self.value_end) if subtext else None\n if isinstance(self.value, str):\n entropy = round(Util.get_shannon_entropy(self.value), 5)\n else:\n entropy = None\n full_output = {\n \"key\": self.key,\n \"line\": self.get_hash_or_subtext(self.line, hashed, cut_pos),\n \"line_num\": self.line_num,\n \"path\": self.path,\n # info may contain variable name - so let it be hashed if requested\n \"info\": self.get_hash_or_subtext(self.info, hashed),\n \"pattern\": self.pattern.pattern,\n \"variable\": self.get_hash_or_subtext(self.variable, hashed),\n \"variable_start\": self.variable_start,\n \"variable_end\": self.variable_end,\n \"separator\": self.separator,\n \"separator_start\": self.separator_start,\n \"separator_end\": self.separator_end,\n \"value\": self.get_hash_or_subtext(self.value, hashed),\n \"value_start\": self.value_start,\n \"value_end\": self.value_end,\n \"entropy\": entropy,\n \"value_leftquote\": self.value_leftquote,\n \"value_rightquote\": self.value_rightquote,\n }\n reported_output = {k: v for k, v in full_output.items() if k in self.config.line_data_output}\n return reported_output\n\n def get_colored_line(self, hashed: bool, subtext: bool = False) -> str:\n \"\"\"Represents the LineData with a value, separator, and variable color formatting\"\"\"\n if hashed:\n # return colored hash\n return Fore.LIGHTGREEN_EX \\\n + self.get_hash_or_subtext(self.line, hashed,\n StartEnd(self.value_start, self.value_end) if subtext else None) \\\n + Style.RESET_ALL\n # at least, value must present\n line = self.line[:self.value_start] \\\n + Fore.LIGHTYELLOW_EX \\\n + self.line[self.value_start:self.value_end] \\\n + Style.RESET_ALL \\\n + self.line[self.value_end:] # noqa: E127\n # separator may be missing\n if 0 <= self.separator_start < self.separator_end <= self.value_start:\n line = line[:self.separator_start] \\\n + Fore.LIGHTGREEN_EX \\\n + line[self.separator_start:self.separator_end] \\\n + Style.RESET_ALL \\\n + line[self.separator_end:]\n # variable may be missing\n if 0 <= self.separator_start \\\n and 0 <= self.variable_start < self.variable_end <= self.separator_end <= self.value_start \\\n or 0 <= self.variable_start < self.variable_end <= self.value_start:\n line = line[:self.variable_start] \\\n + Fore.LIGHTBLUE_EX \\\n + line[self.variable_start:self.variable_end] \\\n + Style.RESET_ALL \\\n + line[self.variable_end:]\n if subtext:\n # display part of the text, centered around the start of the value, style reset at the end as a fallback\n line = f\"{Util.subtext(line, self.value_start + len(line) - len(self.line), ML_HUNK)}{Style.RESET_ALL}\"\n return line\n" }, { "path": "credsweeper/deep_scanner/__init__.py", "content": "" }, { "path": "credsweeper/deep_scanner/abstract_scanner.py", "content": "import contextlib\nimport datetime\nimport logging\nfrom abc import abstractmethod, ABC\nfrom typing import List, Optional, Tuple, Any, Generator\n\nfrom credsweeper.common.constants import RECURSIVE_SCAN_LIMITATION, MIN_DATA_LEN, DEFAULT_ENCODING, UTF_8, \\\n MIN_VALUE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.augment_candidates import augment_candidates\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom credsweeper.file_handler.diff_content_provider import DiffContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\nfrom credsweeper.file_handler.text_content_provider import TextContentProvider\nfrom credsweeper.scanner.scanner import Scanner\n\nlogger = logging.getLogger(__name__)\n\n\nclass AbstractScanner(ABC):\n \"\"\"Base abstract class for all recursive scanners\"\"\"\n\n @property\n @abstractmethod\n def config(self) -> Config:\n \"\"\"Abstract property to be defined in DeepScanner\"\"\"\n raise NotImplementedError(__name__)\n\n @property\n @abstractmethod\n def scanner(self) -> Scanner:\n \"\"\"Abstract property to be defined in DeepScanner\"\"\"\n raise NotImplementedError(__name__)\n\n @abstractmethod\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Abstract method to be defined in DeepScanner\"\"\"\n raise NotImplementedError(__name__)\n\n @staticmethod\n @abstractmethod\n def get_deep_scanners(data: bytes, descriptor: Descriptor, depth: int) -> Tuple[List[Any], List[Any]]:\n \"\"\"Returns possibly scan methods for the data depends on content and fallback scanners\"\"\"\n raise NotImplementedError(__name__)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def recursive_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int = 0, #\n recursive_limit_size: int = 0) -> List[Candidate]:\n \"\"\"Recursive function to scan files which might be containers like ZIP archives\n\n Args:\n data_provider: DataContentProvider object may be a container\n depth: maximal level of recursion\n recursive_limit_size: maximal bytes of opened files to prevent recursive zip-bomb attack\n \"\"\"\n candidates: List[Candidate] = []\n if 0 > depth:\n # break recursion if maximal depth is reached\n logger.debug(\"Bottom reached %s recursive_limit_size:%d\", data_provider.file_path, recursive_limit_size)\n return candidates\n depth -= 1\n if MIN_DATA_LEN > len(data_provider.data):\n # break recursion for minimal data size\n logger.debug(\"Too small data: size=%d, depth=%d, limit=%d, path=%s, info=%s\", len(data_provider.data),\n depth, recursive_limit_size, data_provider.file_path, data_provider.info)\n return candidates\n logger.debug(\"Start data_scan: size=%d, depth=%d, limit=%d, path=%s, info=%s\", len(data_provider.data), depth,\n recursive_limit_size, data_provider.file_path, data_provider.info)\n\n if FilePathExtractor.is_find_by_ext_file(self.config, data_provider.file_type):\n # Skip scanning file and makes fake candidate due the extension is suspicious\n dummy_candidate = Candidate.get_dummy_candidate(self.config, data_provider.file_path,\n data_provider.file_type, data_provider.info,\n FilePathExtractor.FIND_BY_EXT_RULE)\n candidates.append(dummy_candidate)\n else:\n new_candidates = self.deep_scan_with_fallback(data_provider, depth, recursive_limit_size)\n augment_candidates(candidates, new_candidates)\n\n return candidates\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @staticmethod\n def key_value_combination(structure: dict) -> Generator[Tuple[Any, Any], None, None]:\n \"\"\"Combine items by `key` and `value` from a dictionary for augmentation\n {..., \"key\": \"api_key\", \"value\": \"XXXXXXX\", ...} -> (\"api_key\", \"XXXXXXX\")\n\n \"\"\"\n for key_id in (\"key\", \"KEY\", \"Key\"):\n if key_id in structure:\n struct_key = structure.get(key_id)\n break\n else:\n struct_key = None\n if isinstance(struct_key, bytes):\n # sqlite table may produce bytes for `key`\n with contextlib.suppress(UnicodeError):\n struct_key = struct_key.decode(UTF_8)\n # only str type is common used for the augmentation\n if struct_key and isinstance(struct_key, str):\n for value_id in (\"value\", \"VALUE\", \"Value\"):\n if value_id in structure:\n struct_value = structure.get(value_id)\n if struct_value and isinstance(struct_value, (str, bytes)):\n yield struct_key, struct_value\n # break in successful case\n break\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @staticmethod\n def structure_processing(structure: Any) -> Generator[Tuple[Any, Any], None, None]:\n \"\"\"Yields pair `key, value` from given structure if applicable\"\"\"\n if isinstance(structure, dict):\n # transform dictionary to list\n for key, value in structure.items():\n if not value:\n # skip empty values\n continue\n if isinstance(value, (list, tuple)):\n if 1 == len(value):\n # simplify some structures like YAML when single item in new line is a value\n yield key, value[0]\n continue\n # all other data will be precessed in next code\n yield key, value\n yield from AbstractScanner.key_value_combination(structure)\n elif isinstance(structure, (list, tuple)):\n # enumerate the items to fit for return structure\n for key, value in enumerate(structure):\n yield key, value\n else:\n logger.warning(\"Not supported type:%s val:%s\", str(type(structure)), repr(structure))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def structure_scan(\n self, #\n struct_provider: StructContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> List[Candidate]:\n \"\"\"Recursive function to scan structured data\n\n Args:\n struct_provider: DataContentProvider object may be a container\n depth: maximal level of recursion\n recursive_limit_size: maximal bytes of opened files to prevent recursive zip-bomb attack\n \"\"\"\n candidates: List[Candidate] = []\n logger.debug(\"Start struct_scan: depth=%d, limit=%d, path=%s, info=%s\", depth, recursive_limit_size,\n struct_provider.file_path, struct_provider.info)\n\n if 0 > depth:\n # break recursion if maximal depth is reached\n logger.debug(\"Bottom reached %s recursive_limit_size:%d\", struct_provider.file_path, recursive_limit_size)\n return candidates\n\n depth -= 1\n\n augmented_lines_for_keyword_rules = []\n for key, value in AbstractScanner.structure_processing(struct_provider.struct):\n # a keyword rule may be applicable for `key` (str only) and `value` (str, bytes)\n keyword_match = bool(isinstance(key, str) and self.scanner.keywords_required_substrings_check(key.lower()))\n\n if isinstance(value, (dict, list, tuple)) and value:\n # recursive scan for not empty structured `value`\n val_struct_provider = StructContentProvider(struct=value,\n file_path=struct_provider.file_path,\n file_type=struct_provider.file_type,\n info=f\"{struct_provider.info}|STRUCT:{key}\")\n new_candidates = self.structure_scan(val_struct_provider, depth, recursive_limit_size)\n candidates.extend(new_candidates)\n elif isinstance(value, bytes):\n # recursive data scan\n if MIN_DATA_LEN <= len(value):\n bytes_struct_provider = DataContentProvider(data=value,\n file_path=struct_provider.file_path,\n file_type=struct_provider.file_type,\n info=f\"{struct_provider.info}|BYTES:{key}\")\n new_limit = recursive_limit_size - len(value)\n new_candidates = self.recursive_scan(bytes_struct_provider, depth, new_limit)\n candidates.extend(new_candidates)\n if keyword_match and MIN_VALUE_LENGTH <= len(value):\n augmented_lines_for_keyword_rules.append(f\"{key} = {repr(value)}\")\n elif isinstance(value, str):\n # recursive text scan with transformation into bytes\n stripped_value = value.strip()\n if MIN_DATA_LEN <= len(stripped_value):\n # recursive scan only for data which may be decoded at least\n with contextlib.suppress(UnicodeError):\n data = stripped_value.encode(encoding=DEFAULT_ENCODING, errors='strict')\n str_struct_provider = DataContentProvider(data=data,\n file_path=struct_provider.file_path,\n file_type=struct_provider.file_type,\n info=f\"{struct_provider.info}|STRING:{key}\")\n new_limit = recursive_limit_size - len(str_struct_provider.data)\n new_candidates = self.recursive_scan(str_struct_provider, depth, new_limit)\n candidates.extend(new_candidates)\n if keyword_match and MIN_VALUE_LENGTH <= len(stripped_value):\n augmented_lines_for_keyword_rules.append(f\"{key} = {repr(stripped_value)}\")\n elif not value or isinstance(value, (int, float, datetime.date, datetime.datetime)):\n # skip useless types\n pass\n else:\n logger.warning(\"Not supported type:%s value(%s)\", str(type(value)), str(value))\n\n if augmented_lines_for_keyword_rules:\n str_provider = StringContentProvider(augmented_lines_for_keyword_rules,\n file_path=struct_provider.file_path,\n file_type=struct_provider.file_type,\n info=f\"{struct_provider.info}|KEYWORD\")\n new_candidates = self.scanner.scan(str_provider)\n augment_candidates(candidates, new_candidates)\n\n return candidates\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def deep_scan_with_fallback(self, data_provider: DataContentProvider, depth: int,\n recursive_limit_size: int) -> List[Candidate]:\n \"\"\"Scans with deep scanners and fallback scanners if possible\n\n Args:\n data_provider: DataContentProvider with raw data\n depth: maximal level of recursion\n recursive_limit_size: maximal bytes of opened files to prevent recursive zip-bomb attack\n\n Returns: list with candidates\n\n \"\"\"\n candidates: List[Candidate] = []\n deep_scanners, fallback_scanners = self.get_deep_scanners(data_provider.data, data_provider.descriptor, depth)\n fallback = True\n for scan_class in deep_scanners:\n new_candidates = scan_class.data_scan(self, data_provider, depth, recursive_limit_size)\n if new_candidates is None:\n # scanner did not recognise the content type\n continue\n augment_candidates(candidates, new_candidates)\n # this scan is successful, so fallback is not necessary\n fallback = False\n if fallback:\n for scan_class in fallback_scanners:\n fallback_candidates = scan_class.data_scan(self, data_provider, depth, recursive_limit_size)\n if fallback_candidates is None:\n continue\n augment_candidates(candidates, fallback_candidates)\n # use only first successful fallback scanner\n break\n return candidates\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def scan(self,\n content_provider: ContentProvider,\n depth: int,\n recursive_limit_size: Optional[int] = None) -> List[Candidate]:\n \"\"\"Initial scan method to launch recursive scan. Skips ByteScanner to prevent extra scan\n\n Args:\n content_provider: ContentProvider that might contain raw data\n depth: maximal level of recursion\n recursive_limit_size: maximal bytes of opened files to prevent recursive zip-bomb attack\n \"\"\"\n recursive_limit_size = recursive_limit_size if isinstance(recursive_limit_size,\n int) else RECURSIVE_SCAN_LIMITATION\n candidates: List[Candidate] = []\n data: Optional[bytes] = None\n if isinstance(content_provider, (TextContentProvider, ByteContentProvider)):\n # Feature to scan files which might be containers\n data = content_provider.data\n info = f\"FILE:{content_provider.file_path}\"\n elif isinstance(content_provider, DiffContentProvider) and content_provider.diff:\n candidates = self.scanner.scan(content_provider)\n # Feature to scan binary diffs\n diff = content_provider.diff[0].get(\"line\")\n # the check for legal fix mypy issue\n if isinstance(diff, bytes):\n data = diff\n info = f\"DIFF:{content_provider.file_path}\"\n else:\n logger.warning(\"Content provider %s does not support deep scan\", type(content_provider))\n info = \"NA\"\n\n if data:\n data_provider = DataContentProvider(data=data,\n file_path=content_provider.file_path,\n file_type=content_provider.file_type,\n info=content_provider.info or info)\n new_candidates = self.deep_scan_with_fallback(data_provider, depth, recursive_limit_size - len(data))\n augment_candidates(candidates, new_candidates)\n return candidates\n" }, { "path": "credsweeper/deep_scanner/byte_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass ByteScanner(AbstractScanner, ABC):\n \"\"\"Implements plain data scanning\"\"\"\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to represent data as plain text with splitting by lines and scan as text lines\"\"\"\n byte_content_provider = ByteContentProvider(content=data_provider.data,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|RAW\")\n return self.scanner.scan(byte_content_provider)\n" }, { "path": "credsweeper/deep_scanner/bzip2_scanner.py", "content": "import bz2\nimport logging\nfrom abc import ABC\nfrom pathlib import Path\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass Bzip2Scanner(AbstractScanner, ABC):\n \"\"\"Implements bzip2 scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/Bzip2\"\"\"\n if data.startswith(b\"\\x42\\x5A\\x68\") and 10 <= len(data) \\\n and 0x31 <= data[3] <= 0x39 \\\n and 4 == data.find(b\"\\x31\\x41\\x59\\x26\\x53\\x59\", 4, 10):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data from bzip2 archive and launches data_scan\"\"\"\n try:\n file_path = Path(data_provider.file_path)\n new_path = file_path.as_posix()\n if \".bz2\" == file_path.suffix:\n new_path = new_path[:-4]\n bzip2_content_provider = DataContentProvider(data=bz2.decompress(data_provider.data),\n file_path=new_path,\n file_type=Util.get_extension(new_path),\n info=f\"{data_provider.info}|BZIP2:{file_path}\")\n new_limit = recursive_limit_size - len(bzip2_content_provider.data)\n bzip2_candidates = self.recursive_scan(bzip2_content_provider, depth, new_limit)\n return bzip2_candidates\n except Exception as bzip2_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, bzip2_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/crx_scanner.py", "content": "import logging\nimport struct\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass CrxScanner(AbstractScanner, ABC):\n \"\"\"Implements CRX files scanning with cut-off prefix\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Returns True if prefix match\"\"\"\n if data.startswith((b\"Cr24\\x02\\x00\\x00\\x00\", b\"Cr24\\x03\\x00\\x00\\x00\")) and 32 < len(data):\n return True\n return False\n\n @staticmethod\n def zip_extract(data: bytes) -> bytes:\n \"\"\"Extracts zip payload after signature block\"\"\"\n pubkey_length = struct.unpack(\" Optional[List[Candidate]]:\n \"\"\"Tries cut-off header and use ZIP payload\"\"\"\n try:\n zip_data = CrxScanner.zip_extract(data_provider.data)\n zip_content_provider = DataContentProvider(data=zip_data,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|CRX\")\n new_limit = recursive_limit_size - len(zip_data)\n crx_candidates = self.recursive_scan(zip_content_provider, depth, new_limit)\n return crx_candidates\n except Exception as exc:\n logger.warning(exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/csv_scanner.py", "content": "import csv\nimport io\nimport logging\nimport re\nfrom abc import ABC\nfrom typing import List, Optional, Dict, Any\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass CsvScanner(AbstractScanner, ABC):\n \"\"\"Implements CSV scanning\"\"\"\n\n sniffer = csv.Sniffer()\n # do not use space as separator to avoid hallucinations\n DELIMITERS = \",;\\t|\\x1F\"\n\n CSV_PATTERN = re.compile(b\"[^\\r\\n]{1,8000}[,;\\t|\\x1F][^\\r\\n]{1,8000}\")\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Check if data MAY be in CSV format\"\"\"\n end_pos = data.find(b'\\n', 0, MAX_LINE_LENGTH)\n if 0 > end_pos:\n # classic Mac OS format\n end_pos = data.find(b'\\r', 0, MAX_LINE_LENGTH)\n if 0 <= end_pos:\n if CsvScanner.CSV_PATTERN.match(data, pos=0, endpos=end_pos):\n return True\n return False\n\n @classmethod\n def get_structure(cls, text: str) -> List[Dict[str, Any]]:\n \"\"\"Reads a text as CSV standard with guessed dialect\"\"\"\n # windows style \\r\\n\n first_line_end = text.find('\\r', 0, MAX_LINE_LENGTH)\n line_terminator = \"\\r\\n\"\n if 0 > first_line_end:\n # unix style \\n\n first_line_end = text.find('\\n', 0, MAX_LINE_LENGTH)\n line_terminator = \"\\n\"\n if 0 > first_line_end:\n raise ValueError(f\"No suitable line end found in {MAX_LINE_LENGTH} symbols\")\n\n first_line = text[:first_line_end]\n dialect = cls.sniffer.sniff(first_line, delimiters=cls.DELIMITERS)\n rows = []\n reader = csv.DictReader(io.StringIO(text),\n delimiter=dialect.delimiter,\n lineterminator=line_terminator,\n strict=True)\n # check the constant columns number for all rows\n fields_number = sum(1 for x in reader.fieldnames if x is not None)\n for row in reader:\n if not isinstance(row, dict):\n raise ValueError(f\"ERROR: wrong row '{row}'\")\n if len(row) != fields_number or any(x is None for x in row.values()):\n # None means no separator used\n raise ValueError(f\"Different columns number in row '{row}' - mismatch {fields_number}\")\n rows.append(row)\n return rows\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan each row as structure with column name in key\"\"\"\n try:\n if rows := self.get_structure(data_provider.text):\n struct_content_provider = StructContentProvider(struct=rows,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|CSV\")\n new_limit = recursive_limit_size - sum(len(x) for x in rows)\n struct_candidates = self.structure_scan(struct_content_provider, depth, new_limit)\n return struct_candidates\n except Exception as csv_exc:\n logger.debug(\"%s:%s\", data_provider.file_path, csv_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/deb_scanner.py", "content": "import logging\nimport struct\nfrom abc import ABC\nfrom typing import List, Optional, Generator, Tuple\n\nfrom credsweeper.common.constants import MIN_DATA_LEN, UTF_8\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass DebScanner(AbstractScanner, ABC):\n \"\"\"Implements deb (ar) scanning\"\"\"\n\n __header_size = 60\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/Deb_(file_format)\"\"\"\n if data.startswith(b\"!\\n\"):\n return True\n return False\n\n @staticmethod\n def walk_deb(data: bytes) -> Generator[Tuple[int, str, bytes], None, None]:\n \"\"\"Processes sequence of DEB archive and yields offset, name and data\"\"\"\n offset = 8 # b\"!\\n\"\n data_limit = len(data) - DebScanner.__header_size\n while offset <= data_limit:\n _data = data[offset:offset + DebScanner.__header_size]\n offset += DebScanner.__header_size\n # basic header structure\n _name, _, _size, __ = struct.unpack('16s32s10s2s', _data)\n file_size = int(_size)\n if MIN_DATA_LEN < file_size <= len(data) - offset:\n _data = data[offset:offset + file_size]\n yield offset, _name.decode(encoding=UTF_8).strip().rstrip('/'), _data\n offset += file_size if 0 == 1 & file_size else file_size + 1\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data file from .ar (debian) archive and launches data_scan\"\"\"\n try:\n candidates: List[Candidate] = []\n for offset, name, data in DebScanner.walk_deb(data_provider.data):\n deb_content_provider = DataContentProvider(data=data,\n file_path=f\"{data_provider.file_path}\",\n file_type=Util.get_extension(name),\n info=f\"{data_provider.info}|DEB:0x{offset:x}:{name}\")\n new_limit = recursive_limit_size - len(data)\n deb_candidates = self.recursive_scan(deb_content_provider, depth, new_limit)\n candidates.extend(deb_candidates)\n return candidates\n except Exception as exc:\n logger.warning(exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/deep_scanner.py", "content": "import logging\nimport re\nfrom typing import List, Any, Tuple, Union, Dict\n\nfrom credsweeper.common.constants import MIN_DATA_LEN\nfrom credsweeper.config.config import Config\nfrom credsweeper.deep_scanner.byte_scanner import ByteScanner\nfrom credsweeper.deep_scanner.bzip2_scanner import Bzip2Scanner\nfrom credsweeper.deep_scanner.crx_scanner import CrxScanner\nfrom credsweeper.deep_scanner.csv_scanner import CsvScanner\nfrom credsweeper.deep_scanner.deb_scanner import DebScanner\nfrom credsweeper.deep_scanner.docx_scanner import DocxScanner\nfrom credsweeper.deep_scanner.eml_scanner import EmlScanner\nfrom credsweeper.deep_scanner.encoder_scanner import EncoderScanner\nfrom credsweeper.deep_scanner.gzip_scanner import GzipScanner\nfrom credsweeper.deep_scanner.html_scanner import HtmlScanner\nfrom credsweeper.deep_scanner.jclass_scanner import JclassScanner\nfrom credsweeper.deep_scanner.jks_scanner import JksScanner\nfrom credsweeper.deep_scanner.lang_scanner import LangScanner\nfrom credsweeper.deep_scanner.lzma_scanner import LzmaScanner\nfrom credsweeper.deep_scanner.mxfile_scanner import MxfileScanner\nfrom credsweeper.deep_scanner.patch_scanner import PatchScanner\nfrom credsweeper.deep_scanner.pdf_scanner import PdfScanner\nfrom credsweeper.deep_scanner.pkcs_scanner import PkcsScanner\nfrom credsweeper.deep_scanner.png_scanner import PngScanner\nfrom credsweeper.deep_scanner.pptx_scanner import PptxScanner\nfrom credsweeper.deep_scanner.rpm_scanner import RpmScanner\nfrom credsweeper.deep_scanner.rtf_scanner import RtfScanner\nfrom credsweeper.deep_scanner.sqlite3_scanner import Sqlite3Scanner\nfrom credsweeper.deep_scanner.strings_scanner import StringsScanner\nfrom credsweeper.deep_scanner.tar_scanner import TarScanner\nfrom credsweeper.deep_scanner.tmx_scanner import TmxScanner\nfrom credsweeper.deep_scanner.xlsx_scanner import XlsxScanner\nfrom credsweeper.deep_scanner.xml_scanner import XmlScanner\nfrom credsweeper.deep_scanner.zip_scanner import ZipScanner\nfrom credsweeper.deep_scanner.zlib_scanner import ZlibScanner\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom credsweeper.scanner.scanner import Scanner\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass DeepScanner(\n ByteScanner, #\n Bzip2Scanner, #\n CrxScanner, #\n CsvScanner, #\n DocxScanner, #\n EncoderScanner, #\n GzipScanner, #\n HtmlScanner, #\n JclassScanner, #\n JksScanner, #\n LangScanner, #\n LzmaScanner, #\n MxfileScanner, #\n EmlScanner, #\n PatchScanner, #\n PdfScanner, #\n PkcsScanner, #\n PngScanner, #\n PptxScanner, #\n RtfScanner, #\n RpmScanner, #\n Sqlite3Scanner, #\n StringsScanner, #\n TarScanner, #\n DebScanner, #\n XmlScanner, #\n XlsxScanner, #\n ZipScanner, #\n ZlibScanner, #\n): # yapf: disable\n \"\"\"Advanced scanner with recursive exploring of data\"\"\"\n\n def __init__(self, config: Config, scanner: Scanner) -> None:\n \"\"\"Initialize Advanced credential scanner.\n\n Args:\n scanner: CredSweeper scanner object\n config: dictionary variable, stores analyzer features\n \"\"\"\n self.__config = config\n self.__scanner = scanner\n\n @property\n def config(self) -> Config:\n return self.__config\n\n @property\n def scanner(self) -> Scanner:\n return self.__scanner\n\n # manually crafted dict to detect a media format with first byte, prefix and optionally pattern\n MEDIA_PATTERNS: Dict[int, List[Tuple[bytes, re.Pattern]]] = {\n 0x00: [\n # JPEG2000\n (b\"\\x00\\x00\\x00\\x0C\\x6A\\x50\\x20\\x20\\x0D\\x0A\\x87\\x0A\", None),\n # ICO\n (b\"\\x00\\x00\\x01\\x00\", None),\n # TTF\n (b\"\\x00\\x01\\x00\\x00\\x00\", None),\n # 3gp\n (b\"\\x00\\x00\\x00\", re.compile(b\"\\x00\\x00\\x00.ftyp3g\")),\n # GITCRYPT is not a media but added to use pedantic scan for strings and reduce extra warnings\n (b\"\\x00GITCRYPT\\x00\", None),\n ],\n 0x1A: [\n # Matroska\n (b\"\\x1A\\x45\\xDF\\xA3\", None),\n ],\n 0x7F: [\n # ELF signature - to quick pass for strings scanner\n (b\"\\x7FELF\", re.compile(b\"\\x7FELF[\\x01\\x02][\\x01\\x02]\\x01[\\x00-\\x12]\"))\n ],\n 0x89: [\n # PNG - can store text chunks inside\n (b\"\\x89PNG\\x0D\\x0A\\x1A\\x0A\", None),\n ],\n 0xFF: [\n # JPEG or MPEG-1 Layer 3\n (b\"\\xFF\", re.compile(b\"\\xFF(\\xD8\\xFF[\\xDB\\xEE\\xE1\\xE0\\x51]|[\\xFB\\xF3\\xF2])\")),\n ],\n ord('8'): [\n # PSD\n (b\"8BPS\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\", None),\n # PSB\n (b\"8BPS\\x00\\x02\\x00\\x00\\x00\\x00\\x00\\x00\", None),\n ],\n ord('B'): [\n # BMP\n (b\"BM\", re.compile(b\"BM.{2}\\x00{4}\")),\n ],\n ord('G'): [\n # GIF\n (b\"GIF8\", re.compile(b\"GIF8[79]a[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")\n ),\n ],\n ord('I'): [\n # TIFF little endian\n (b\"II\", re.compile(b\"II[+*]\\x00[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n # ID2v3 for various media (e.g. MP3)\n (b\"ID3\\x03\\x00\\x00\\x00\", None),\n ],\n ord('M'): [\n # TIFF big endian\n (b\"MM\", re.compile(b\"MM\\x00[+*][^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('O'): [\n # OGG\n (b\"OggS\", re.compile(b\"OggS[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n # OpenType font file\n (b\"OTTO\\x00\",\n re.compile(b\"OTTO\\x00[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('R'): [\n # RIFF va\n (b\"RIF\",\n re.compile(b\"RIF[FX].{4}[ 0-9A-Za-z]{4}\"\n b\"[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('X'): [\n # Macromedia\n (b\"XFIR\",\n re.compile(b\"XFIR.{4}[ 0-9A-Za-z]{4}\"\n b\"[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('f'): [\n # mp4\n (b\"ftyp\",\n re.compile(b\"ftyp(isom|MSNV)[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('g'): [\n # gimp\n (b\"gimp xcf\",\n re.compile(b\"gimp xcf (file|v001|v002)\\x00\"\n b\"[^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n ord('w'): [\n # WOFF 1.0, 2.0\n (b\"wOF\", re.compile(b\"wOF[2F][^\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]{0,4096}[\\x00-\\x08\\x0C\\x0E\\x1F\\x80-\\xFF]\")),\n ],\n }\n\n @staticmethod\n def is_media(data: Union[bytes, bytearray]) -> bool:\n \"\"\"Returns True if well-known media format found\"\"\"\n if patterns := DeepScanner.MEDIA_PATTERNS.get(data[0]):\n for prefix, pattern in patterns:\n # use prefix for speed-up total search\n if prefix and data.startswith(prefix) and (pattern is None or pattern.match(data)):\n return True\n return False\n\n @staticmethod\n def get_deep_scanners(data: bytes, descriptor: Descriptor, depth: int) -> Tuple[List[Any], List[Any]]:\n \"\"\"Returns possibly scan methods for the data depends on content and fallback scanners\"\"\"\n deep_scanners: List[Any] = []\n fallback_scanners: List[Any] = []\n if not data or not isinstance(data, (bytes, bytearray)) or len(data) < MIN_DATA_LEN:\n # Guard clause: reject empty or invalid input data early\n pass\n elif ZipScanner.match(data):\n if 0 < depth:\n deep_scanners.append(ZipScanner)\n # probably, there might be a docx, xlsx and so on.\n # It might be scanned with text representation in third-party libraries.\n if descriptor.extension in (\".xlsx\", \".ods\"):\n deep_scanners.append(XlsxScanner)\n else:\n fallback_scanners.append(XlsxScanner)\n if \".docx\" == descriptor.extension:\n deep_scanners.append(DocxScanner)\n else:\n fallback_scanners.append(DocxScanner)\n if \".pptx\" == descriptor.extension:\n deep_scanners.append(PptxScanner)\n else:\n fallback_scanners.append(PptxScanner)\n elif XlsxScanner.match(data):\n if \".xls\" == descriptor.extension:\n deep_scanners.append(XlsxScanner)\n else:\n fallback_scanners.append(XlsxScanner)\n elif Bzip2Scanner.match(data):\n if 0 < depth:\n deep_scanners.append(Bzip2Scanner)\n elif LzmaScanner.match(data):\n if 0 < depth:\n deep_scanners.append(LzmaScanner)\n elif TarScanner.match(data):\n if 0 < depth:\n deep_scanners.append(TarScanner)\n elif DebScanner.match(data):\n if 0 < depth:\n deep_scanners.append(DebScanner)\n elif GzipScanner.match(data):\n if 0 < depth:\n deep_scanners.append(GzipScanner)\n elif PdfScanner.match(data):\n deep_scanners.append(PdfScanner)\n elif PngScanner.match(data):\n deep_scanners.append(PngScanner)\n elif RpmScanner.match(data):\n if 0 < depth:\n deep_scanners.append(RpmScanner)\n elif JclassScanner.match(data):\n deep_scanners.append(JclassScanner)\n elif JksScanner.match(data):\n deep_scanners.append(JksScanner)\n elif Sqlite3Scanner.match(data):\n if 0 < depth:\n deep_scanners.append(Sqlite3Scanner)\n elif PkcsScanner.match(data):\n deep_scanners.append(PkcsScanner)\n elif CrxScanner.match(data):\n if 0 < depth:\n deep_scanners.append(CrxScanner)\n elif RtfScanner.match(data):\n deep_scanners.append(RtfScanner)\n fallback_scanners.append(ByteScanner)\n elif XmlScanner.match(data):\n if HtmlScanner.match(data):\n deep_scanners.append(HtmlScanner)\n deep_scanners.append(XmlScanner)\n fallback_scanners.append(ByteScanner)\n elif MxfileScanner.match(data):\n deep_scanners.append(MxfileScanner)\n deep_scanners.append(XmlScanner)\n fallback_scanners.append(ByteScanner)\n elif TmxScanner.match(data):\n deep_scanners.append(TmxScanner)\n fallback_scanners.append(XmlScanner)\n fallback_scanners.append(ByteScanner)\n else:\n deep_scanners.append(XmlScanner)\n fallback_scanners.append(ByteScanner)\n elif EmlScanner.match(data):\n if descriptor.extension in (\".eml\", \".mht\"):\n deep_scanners.append(EmlScanner)\n else:\n if 0 < depth:\n # a formal patch looks like an eml\n deep_scanners.append(PatchScanner)\n fallback_scanners.append(EmlScanner)\n fallback_scanners.append(ByteScanner)\n elif DeepScanner.is_media(data):\n # only StringsScanner may be applied for the formats effective\n if 0 < depth:\n fallback_scanners.append(StringsScanner)\n elif not Util.is_binary(data):\n # keep ByteScanner first to apply real value position if possible\n deep_scanners.append(ByteScanner)\n if 0 < depth:\n deep_scanners.append(PatchScanner)\n deep_scanners.append(LangScanner)\n if CsvScanner.match(data):\n deep_scanners.append(CsvScanner)\n if EncoderScanner.match(data):\n deep_scanners.append(EncoderScanner)\n if ZlibScanner.match(data):\n deep_scanners.append(ZlibScanner)\n else:\n if 0 < depth:\n if ZlibScanner.match(data):\n deep_scanners.append(ZlibScanner)\n fallback_scanners.append(StringsScanner)\n else:\n deep_scanners.append(StringsScanner)\n if not descriptor.info.endswith(\"|BASE64\"):\n logger.warning(\"Cannot apply a deep scanner for type %s prefix %s %d\", descriptor, repr(data[:32]),\n len(data))\n return deep_scanners, fallback_scanners\n" }, { "path": "credsweeper/deep_scanner/docx_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nimport docx\nfrom docx.document import Document\nfrom docx.oxml import CT_P, CT_Tbl, CT_SectPr, CT_TcPr\nfrom docx.section import Section, _Header, _Footer\nfrom docx.table import _Cell, Table\nfrom docx.text.paragraph import Paragraph\nfrom lxml.etree import _Element\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass DocxScanner(AbstractScanner, ABC):\n \"\"\"Implements docx scanning\"\"\"\n\n @staticmethod\n def _iter_block_items(block):\n if isinstance(block, Paragraph):\n yield block\n return\n if isinstance(block, (_Header, _Footer)):\n for table in block.tables:\n for row in table.rows:\n for cell in row.cells:\n yield from DocxScanner._iter_block_items(cell)\n yield from block.paragraphs\n return\n if isinstance(block, Section):\n yield from DocxScanner._iter_block_items(block.header)\n yield from DocxScanner._iter_block_items(block.footer)\n return\n\n if isinstance(block, Document):\n parent_elm = block.element.body\n elif isinstance(block, _Cell):\n parent_elm = block._tc # pylint: disable=W0212\n else:\n raise ValueError(f\"unrecognised:{type(block)}\")\n\n for child in parent_elm.iterchildren():\n if isinstance(child, CT_P):\n yield Paragraph(child, block)\n elif isinstance(child, CT_Tbl):\n table = Table(child, block)\n for row in table.rows:\n for cell in row.cells:\n yield from DocxScanner._iter_block_items(cell)\n elif isinstance(child, (CT_TcPr, CT_SectPr)):\n # config\n pass\n elif isinstance(child, _Element):\n yield child\n else:\n logger.warning(\"Unknown:%s\", type(child))\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan DOCX text with splitting by lines\"\"\"\n try:\n docx_lines: List[str] = []\n\n doc = docx.Document(io.BytesIO(data_provider.data))\n for block in self._iter_block_items(doc):\n if block.text:\n docx_lines.append(block.text)\n\n header_lines_set = set()\n footer_lines_set = set()\n for section in doc.sections:\n for header in [section.first_page_header, section.even_page_header, section.header]:\n for block in self._iter_block_items(header):\n if block.text:\n header_lines_set.add(block.text)\n for footer in [section.first_page_footer, section.even_page_footer, section.footer]:\n for block in self._iter_block_items(footer):\n if block.text:\n footer_lines_set.add(block.text)\n docx_lines.extend(sorted(list(header_lines_set)))\n docx_lines.extend(sorted(list(footer_lines_set)))\n\n string_data_provider = StringContentProvider(lines=docx_lines,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|DOCX\")\n docx_candidates = self.scanner.scan(string_data_provider)\n return docx_candidates\n\n except Exception as docx_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, docx_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/eml_scanner.py", "content": "import email\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass EmlScanner(AbstractScanner, ABC):\n \"\"\"Implements eml scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According to https://datatracker.ietf.org/doc/html/rfc822 lookup the fields: Date, From, To or Subject\"\"\"\n if (b\"\\nDate:\" in data or data.startswith(b\"Date:\")) \\\n and (b\"\\nFrom:\" in data or data.startswith(b\"From:\")) \\\n and (b\"\\nTo:\" in data or data.startswith(b\"To:\")) \\\n and (b\"\\nSubject:\" in data or data.startswith(b\"Subject:\")):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan EML with text representation\"\"\"\n try:\n candidates: List[Candidate] = []\n msg = email.message_from_bytes(data_provider.data)\n for part in msg.walk():\n content_type = part.get_content_type()\n body = part.get_payload(decode=True)\n\n if not isinstance(body, (bytes, str)):\n continue\n if \"text/plain\" == content_type:\n eml_text_data_provider = ByteContentProvider(\n content=(body if isinstance(body, bytes) else body.encode()),\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|EML-TEXT\")\n eml_candidates = self.scanner.scan(eml_text_data_provider)\n candidates.extend(eml_candidates)\n else:\n x_data_provider = DataContentProvider(data=(body if isinstance(body, bytes) else body.encode()),\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|EML-DATA\")\n new_limit = recursive_limit_size - len(body)\n if \"text/html\" == content_type and x_data_provider.represent_as_html(\n depth, new_limit, self.scanner.keywords_required_substrings_check):\n string_data_provider = StringContentProvider(lines=x_data_provider.lines,\n line_numbers=x_data_provider.line_numbers,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|EML-HTML\")\n html_candidates = self.scanner.scan(string_data_provider)\n candidates.extend(html_candidates)\n elif content_type.startswith(\"application\"):\n x_candidates = self.recursive_scan(x_data_provider, depth, new_limit)\n candidates.extend(x_candidates)\n else:\n logger.warning(\"%s:%s:%s cannot be supported\", data_provider.file_path, content_type,\n type(body))\n return candidates\n except Exception as eml_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, eml_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/encoder_scanner.py", "content": "import contextlib\nimport logging\nimport re\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n# 8 bytes are encoded to 12 symbols 12345678 -> MTIzNDU2Nzg=\nMIN_ENCODED_DATA_LEN = 12\n\n\nclass EncoderScanner(AbstractScanner, ABC):\n \"\"\"Implements recursive iteration when data might be encoded from base64\"\"\"\n\n BASE64_PATTERN = re.compile(\n rb\"(\\xFF\\xFE|\\xFE\\xFF)?(\"\n rb\"(?:(?P[A-Z])|(?P[a-z])|(?P[0-9/+])|[\\s\\x00\\\\])+(?(a)(?(b)(?(c)(=+|$)|(?!x)x)|(?!x)x)|(?!x)x)|\"\n rb\"(?:(?P[A-Z])|(?P[a-z])|(?P[0-9_-])|[\\s\\x00\\\\])+(?(e)(?(f)(?(g)(=+|$)|(?!x)x)|(?!x)x)|(?!x)x))\")\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Check if data MAY be base64 encoded with whitespaces (escaping too)\"\"\"\n if len(data) >= MIN_ENCODED_DATA_LEN \\\n and EncoderScanner.BASE64_PATTERN.match(data, pos=0, endpos=MAX_LINE_LENGTH):\n return True\n return False\n\n @staticmethod\n def decode(text: str) -> Optional[bytes]:\n \"\"\"Decodes base64 text with cleaning whitespaces. Returns None when the decoding fails\"\"\"\n with contextlib.suppress(Exception):\n return Util.decode_base64(text=Util.PEM_CLEANING_PATTERN.sub(r'', text).replace('\\\\', ''),\n padding_safe=True,\n urlsafe_detect=True)\n return None\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to decode data from base64 encode to bytes and scan as bytes again\"\"\"\n if decoded := EncoderScanner.decode(data_provider.text):\n decoded_data_provider = DataContentProvider(data=decoded,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|BASE64\")\n new_limit = recursive_limit_size - len(decoded_data_provider.data)\n return self.recursive_scan(decoded_data_provider, depth, new_limit)\n return None\n" }, { "path": "credsweeper/deep_scanner/gzip_scanner.py", "content": "import gzip\nimport io\nimport logging\nfrom abc import ABC\nfrom pathlib import Path\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass GzipScanner(AbstractScanner, ABC):\n \"\"\"Realises gzip scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://www.rfc-editor.org/rfc/rfc1952\"\"\"\n if data.startswith(b\"\\x1F\\x8B\\x08\"):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data from gzip archive and launches data_scan\"\"\"\n try:\n with gzip.open(io.BytesIO(data_provider.data)) as f:\n file_path = Path(data_provider.file_path)\n new_path = file_path.as_posix()\n if \".gz\" == file_path.suffix:\n new_path = new_path[:-3]\n gzip_content_provider = DataContentProvider(data=f.read(),\n file_path=new_path,\n file_type=Util.get_extension(new_path),\n info=f\"{data_provider.info}|GZIP:{new_path}\")\n new_limit = recursive_limit_size - len(gzip_content_provider.data)\n gzip_candidates = self.recursive_scan(gzip_content_provider, depth, new_limit)\n return gzip_candidates\n except Exception as gzip_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, gzip_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/html_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass HtmlScanner(AbstractScanner, ABC):\n \"\"\"Implements html scanning if possible\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Used to detect html format. Suppose, invocation of is_xml() was True before.\"\"\"\n for opening_tag, closing_tag in [(b\"\"), (b\"\"), (b\"\"),\n (b\"

\", b\"

\"), (b\"\", b\"\"), (b\"
\", b\"
\"),\n (b\"
  • \", b\"
    • \"), (b\"
      \", b\"
    \"), (b\"
      \", b\"
    \"),\n (b\"\", b\"\"), (b\"\", b\"\"), (b\"\", b\"\")]:\n opening_pos = data.find(opening_tag, 0, MAX_LINE_LENGTH)\n if 0 <= opening_pos < data.find(closing_tag, opening_pos):\n # opening and closing tags were found - suppose it is an HTML\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to represent data as html text and scan as text lines\"\"\"\n if result := data_provider.represent_as_html(depth, recursive_limit_size,\n self.scanner.keywords_required_substrings_check):\n string_data_provider = StringContentProvider(lines=data_provider.lines,\n line_numbers=data_provider.line_numbers,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|HTML\")\n return self.scanner.scan(string_data_provider)\n return None if result is None else []\n" }, { "path": "credsweeper/deep_scanner/jclass_scanner.py", "content": "import io\nimport logging\nimport struct\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.common.constants import UTF_8\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass JclassScanner(AbstractScanner, ABC):\n \"\"\"Implements java .class scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - java class\"\"\"\n if data.startswith(b\"\\xCA\\xFE\\xBA\\xBE\"):\n return True\n return False\n\n @staticmethod\n def u2(stream: io.BytesIO) -> int:\n \"\"\"Extracts unsigned 16 bit big-endian\"\"\"\n return int(struct.unpack(\">H\", stream.read(2))[0])\n\n @staticmethod\n def get_utf8_constants(stream: io.BytesIO) -> List[str]:\n \"\"\"Extracts only Utf8 constants from java ClassFile\"\"\"\n result = []\n # actual number of items is one less!\n items_counter = JclassScanner.u2(stream) - 1\n while 0 < items_counter:\n items_counter -= 1\n # uint8\n tag = int(stream.read(1)[0])\n if 1 == tag:\n # UTF-8 string in bytes may be bigger than in characters\n length = JclassScanner.u2(stream)\n data = stream.read(int(length))\n value = data.decode(encoding=UTF_8, errors=\"replace\")\n result.append(value)\n elif tag in (3, 4, 9, 10, 11, 12, 18):\n _ = stream.read(4)\n elif tag in (7, 8, 16):\n _ = stream.read(2)\n elif tag in (5, 6):\n _ = stream.read(8)\n # long and double types use two indexes\n items_counter -= 1\n elif 15 == tag:\n _ = stream.read(3)\n else:\n logger.warning(\"Unknown tag %s\", tag)\n break\n return result\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data from binary\"\"\"\n try:\n stream = io.BytesIO(data_provider.data)\n stream.read(4) # magic\n minor = JclassScanner.u2(stream)\n major = JclassScanner.u2(stream)\n constants = JclassScanner.get_utf8_constants(stream)\n struct_content_provider = StructContentProvider(struct=constants,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|Java.{major}.{minor}\")\n new_limit = recursive_limit_size - sum(len(x) for x in constants)\n candidates = self.structure_scan(struct_content_provider, depth, new_limit)\n return candidates\n except Exception as jclass_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, jclass_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/jks_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nimport jks\n\nfrom credsweeper.common.constants import Severity, Confidence\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass JksScanner(AbstractScanner, ABC):\n \"\"\"Implements jks scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - jks\"\"\"\n if data.startswith(b\"\\xFE\\xED\\xFE\\xED\"):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan JKS to open with standard password\"\"\"\n for pw_probe in self.config.bruteforce_list:\n value = repr(pw_probe)\n try:\n keystore = jks.KeyStore.loads(data_provider.data, pw_probe, try_decrypt_keys=True)\n # the password probe has passed, it will be the value\n if keystore.private_keys or keystore.secret_keys:\n severity = Severity.HIGH\n confidence = Confidence.STRONG\n info = f\"{data_provider.info}|JKS:default password\"\n rule_name = f\"JKS private key with password {value}\"\n else:\n severity = Severity.LOW\n confidence = Confidence.WEAK\n info = f\"{data_provider.info}|JKS:sensitive data\"\n rule_name = f\"JKS sensitive data with password {value}\"\n candidate = Candidate.get_dummy_candidate(\n self.config, #\n data_provider.file_path, #\n data_provider.file_type, #\n info, #\n rule_name)\n candidate.severity = severity\n candidate.confidence = confidence\n candidate.line_data_list[0].line = candidate.line_data_list[0].value = value\n candidate.line_data_list[0].value_start = 0\n candidate.line_data_list[0].value_end = len(value)\n return [candidate]\n except Exception as jks_exc:\n logger.debug(\"%s:%s:%s\", data_provider.file_path, pw_probe, jks_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/lang_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass LangScanner(AbstractScanner, ABC):\n \"\"\"Implements scanning of data if it is a script of some markup language\"\"\"\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to represent data as markup language and scan as structure\"\"\"\n if result := data_provider.represent_as_structure():\n struct_data_provider = StructContentProvider(struct=data_provider.structure,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|STRUCT\")\n return self.structure_scan(struct_data_provider, depth, recursive_limit_size)\n return None if result is None else []\n" }, { "path": "credsweeper/deep_scanner/lzma_scanner.py", "content": "import logging\nimport lzma\nfrom abc import ABC\nfrom pathlib import Path\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass LzmaScanner(AbstractScanner, ABC):\n \"\"\"Implements lzma scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - lzma also xz\"\"\"\n if data.startswith((b\"\\xFD7zXZ\\x00\", b\"\\x5D\\x00\\x00\")):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data from lzma archive and launches data_scan\"\"\"\n try:\n file_path = Path(data_provider.file_path)\n new_path = file_path.as_posix()\n if \".xz\" == file_path.suffix:\n new_path = new_path[:-3]\n elif \".lzma\" == file_path.suffix:\n new_path = new_path[:-5]\n lzma_content_provider = DataContentProvider(data=lzma.decompress(data_provider.data),\n file_path=new_path,\n file_type=Util.get_extension(new_path),\n info=f\"{data_provider.info}|LZMA:{file_path}\")\n new_limit = recursive_limit_size - len(lzma_content_provider.data)\n lzma_candidates = self.recursive_scan(lzma_content_provider, depth, new_limit)\n return lzma_candidates\n except Exception as lzma_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, lzma_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/mxfile_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom bs4 import BeautifulSoup\nfrom lxml import etree\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass MxfileScanner(AbstractScanner, ABC):\n \"\"\"Scanner for drawio diagram\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Used to detect mxfile (drawio) format. Suppose, invocation of is_xml() was True before.\"\"\"\n mxfile_tag_pos = data.find(b\"\", mxfile_tag_pos):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to get text data from the xml format\"\"\"\n try:\n lines = []\n line_numbers = []\n tree = etree.fromstring(data_provider.text)\n for element in tree.iter():\n if \"mxCell\" == getattr(element, \"tag\"):\n line_number = element.sourceline\n attr = getattr(element, \"attrib\")\n if attr is None or not (value := attr.get(\"value\")):\n continue\n if html := BeautifulSoup(value, features=\"html.parser\"):\n _, value_lines, __ = data_provider.simple_html_representation(html)\n for line in value_lines:\n lines.append(line)\n line_numbers.append(line_number)\n mxfile_data_provider = StringContentProvider(lines=lines,\n line_numbers=line_numbers,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|MXFILE\")\n return self.scanner.scan(mxfile_data_provider)\n except Exception as exc:\n logger.warning(exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/patch_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.common.constants import DiffRowType\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.patches_provider import PatchesProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass PatchScanner(AbstractScanner, ABC):\n \"\"\"Implements .patch scanning\"\"\"\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan EML with text representation\"\"\"\n try:\n candidates: List[Candidate] = []\n # common limitation\n new_limit_size = recursive_limit_size - len(data_provider.data)\n # ADDED\n path_added = [(data_provider.file_path, io.BytesIO(data_provider.data))]\n added_content_provider = PatchesProvider(path_added, change_type=DiffRowType.ADDED)\n for added_file in added_content_provider.get_scannable_files(self.config):\n added_candidates = self.scan(added_file, depth, new_limit_size)\n candidates.extend(added_candidates)\n # DELETED\n path_deleted = [(data_provider.file_path, io.BytesIO(data_provider.data))]\n deleted_content_provider = PatchesProvider(path_deleted, change_type=DiffRowType.DELETED)\n for deleted_file in deleted_content_provider.get_scannable_files(self.config):\n added_candidates = self.scan(deleted_file, depth, new_limit_size)\n candidates.extend(added_candidates)\n # update the line data for deep scan only\n for i in candidates:\n for line_data in i.line_data_list:\n line_data.path = data_provider.file_path\n line_data.info = f\"{data_provider.info}|PATCH:{line_data.info}\"\n return candidates\n except Exception as patch_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, patch_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/pdf_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom pdfminer.high_level import extract_pages\nfrom pdfminer.layout import LAParams, LTText, LTItem\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider, MIN_DATA_LEN\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass PdfScanner(AbstractScanner, ABC):\n \"\"\"Implements pdf scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - pdf\"\"\"\n if data.startswith(b\"%PDF-\"):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan PDF elements recursively and the whole text on page as strings\"\"\"\n # PyPDF2 - https://github.com/py-pdf/pypdf/issues/1328 text in table is merged without spaces\n # pdfminer.six - splits text in table to many lines. Allows to walk through elements\n try:\n candidates = []\n for page in extract_pages(io.BytesIO(data_provider.data), laparams=LAParams()):\n for element in page:\n if isinstance(element, LTText):\n element_text = element.get_text().strip()\n if 0 < depth and element_text:\n if MIN_DATA_LEN < len(element_text):\n pdf_content_provider = DataContentProvider(\n data=element_text.encode(),\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|PDF:{page.pageid}\")\n new_limit = recursive_limit_size - len(pdf_content_provider.data)\n element_candidates = self.recursive_scan(pdf_content_provider, depth, new_limit)\n candidates.extend(element_candidates)\n else:\n string_data_provider = StringContentProvider(lines=[element_text],\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|PDF:{page.pageid}\")\n pdf_candidates = self.scanner.scan(string_data_provider)\n candidates.extend(pdf_candidates)\n elif isinstance(element, LTItem):\n pass\n else:\n logger.warning(\"Unsupported %s\", element)\n return candidates\n except Exception as pdf_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, pdf_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/pkcs_scanner.py", "content": "import base64\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional, Union\n\nfrom credsweeper.common.constants import Severity, Confidence\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass PkcsScanner(AbstractScanner, ABC):\n \"\"\"Implements pkcs12 scanning\"\"\"\n\n @staticmethod\n def match(data: Union[bytes, bytearray]) -> int:\n \"\"\"Matched ASN1 structure\"\"\"\n return bool(Util.get_asn1_size(data))\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan PKCS12 to open with standard password\"\"\"\n for pw_probe in self.config.bruteforce_list:\n try:\n password = pw_probe.encode() if pw_probe else None\n if pkey := Util.load_pk(data_provider.data, password):\n if not Util.check_pk(pkey):\n logger.debug(\"False alarm %s\", data_provider.info)\n return []\n candidate = Candidate.get_dummy_candidate(\n self.config, #\n data_provider.file_path, #\n data_provider.file_type, #\n info=f\"{data_provider.info}|PKCS_PASSWORD:{repr(password)}\", #\n rule_name=f\"PKCS with password {repr(pw_probe)}\" if pw_probe else \"PKCS without password\")\n candidate.line_data_list[0].line = base64.b64encode(data_provider.data).decode()\n candidate.line_data_list[0].value = repr(password)\n # high severity is assigned to private key rules\n candidate.severity = Severity.HIGH\n candidate.confidence = Confidence.STRONG\n return [candidate]\n except Exception as pkcs_exc:\n logger.debug(\"%s:%s:%s\", data_provider.file_path, pw_probe, pkcs_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/png_scanner.py", "content": "import logging\nimport struct\nfrom abc import ABC\nfrom typing import List, Optional, Generator, Tuple\n\nfrom credsweeper.common.constants import LATIN_1, UTF_8\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass PngScanner(AbstractScanner, ABC):\n \"\"\"Implements PNG scanning for text chunks\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Returns True if prefix match\"\"\"\n if data.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\"):\n return True\n return False\n\n @staticmethod\n def yield_png_chunks(data: bytes) -> Generator[Tuple[int, str, bytes], None, None]:\n \"\"\"Processes PNG chunks and yields offset, type and data\"\"\"\n offset = 8 # b\"\\x89PNG\\r\\n\\x1a\\n\"\n data_limit = len(data) - 12\n while offset <= data_limit:\n chunk_size = struct.unpack(\">I\", data[offset:offset + 4])[0]\n chunk_type = data[offset + 4:offset + 8]\n offset += 8\n if len(data) < offset + chunk_size:\n raise ValueError(f\"PNG chunk size {chunk_size} exceeds data limit 0x{offset:x}\")\n match chunk_type:\n case b\"IEND\":\n # https://www.w3.org/TR/png/#11IEND\n break\n case b\"tEXt\":\n # https://www.w3.org/TR/png/#11tEXt\n keyword, text_data = data[offset:offset + chunk_size].split(b'\\0', 1)\n yield offset, f\"PNG_TEXT:{keyword.decode(encoding=LATIN_1, errors='strict')}\", text_data\n case b\"zTXt\":\n # https://www.w3.org/TR/png/#11zTXt\n keyword, ztxt_data = data[offset:offset + chunk_size].split(b'\\0', 1)\n if not ztxt_data.startswith(b'\\0'):\n raise ValueError(f\"Unsupported compression method {ztxt_data[0]}\")\n yield offset, f\"PNG_ZTXT:{keyword.decode(encoding=LATIN_1, errors='strict')}\", ztxt_data[1:]\n case b\"iTXt\":\n # https://www.w3.org/TR/png/#11iTXt\n keyword, itxt_data = data[offset:offset + chunk_size].split(b'\\0', 1)\n\n if itxt_data.startswith(b\"\\x00\\x00\"):\n compression = False\n elif itxt_data.startswith(b\"\\x01\\x00\"):\n compression = True\n else:\n raise ValueError(f\"Unsupported compression {repr(itxt_data[:2])}\")\n lang_tag, itxt_data = itxt_data[2:].split(b'\\0', 1)\n trans_key, itxt_data = itxt_data.split(b'\\0', 1)\n yield (offset, f\"PNG_ITXT_{'1' if compression else '0'}\"\n f\":{keyword.decode(encoding=UTF_8)}\"\n f\":{lang_tag.decode(encoding=UTF_8)}\"\n f\":{trans_key.decode(encoding=UTF_8)}\", itxt_data)\n case _:\n pass\n # skip crc verification\n offset += chunk_size + 4\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan each row as structure with column name in key\"\"\"\n try:\n candidates: List[Candidate] = []\n for offset, chunk_type, data in PngScanner.yield_png_chunks(data_provider.data):\n png_content_provider = DataContentProvider(data=data,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|{chunk_type}:0x{offset:x}\")\n new_limit = recursive_limit_size - len(data)\n png_candidates = self.recursive_scan(png_content_provider, depth, new_limit)\n candidates.extend(png_candidates)\n return candidates\n except Exception as exc:\n logger.warning(exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/pptx_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom pptx import Presentation\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass PptxScanner(AbstractScanner, ABC):\n \"\"\"Implements pptx scanning\"\"\"\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan pptx text elements for all slides\"\"\"\n try:\n candidates = []\n pptx_lines = []\n presentation = Presentation(io.BytesIO(data_provider.data))\n for n, slide in enumerate(presentation.slides):\n for shape in slide.shapes:\n if shape.has_text_frame:\n for paragraph in shape.text_frame.paragraphs:\n pptx_lines.append(paragraph.text)\n string_data_provider = StringContentProvider(lines=pptx_lines,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|PPTX:{n+1}\")\n pptx_candidates = self.scanner.scan(string_data_provider)\n candidates.extend(pptx_candidates)\n return candidates\n except Exception as pptx_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, pptx_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/rpm_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nimport rpmfile\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass RpmScanner(AbstractScanner, ABC):\n \"\"\"Implements rpm scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures\"\"\"\n if data.startswith(b\"\\xED\\xAB\\xEE\\xDB\"):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts files one by one from the package type and launches recursive scan\"\"\"\n try:\n candidates = []\n with rpmfile.open(fileobj=io.BytesIO(data_provider.data)) as rpm_file:\n for member in rpm_file.getmembers():\n # skip directory\n if 0 != member.isdir:\n continue\n if FilePathExtractor.check_exclude_file(self.config, member.name):\n continue\n if 0 > recursive_limit_size - member.size:\n logger.warning(\"%s: size %s is over limit %s depth:%s\", member.filename, member.size,\n recursive_limit_size, depth)\n continue\n rpm_content_provider = DataContentProvider(data=rpm_file.extractfile(member).read(),\n file_path=data_provider.file_path,\n file_type=Util.get_extension(member.name),\n info=f\"{data_provider.info}|RPM:{member.name}\")\n new_limit = recursive_limit_size - len(rpm_content_provider.data)\n rpm_candidates = self.recursive_scan(rpm_content_provider, depth, new_limit)\n candidates.extend(rpm_candidates)\n return candidates\n except Exception as rpm_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, rpm_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/rtf_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom striprtf import striprtf\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass RtfScanner(AbstractScanner, ABC):\n \"\"\"Implements squash file system scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - Rich Text Format\"\"\"\n if data.startswith(b\"{\\\\rtf1\") and data.endswith(b\"}\"):\n return True\n return False\n\n @staticmethod\n def get_lines(text: str) -> List[str]:\n \"\"\"Extracts text lines from RTF format\"\"\"\n rtf_text = striprtf.rtf_to_text(text)\n lines = Util.split_text(rtf_text)\n return lines\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Scans data as RTF\"\"\"\n try:\n string_data_provider = StringContentProvider(lines=RtfScanner.get_lines(data_provider.text),\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|RTF\")\n rtf_candidates = self.scanner.scan(string_data_provider)\n return rtf_candidates\n except Exception as rtf_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, rtf_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/sqlite3_scanner.py", "content": "import logging\nimport os.path\nimport sqlite3\nimport sys\nimport tempfile\nfrom abc import ABC\nfrom typing import List, Optional, Tuple, Any, Generator\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass Sqlite3Scanner(AbstractScanner, ABC):\n \"\"\"Implements SQLite3 database scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures - SQLite Database\"\"\"\n if data.startswith(b\"SQLite format 3\\0\"):\n return True\n return False\n\n @staticmethod\n def __walk(sqlite3db) -> Generator[Tuple[str, Any], None, None]:\n sqlite3db.row_factory = sqlite3.Row\n cursor = sqlite3db.cursor()\n cursor.execute(\"SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%';\")\n for table in cursor.fetchall():\n table_name = table[0]\n try:\n cursor.execute(f\"SELECT * FROM {table_name}\")\n for row in cursor:\n yield table_name, dict(row)\n except sqlite3.DatabaseError as exc:\n print(f\"Error reading table {table_name}: {exc}\")\n\n @staticmethod\n def walk_sqlite(data: bytes) -> Generator[Tuple[str, Any], None, None]:\n \"\"\"Yields data from sqlite3 database\"\"\"\n if 10 < sys.version_info.minor:\n # Added in version 3.11\n with sqlite3.connect(\":memory:\") as sqlite3db:\n sqlite3db.deserialize(data) # type: ignore\n yield from Sqlite3Scanner.__walk(sqlite3db)\n elif \"nt\" != os.name:\n # a tmpfile has to be used. TODO: remove when 3.10 will deprecate\n with tempfile.NamedTemporaryFile(suffix=\".sqlite\") as t:\n t.write(data)\n t.flush()\n with sqlite3.connect(t.name) as sqlite3db:\n yield from Sqlite3Scanner.__walk(sqlite3db)\n elif \"nt\" == os.name:\n # windows trick. TODO: remove when 3.10 will deprecate\n with tempfile.NamedTemporaryFile(delete=False, suffix=\".sqlite\") as t:\n t.write(data)\n t.flush()\n sqlite3db = sqlite3.connect(t.name)\n yield from Sqlite3Scanner.__walk(sqlite3db)\n sqlite3db.close()\n if os.path.exists(t.name):\n os.remove(t.name)\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts data file from .ar (debian) archive and launches data_scan\"\"\"\n try:\n candidates: List[Candidate] = []\n new_limit = recursive_limit_size - len(data_provider.data)\n for table, row in self.walk_sqlite(data_provider.data):\n struct_content_provider = StructContentProvider(struct=row,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|SQLite3.{table}\")\n if new_candidates := self.structure_scan(struct_content_provider, depth, new_limit):\n candidates.extend(new_candidates)\n return candidates\n except Exception as exc:\n logger.warning(exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/strings_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional, Tuple\n\nfrom credsweeper.common.constants import MIN_DATA_LEN\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass StringsScanner(AbstractScanner, ABC):\n \"\"\"Implements known binary file scanning with ASCII strings representations\"\"\"\n\n @staticmethod\n def get_enumerated_lines(data: bytes) -> List[Tuple[int, str]]:\n \"\"\"Processes binary to found ASCII strings. Use offset instead line number.\"\"\"\n enumerated_lines = []\n offset = -1\n line_items = []\n for n, x in enumerate(data):\n if 0x09 == x or 0x20 <= x <= 0x7E:\n # TAB, SPACE and visible ASCII symbols\n if 0 > offset:\n # use start of string as line number\n offset = n\n line_items.append(chr(x))\n continue\n if MIN_DATA_LEN <= len(line_items):\n # add valuable lines only\n enumerated_lines.append((offset, ''.join(line_items)))\n offset = -1\n line_items.clear()\n if MIN_DATA_LEN <= len(line_items):\n enumerated_lines.append((offset, ''.join(line_items)))\n return enumerated_lines\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Scan binary files for ASCII strings\"\"\"\n if strings := StringsScanner.get_enumerated_lines(data_provider.data):\n string_data_provider = StringContentProvider(lines=[x[1] for x in strings],\n line_numbers=[x[0] for x in strings],\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|STRINGS\")\n return self.scanner.scan(string_data_provider)\n return None if strings is None else []\n" }, { "path": "credsweeper/deep_scanner/tar_scanner.py", "content": "import contextlib\nimport io\nimport logging\nimport tarfile\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass TarScanner(AbstractScanner, ABC):\n \"\"\"Implements tar scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures\"\"\"\n if 512 <= len(data) and 257 == data.find(b\"\\x75\\x73\\x74\\x61\\x72\", 257, 262) \\\n and (262 == data.find(b\"\\x00\\x30\\x30\", 262, 265)\n or 262 == data.find(b\"\\x20\\x20\\x00\", 262, 265)):\n with contextlib.suppress(Exception):\n chksum = tarfile.nti(data[148:156]) # type: ignore\n unsigned_chksum, signed_chksum = tarfile.calc_chksums(data) # type: ignore\n if chksum == unsigned_chksum or chksum == signed_chksum:\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts files one by one from tar archive and launches data_scan\"\"\"\n try:\n candidates = []\n with tarfile.TarFile(fileobj=io.BytesIO(data_provider.data)) as tf:\n for tfi in tf.getmembers():\n # skip directory\n if not tfi.isreg():\n continue\n if FilePathExtractor.check_exclude_file(self.config, tfi.name):\n continue\n if 0 > recursive_limit_size - tfi.size:\n logger.warning(\"%s: size %s is over limit %s depth:%s\", tfi.name, tfi.size,\n recursive_limit_size, depth)\n continue\n with tf.extractfile(tfi) as f:\n tar_content_provider = DataContentProvider(data=f.read(),\n file_path=data_provider.file_path,\n file_type=Util.get_extension(tfi.name),\n info=f\"{data_provider.info}|TAR:{tfi.name}\")\n # Nevertheless, use extracted data size\n new_limit = recursive_limit_size - len(tar_content_provider.data)\n tar_candidates = self.recursive_scan(tar_content_provider, depth, new_limit)\n candidates.extend(tar_candidates)\n return candidates\n except Exception as tar_exc:\n # too many exception types might be produced with broken tar\n logger.warning(\"%s:%s\", data_provider.file_path, tar_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/tmx_scanner.py", "content": "import logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom lxml import etree\n\nfrom credsweeper.common.constants import MIN_DATA_LEN, MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass TmxScanner(AbstractScanner, ABC):\n \"\"\"Realises tmX files scanning for values only. Image tags are skipped.\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Used to detect tm7,tm6,etc. (ThreadModeling) format.\"\"\"\n for opening_tag, closing_tag in [(b\"\"),\n (b\"\")]:\n opening_pos = data.find(opening_tag, 0, MAX_LINE_LENGTH)\n if 0 <= opening_pos < data.find(closing_tag, opening_pos):\n # opening and closing tags were found - suppose it is an HTML\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to represent data as xml text and scan as text lines\"\"\"\n try:\n lines = []\n # the format is always in single line xlm, so line numbers are not actual\n tree = etree.fromstring(data_provider.data)\n for element in tree.iter():\n tag = Util.extract_element_data(element, \"tag\")\n if \"Image\" in tag:\n continue\n text = Util.extract_element_data(element, \"text\")\n if MIN_DATA_LEN > len(text):\n continue\n lines.append(text)\n tmx_data_provider = StringContentProvider(lines=lines,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|TMX\")\n return self.scanner.scan(tmx_data_provider)\n except Exception as exc:\n logger.warning(\"Cannot processed tmX file %s %s\", str(data_provider.file_path), str(exc))\n return None\n" }, { "path": "credsweeper/deep_scanner/xlsx_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\n\nimport pandas as pd\n\nfrom credsweeper.credentials.augment_candidates import augment_candidates\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass XlsxScanner(AbstractScanner, ABC):\n \"\"\"Implements xlsx scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures\"\"\"\n if data.startswith(b\"\\xD0\\xCF\\x11\\xE0\\xA1\\xB1\\x1A\\xE1\"):\n # Compound File Binary Format: doc, xls, ppt, msi, msg\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to scan xlsx text elements for all slides\"\"\"\n try:\n candidates = []\n book = pd.read_excel(io.BytesIO(data_provider.data), sheet_name=None, header=None)\n for sheet_name, sheet_data in book.items():\n sheet_info = f\"{data_provider.info}|{sheet_name}\"\n # replace open xml carriage returns _x000D_ before line feed only\n df = sheet_data.replace(to_replace=\"_x000D_\\n\", value='\\n', regex=True).fillna('').astype(str)\n for row_pos, row in enumerate(df.values):\n for col_pos, cell in enumerate(row):\n cell_info = f\"{sheet_info}:{Util.get_excel_column_name(col_pos)}{row_pos + 1}\"\n cell_provider = StringContentProvider(lines=cell.splitlines(),\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=cell_info)\n cell_candidates = self.scanner.scan(cell_provider)\n candidates.extend(cell_candidates)\n row_line = '\\t'.join(row)\n row_provider = StringContentProvider(lines=[row_line],\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{sheet_info}:R{row_pos + 1}\")\n row_candidates = self.scanner.scan(row_provider)\n augment_candidates(candidates, row_candidates)\n\n return candidates\n except Exception as xlsx_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, xlsx_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/xml_scanner.py", "content": "import logging\nimport re\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass XmlScanner(AbstractScanner, ABC):\n \"\"\"Realises xml scanning\"\"\"\n\n # A well-formed XML must start from < or a whitespace character\n XML_FIRST_BRACKET_PATTERN = re.compile(rb\"^\\s*<\")\n XML_OPENING_TAG_PATTERN = re.compile(rb\"<([0-9A-Za-z_]{1,256})\")\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Used to detect xml format from raw bytes\"\"\"\n if XmlScanner.XML_FIRST_BRACKET_PATTERN.search(data, 0, MAX_LINE_LENGTH):\n if first_bracket_match := XmlScanner.XML_OPENING_TAG_PATTERN.search(data, 0, MAX_LINE_LENGTH):\n start_pos = first_bracket_match.start()\n closing_tag = b\"\"\n if start_pos < data.find(closing_tag, start_pos):\n return True\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Tries to represent data as xml text and scan as text lines\"\"\"\n if result := data_provider.represent_as_xml():\n string_data_provider = StringContentProvider(lines=data_provider.lines,\n line_numbers=data_provider.line_numbers,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|XML\")\n return self.scanner.scan(string_data_provider)\n return None if result is None else []\n" }, { "path": "credsweeper/deep_scanner/zip_scanner.py", "content": "import io\nimport logging\nfrom abc import ABC\nfrom typing import List, Optional\nfrom zipfile import ZipFile\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass ZipScanner(AbstractScanner, ABC):\n \"\"\"Implements zip scanning\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"According https://en.wikipedia.org/wiki/List_of_file_signatures\"\"\"\n if data.startswith(b\"PK\") and 4 <= len(data):\n if 0x03 == data[2] and 0x04 == data[3]:\n # normal PK\n return True\n if 0x05 == data[2] and 0x06 == data[3]:\n # empty archive - no sense to scan in other scanners, so let it be a zip\n return True\n if 0x07 == data[2] and 0x08 == data[3]:\n # spanned archive - NOT SUPPORTED\n return False\n return False\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Extracts files one by one from zip archives and launches data_scan\"\"\"\n try:\n candidates = []\n with ZipFile(io.BytesIO(data_provider.data)) as zf:\n for zfl in zf.infolist():\n # skip directory\n if zfl.is_dir():\n continue\n if FilePathExtractor.check_exclude_file(self.config, zfl.filename):\n continue\n if 0 > recursive_limit_size - zfl.file_size:\n logger.warning(\"%s: size %s is over limit %s depth:%s\", zfl.filename, zfl.file_size,\n recursive_limit_size, depth)\n continue\n with zf.open(zfl) as f:\n zip_content_provider = DataContentProvider(data=f.read(),\n file_path=data_provider.file_path,\n file_type=Util.get_extension(zfl.filename),\n info=f\"{data_provider.info}|ZIP:{zfl.filename}\")\n # nevertheless use extracted data size\n new_limit = recursive_limit_size - len(zip_content_provider.data)\n zip_candidates = self.recursive_scan(zip_content_provider, depth, new_limit)\n candidates.extend(zip_candidates)\n return candidates\n except Exception as zip_exc:\n # too many exception types might be produced with broken zip\n logger.warning(\"%s:%s\", data_provider.file_path, zip_exc)\n return None\n" }, { "path": "credsweeper/deep_scanner/zlib_scanner.py", "content": "import logging\nimport zlib\nfrom abc import ABC\nfrom typing import List, Optional\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass ZlibScanner(AbstractScanner, ABC):\n \"\"\"Implements zlib data inflate and scan\"\"\"\n\n @staticmethod\n def match(data: bytes | bytearray) -> bool:\n \"\"\"Returns True if data looks like deflated data with zlib\"\"\"\n if 6 < len(data):\n cmf = data[0]\n flg = data[1]\n if 8 == (0xF & cmf) and 7 >= (cmf >> 4) and 0 == ((cmf << 8) | flg) % 31 and 0 == (0x20 & flg):\n if 0x3 != (data[2] >> 1):\n # the last check of impossible bits\n return True\n return False\n\n @staticmethod\n def decompress(limit: int, data: bytes) -> bytes:\n \"\"\"Returns decompressed data by chunks with a limit or exception in unusual cases\"\"\"\n zlib_obj = zlib.decompressobj()\n result = zlib_obj.decompress(data, max_length=limit)\n if zlib_obj.unconsumed_tail:\n raise ValueError(f\"Limit exceeds for {len(zlib_obj.unconsumed_tail)}\")\n if not zlib_obj.eof:\n raise ValueError(\"Truncated zlib stream\")\n if zlib_obj.unused_data:\n raise ValueError(f\"Unused data {len(zlib_obj.unused_data)}\")\n return result\n\n def data_scan(\n self, #\n data_provider: DataContentProvider, #\n depth: int, #\n recursive_limit_size: int) -> Optional[List[Candidate]]:\n \"\"\"Inflate data from zlib compressed and launches data_scan\"\"\"\n try:\n decompressed = ZlibScanner.decompress(recursive_limit_size, data_provider.data)\n zlib_content_provider = DataContentProvider(data=decompressed,\n file_path=data_provider.file_path,\n file_type=data_provider.file_type,\n info=f\"{data_provider.info}|ZLIB\")\n new_limit = recursive_limit_size - len(decompressed)\n zlib_candidates = self.recursive_scan(zlib_content_provider, depth, new_limit)\n return zlib_candidates\n except Exception as zlib_exc:\n logger.warning(\"%s:%s\", data_provider.file_path, zlib_exc)\n return None\n" }, { "path": "credsweeper/file_handler/__init__.py", "content": "" }, { "path": "credsweeper/file_handler/abstract_provider.py", "content": "import io\nfrom abc import ABC, abstractmethod\nfrom pathlib import Path\nfrom typing import Union, Tuple, Sequence\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.content_provider import ContentProvider\n\n\nclass AbstractProvider(ABC):\n \"\"\"Base class for all files provider objects.\"\"\"\n\n def __init__(self, paths: Sequence[Union[str, Path, io.BytesIO, Tuple[Union[str, Path], io.BytesIO]]]) -> None:\n \"\"\"Initialize Files Provider object for 'paths'.\n\n Args:\n paths: file paths list to scan or io.BytesIO or tuple with both\n\n \"\"\"\n self.paths = paths\n\n @property\n def paths(self) -> Sequence[Union[str, Path, io.BytesIO, Tuple[Union[str, Path], io.BytesIO]]]:\n \"\"\"paths getter\"\"\"\n return self.__paths\n\n @paths.setter\n def paths(self, paths: Sequence[Union[str, Path, io.BytesIO, Tuple[Union[str, Path], io.BytesIO]]]) -> None:\n \"\"\"paths setter\"\"\"\n self.__paths = paths\n\n @abstractmethod\n def get_scannable_files(self, config: Config) -> Sequence[ContentProvider]:\n \"\"\"Get list of file object for analysis based on attribute \"paths\".\n\n Args:\n config: dict of credsweeper configuration\n\n Return:\n file objects to analyse\n\n \"\"\"\n raise NotImplementedError()\n" }, { "path": "credsweeper/file_handler/analysis_target.py", "content": "from functools import cached_property\nfrom typing import List, Optional\n\nfrom credsweeper.file_handler.descriptor import Descriptor\n\n\nclass AnalysisTarget:\n \"\"\"AnalysisTarget\"\"\"\n\n def __init__(\n self,\n line_pos: int,\n lines: List[str],\n line_nums: List[int],\n descriptor: Descriptor,\n line: Optional[str] = None,\n offset: Optional[int] = None,\n ):\n self.__line_pos = line_pos\n self.__lines = lines\n self.__line_nums = line_nums\n self.__descriptor = descriptor\n self.__line = line\n self.__offset = offset\n\n @cached_property\n def offset(self) -> Optional[int]:\n \"\"\"cached value\"\"\"\n # when the offset is not None - it means that original line was split into chunks\n return self.__offset\n\n @cached_property\n def line(self) -> str:\n \"\"\"cached value\"\"\"\n if self.__line is None:\n # normal target\n return self.__lines[self.__line_pos]\n # chunked target\n return self.__line\n\n @cached_property\n def line_len(self) -> int:\n \"\"\"cached value\"\"\"\n return len(self.line)\n\n @cached_property\n def line_strip(self) -> str:\n \"\"\"cached value\"\"\"\n return self.line.strip()\n\n @cached_property\n def line_strip_len(self) -> int:\n \"\"\"cached value\"\"\"\n return len(self.line_strip)\n\n @cached_property\n def line_lower(self) -> str:\n \"\"\"cached value\"\"\"\n return self.line.lower()\n\n @cached_property\n def line_lower_strip(self) -> str:\n \"\"\"cached value\"\"\"\n return self.line_lower.strip()\n\n @cached_property\n def lines(self) -> List[str]:\n \"\"\"cached value\"\"\"\n return self.__lines\n\n @cached_property\n def lines_len(self) -> int:\n \"\"\"cached value\"\"\"\n return len(self.__lines)\n\n @cached_property\n def line_pos(self) -> int:\n \"\"\"cached value\"\"\"\n return self.__line_pos\n\n @cached_property\n def line_num(self) -> int:\n \"\"\"cached value\"\"\"\n return self.__line_nums[self.__line_pos]\n\n @cached_property\n def line_nums(self) -> List[int]:\n \"\"\"cached value\"\"\"\n return self.__line_nums\n\n @cached_property\n def file_path(self) -> Optional[str]:\n \"\"\"cached value\"\"\"\n return self.__descriptor.path\n\n @cached_property\n def file_type(self) -> Optional[str]:\n \"\"\"cached value\"\"\"\n return self.__descriptor.extension\n\n @cached_property\n def info(self) -> Optional[str]:\n \"\"\"cached value\"\"\"\n return self.__descriptor.info\n\n @cached_property\n def descriptor(self) -> Descriptor:\n \"\"\"cached value\"\"\"\n return self.__descriptor\n" }, { "path": "credsweeper/file_handler/byte_content_provider.py", "content": "import logging\nfrom functools import cached_property\nfrom typing import List, Optional, Generator\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass ByteContentProvider(ContentProvider):\n \"\"\"Allow to scan byte sequence instead of extra reading a file\"\"\"\n\n def __init__(\n self, #\n content: bytes, #\n file_path: Optional[str] = None, #\n file_type: Optional[str] = None, #\n info: Optional[str] = None) -> None:\n \"\"\"\n Parameters:\n content: The bytes are transformed to an array of lines with split by new line character.\n\n \"\"\"\n super().__init__(file_path=file_path, file_type=file_type, info=info)\n self.__data = content\n self.__lines: Optional[List[str]] = None\n\n @cached_property\n def data(self) -> Optional[bytes]:\n \"\"\"data RO getter for ByteContentProvider\"\"\"\n return self.__data\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__data = None\n if \"data\" in self.__dict__:\n delattr(self, \"data\")\n self.__lines = None\n if \"lines\" in self.__dict__:\n delattr(self, \"lines\")\n\n @cached_property\n def lines(self) -> List[str]:\n \"\"\"lines RO getter for ByteContentProvider\"\"\"\n if self.__lines is None:\n text = Util.decode_text(self.__data)\n if text is None:\n if not self.info.endswith(\"|BASE64|RAW\"):\n # avoid extra warnings for the hypothesis\n logger.warning(\"Binary data detected %s %s %s\", self.file_path, self.info,\n repr(self.__data[:32]) if isinstance(self.__data, bytes) else \"NONE\")\n self.__lines = []\n else:\n self.__lines = Util.split_text(text)\n return self.__lines if self.__lines is not None else []\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Return lines to scan.\n\n Args:\n min_len: minimal line length to scan\n\n Return:\n list of analysis targets based on every row in a content\n\n \"\"\"\n return self.lines_to_targets(min_len, self.lines)\n" }, { "path": "credsweeper/file_handler/content_provider.py", "content": "import logging\nfrom abc import ABC, abstractmethod\nfrom functools import cached_property\nfrom typing import List, Optional, Generator\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass ContentProvider(ABC):\n \"\"\"Base class to provide access to analysis targets for scanned object.\"\"\"\n\n def __init__(\n self, #\n file_path: Optional[str] = None, #\n file_type: Optional[str] = None, #\n info: Optional[str] = None) -> None:\n \"\"\"\n Parameters:\n file_path: optional string. Might be specified if you know the file name where data were taken from.\n file_type: optional string. File extension e.g. \".java\". It might be obtained from file_path if not given.\n info: optional string. Any information to help understand how a credential was found.\n\n \"\"\"\n _file_path: str = file_path or \"\"\n _file_type: str = file_type if file_type is not None else Util.get_extension(file_path)\n _info: str = info or \"\"\n self.__descriptor = Descriptor(_file_path, _file_type, _info)\n\n @abstractmethod\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Load and preprocess file diff data to scan.\n\n Args:\n min_len: minimal line length to scan\n\n Return:\n row objects to analysing\n\n \"\"\"\n raise NotImplementedError()\n\n @cached_property\n def descriptor(self) -> Descriptor:\n \"\"\"descriptor getter\"\"\"\n return self.__descriptor\n\n @cached_property\n def file_path(self) -> str:\n \"\"\"file_path getter\"\"\"\n return self.__descriptor.path\n\n @cached_property\n def file_type(self) -> str:\n \"\"\"file_type getter\"\"\"\n return self.__descriptor.extension\n\n @cached_property\n def info(self) -> str:\n \"\"\"info getter\"\"\"\n return self.__descriptor.info\n\n @cached_property\n @abstractmethod\n def data(self) -> Optional[bytes]:\n \"\"\"abstract data getter\"\"\"\n raise NotImplementedError(__name__)\n\n @abstractmethod\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n raise NotImplementedError(__name__)\n\n def lines_to_targets(\n self, #\n min_len: int,\n lines: List[str], #\n line_nums: Optional[List[int]] = None) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Creates list of targets with multiline concatenation\"\"\"\n lines_range = range(len(lines))\n if line_nums is None or len(line_nums) != len(lines):\n if line_nums is not None:\n logger.warning(\"Line numerations %s does not match lines %s. Plain numeration applied\", len(line_nums),\n len(lines))\n line_nums = [1 + x for x in lines_range]\n\n for line_pos in lines_range:\n line = lines[line_pos]\n if min_len > len(line.strip()):\n # Ignore target if stripped part is too short for all types\n continue\n if MAX_LINE_LENGTH < len(line):\n for chunk_start, chunk_end in Util.get_chunks(len(line)):\n target = AnalysisTarget(\n line_pos=line_pos, #\n lines=lines, #\n line_nums=line_nums, #\n descriptor=self.descriptor, #\n line=line[chunk_start:chunk_end], #\n offset=chunk_start)\n yield target\n else:\n target = AnalysisTarget(line_pos, lines, line_nums, self.descriptor)\n yield target\n" }, { "path": "credsweeper/file_handler/data_content_provider.py", "content": "import json\nimport logging\nimport warnings\nfrom functools import cached_property\nfrom typing import List, Optional, Any, Generator, Callable, Tuple\n\nimport yaml\nfrom bs4 import BeautifulSoup, Tag, XMLParsedAsHTMLWarning\n\nfrom credsweeper.common.constants import MIN_DATA_LEN\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.utils.util import Util\n\nwarnings.filterwarnings(\"ignore\", category=XMLParsedAsHTMLWarning, module='bs4')\nlogger = logging.getLogger(__name__)\n\n# 12345678 - minimal xml with a credential\nMIN_XML_LEN = 16\n\n\nclass DataContentProvider(ContentProvider):\n \"\"\"Dummy raw provider to keep bytes\"\"\"\n\n def __init__(\n self, #\n data: bytes, #\n file_path: Optional[str] = None, #\n file_type: Optional[str] = None, #\n info: Optional[str] = None) -> None:\n \"\"\"\n Parameters:\n data: byte sequence to be stored for deep analysis\n\n \"\"\"\n super().__init__(file_path=file_path, file_type=file_type, info=info)\n self.__data = data\n self.__text: Optional[str] = None\n self.structure: Optional[List[Any]] = None\n self.decoded: Optional[bytes] = None\n self.lines: List[str] = []\n self.line_numbers: List[int] = []\n self.__html_lines_size = len(data) # the size is used to limit extra memory consumption during html combination\n\n @cached_property\n def data(self) -> Optional[bytes]:\n \"\"\"data RO getter for DataContentProvider and the property is used in deep scan\"\"\"\n return self.__data\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__data = None\n if \"data\" in self.__dict__:\n delattr(self, \"data\")\n self.__text = None\n if \"text\" in self.__dict__:\n delattr(self, \"text\")\n self.structure = None\n self.decoded = None\n self.lines = []\n self.line_numbers = []\n\n @cached_property\n def text(self) -> str:\n \"\"\"Getter to produce a text from DEFAULT_ENCODING. Empty str for unrecognized data\"\"\"\n if self.__text is None:\n self.__text = Util.decode_text(self.__data) or ''\n return self.__text\n\n def __is_structure(self) -> bool:\n \"\"\"Check whether a structure was recognized\"\"\"\n return self.structure is not None and (isinstance(self.structure, dict) and 0 < len(self.structure.keys())\n or isinstance(self.structure, list) and 0 < len(self.structure))\n\n def represent_as_structure(self) -> Optional[bool]:\n \"\"\"Tries to convert data with many parsers. Stores result to internal structure\n\n Return:\n True if some structure found\n False if no data found\n None if the format is not acceptable\n\n \"\"\"\n if MIN_DATA_LEN > len(self.text):\n return False\n # JSON & NDJSON\n if '{' in self.text and '}' in self.text and '\"' in self.text and ':' in self.text:\n try:\n self.structure = json.loads(self.text)\n logger.debug(\"CONVERTED from json\")\n except Exception as exc:\n logger.debug(\"Cannot parse as json:%s %s\", exc, self.data)\n else:\n if self.__is_structure():\n return True\n try:\n self.structure = []\n for line in self.text.splitlines():\n # each line must be in json format, otherwise - exception rises\n self.structure.append(json.loads(line))\n logger.debug(\"CONVERTED from ndjson\")\n except Exception as exc:\n logger.debug(\"Cannot parse as ndjson:%s %s\", exc, self.data)\n self.structure = None\n else:\n if self.__is_structure():\n return True\n else:\n logger.debug(\"Data do not contain { - weak JSON\")\n\n # # # Python\n try:\n # search only in sources with strings\n if (';' in self.text or 2 < self.text.count('\\n') or 2 < self.text.count('\\r')) \\\n and ('\"' in self.text or \"'\" in self.text):\n self.structure = Util.parse_python(self.text)\n logger.debug(\"CONVERTED from Python\")\n else:\n logger.debug(\"Data do not contain line feed - weak PYTHON\")\n except Exception as exc:\n logger.debug(\"Cannot parse as Python:%s %s\", exc, self.data)\n else:\n if self.__is_structure():\n return True\n # # # YAML - almost always recognized\n try:\n if ':' in self.text and (2 < self.text.count('\\n') or 2 < self.text.count('\\r')):\n self.structure = yaml.safe_load(self.text)\n logger.debug(\"CONVERTED from yaml\")\n else:\n logger.debug(\"Data do not contain colon mark - weak YAML\")\n except Exception as exc:\n logger.debug(\"Cannot parse as yaml:%s %s\", exc, self.data)\n else:\n if self.__is_structure():\n return True\n # # # None of above\n return None\n\n def represent_as_xml(self) -> Optional[bool]:\n \"\"\"Tries to read data as xml\n\n Return:\n True if reading was successful\n False if no data found\n None if the format is not acceptable\n\n \"\"\"\n if MIN_XML_LEN > len(self.text):\n return False\n try:\n if '<' in self.text and '>' in self.text and \" Optional[Tuple[int, str]]:\n \"\"\"multiline cell will be analysed as text or return single line from cell\n returns line number and one line for analysis\n If there are no text or the text will be analysed as multiline - it returns None\"\"\"\n # use not stripped get_text, otherwise all format is cleaned\n cell_text = cell.get_text()\n cell_lines = cell_text.splitlines()\n line_numbers: List[int] = []\n stripped_lines: List[str] = []\n for offset, line in enumerate(cell_lines):\n if stripped_line := line.strip():\n line_numbers.append(cell.sourceline + offset)\n stripped_lines.append(stripped_line)\n\n if not stripped_lines:\n return None\n if 1 == len(stripped_lines):\n return line_numbers[0], stripped_lines[0]\n # otherwise the cell will be analyzed as multiline text\n self.line_numbers.extend(line_numbers)\n self.lines.extend(stripped_lines)\n self.__html_lines_size += sum(len(x) for x in stripped_lines)\n return None\n\n @staticmethod\n def simple_html_representation(html: BeautifulSoup) -> Tuple[List[int], List[str], int]:\n \"\"\"simple parse as it is displayed to user and appends the lines\"\"\"\n line_numbers: List[int] = []\n lines: List[str] = []\n lines_size = 0\n # use dedicated variable to deal with yapf and flake\n tags_to_split = [\n \"p\", \"br\", \"tr\", \"li\", \"ol\", \"h1\", \"h2\", \"h3\", \"h4\", \"h5\", \"h6\", \"blockquote\", \"pre\", \"div\", \"th\", \"td\"\n ]\n for p in html.find_all(tags_to_split):\n p.append('\\t')\n html_lines = html.get_text().splitlines()\n for line_number, doc_line in enumerate(html_lines):\n line = doc_line.strip()\n if line:\n line_numbers.append(line_number + 1)\n lines.append(line)\n lines_size += len(line)\n return line_numbers, lines, lines_size\n\n @staticmethod\n def _table_depth_reached(table: Tag, depth: int) -> bool:\n if parent := table.parent:\n if isinstance(parent, BeautifulSoup):\n return False\n if 0 > depth:\n return True\n if \"table\" == parent.name:\n depth -= 1\n return DataContentProvider._table_depth_reached(parent, depth)\n return True\n\n def _table_representation(\n self, #\n table: Tag, #\n depth: int, #\n recursive_limit_size: int, #\n keywords_required_substrings_check: Callable[[str], bool]):\n \"\"\"\n transform table if table cell is assigned to header cell\n make from cells a chain like next is assigned to previous\n \"\"\"\n if DataContentProvider._table_depth_reached(table, depth):\n logger.warning(\"Recursive depth limit was reached during HTML table combinations\")\n return\n table_header: Optional[List[Optional[str]]] = None\n rowspan_columns = []\n for tr in table.find_all(\"tr\"):\n if recursive_limit_size < self.__html_lines_size:\n # weird tables may lead to oversize memory\n break\n record_numbers = []\n record_lines = []\n record_leading = None\n if table_header is None:\n table_header = []\n # first row in table may be a header with and a style, but search too\n for cell in tr.find_all([\"th\", \"td\"]):\n if recursive_limit_size < self.__html_lines_size:\n # keep the duplicates for early breaks!\n break\n colspan_header = int(cell.get(\"colspan\", 1))\n if td_numbered_line := self._check_multiline_cell(cell):\n td_text = td_numbered_line[1]\n td_text_has_keywords = keywords_required_substrings_check(td_text.lower())\n for _ in range(colspan_header):\n rowspan_header = int(cell.get(\"rowspan\", 1))\n rowspan_columns.append(rowspan_header)\n if td_text_has_keywords:\n table_header.append(td_text)\n else:\n table_header.append(None)\n if record_leading is None:\n if td_text_has_keywords:\n record_leading = td_text\n else:\n record_leading = \"\"\n else:\n record_numbers.append(td_numbered_line[0])\n record_lines.append(f\"{record_leading} : {td_text}\")\n # add single text to lines for analysis\n self.line_numbers.append(td_numbered_line[0])\n self.lines.append(td_text)\n self.__html_lines_size += len(td_text)\n else:\n # empty cell or multiline cell\n for _ in range(colspan_header):\n # number of columns is defined with header only\n rowspan_header = int(cell.get(\"rowspan\", 1))\n rowspan_columns.append(rowspan_header)\n table_header.append(None)\n else:\n header_pos = 0\n # not a first line in table - may be combined with a header\n for cell in tr.find_all(\"td\"):\n if recursive_limit_size < self.__html_lines_size:\n # keep the duplicates for early breaks!\n break\n while header_pos < len(rowspan_columns) and 1 < rowspan_columns[header_pos]:\n rowspan_columns[header_pos] -= 1\n header_pos += 1\n colspan_cell = int(cell.get(\"colspan\", 1))\n rowspan_cell = int(cell.get(\"rowspan\", 1))\n for i in range(header_pos, header_pos + colspan_cell):\n if i < len(rowspan_columns):\n rowspan_columns[i] += rowspan_cell - 1\n if td_numbered_line := self._check_multiline_cell(cell):\n td_text = td_numbered_line[1]\n if record_leading is None:\n td_text_has_keywords = keywords_required_substrings_check(td_text.lower())\n if td_text_has_keywords:\n record_leading = td_text\n else:\n record_leading = \"\"\n elif record_leading:\n record_numbers.append(td_numbered_line[0])\n record_lines.append(f\"{record_leading} : {td_text}\")\n if header_pos < len(table_header):\n if header_text := table_header[header_pos]:\n self.line_numbers.append(td_numbered_line[0])\n self.lines.append(f\"{header_text} : {td_text}\")\n self.__html_lines_size += len(td_text)\n else:\n # empty cell or multiline cell\n table_header.append(None)\n header_pos += colspan_cell\n if record_lines:\n # add combinations with left column\n self.line_numbers.extend(record_numbers)\n self.lines.extend(record_lines)\n self.__html_lines_size += sum(len(x) for x in record_lines)\n\n def _html_tables_representation(\n self, #\n html: BeautifulSoup, #\n depth: int, #\n recursive_limit_size: int, #\n keywords_required_substrings_check: Callable[[str], bool]):\n \"\"\"Iterates for all tables in html to explore cells and their combinations\"\"\"\n depth -= 1\n if 0 > depth:\n return\n for table in html.find_all(\"table\"):\n if recursive_limit_size < self.__html_lines_size:\n logger.warning(\"Recursive size limit was reached during HTML table combinations\")\n break\n self._table_representation(table, depth, recursive_limit_size, keywords_required_substrings_check)\n\n def represent_as_html(\n self, #\n depth: int, #\n recursive_limit_size: int, #\n keywords_required_substrings_check: Callable[[str], bool]) -> Optional[bool]:\n \"\"\"Tries to read data as html\n\n Return:\n True if reading was successful\n False if no data found\n None if the format is not acceptable\n\n \"\"\"\n try:\n if \"\" in self.text:\n if html := BeautifulSoup(self.text, features=\"html.parser\"):\n line_numbers, lines, lines_size = self.simple_html_representation(html)\n self.line_numbers.extend(line_numbers)\n self.lines.extend(lines)\n self.__html_lines_size += lines_size\n # apply recursive_limit_size/2 to reduce extra calculation\n # of all accompanying losses per objects allocation\n self._html_tables_representation(html, depth, recursive_limit_size >> 1,\n keywords_required_substrings_check)\n logger.debug(\"CONVERTED from html\")\n else:\n logger.debug(\"Data do not contain specific tags - weak HTML\")\n except Exception as exc:\n logger.debug(\"Cannot parse as HTML:%s %s\", exc, self.data)\n else:\n return bool(self.lines and self.line_numbers)\n return None\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Return nothing. The class provides only data storage.\n\n Args:\n min_len: minimal line length to scan\n\n Raise:\n NotImplementedError\n\n \"\"\"\n raise NotImplementedError()\n" }, { "path": "credsweeper/file_handler/descriptor.py", "content": "from dataclasses import dataclass\n\n\n@dataclass(frozen=True)\nclass Descriptor:\n \"\"\"Descriptor for file - optimize memory consumption\"\"\"\n path: str\n extension: str\n info: str\n" }, { "path": "credsweeper/file_handler/diff_content_provider.py", "content": "import logging\nfrom dataclasses import dataclass\nfrom functools import cached_property\nfrom typing import List, Tuple, Generator, TypedDict, Optional, Union, Any, Dict, cast\n\nimport whatthepatch\n\nfrom credsweeper.common.constants import DiffRowType\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\n\nlogger = logging.getLogger(__name__)\n\nDiffDict = TypedDict(\n \"DiffDict\",\n {\n \"old\": Optional[int], #\n \"new\": Optional[int], #\n \"line\": Union[str, bytes], # bytes are possibly since whatthepatch v1.0.4\n \"hunk\": Any # not used\n })\n\n\n@dataclass(frozen=True)\nclass DiffRowData:\n \"\"\"Class for keeping data of diff row.\"\"\"\n\n line_type: DiffRowType\n line_numb: int\n line: str\n\n\nclass DiffContentProvider(ContentProvider):\n \"\"\"Provide data from a single `.patch` file.\n\n Parameters:\n file_path: path to file\n change_type: set added or deleted file data to scan\n diff: list of file row changes, with base elements represented as::\n\n {\n \"old\": line number before diff,\n \"new\": line number after diff,\n \"line\": line text,\n \"hunk\": diff hunk number\n }\n\n \"\"\"\n\n def __init__(\n self, #\n file_path: str, #\n change_type: DiffRowType, #\n diff: List[DiffDict]) -> None:\n super().__init__(file_path=file_path, info=f\"{file_path}:{change_type.value}\")\n self.__change_type = change_type\n self.__diff = diff\n\n @cached_property\n def data(self) -> bytes:\n \"\"\"data getter for DiffContentProvider\"\"\"\n raise NotImplementedError(__name__)\n\n @cached_property\n def diff(self) -> List[DiffDict]:\n \"\"\"diff getter for DiffContentProvider\"\"\"\n return self.__diff\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__diff = []\n if \"diff\" in self.__dict__:\n delattr(self, \"diff\")\n\n @staticmethod\n def parse_lines_data(change_type: DiffRowType, lines_data: List[DiffRowData]) -> Tuple[List[int], List[str]]:\n \"\"\"Parse diff lines data.\n\n Return list of line numbers with change type \"self.change_type\" and list of all lines in file\n in original order(replaced all lines not mentioned in diff file with blank line)\n\n Args:\n change_type: set added or deleted file data to scan\n lines_data: data of all rows mentioned in diff file\n\n Return:\n tuple of line numbers with change type \"self.change_type\" and all file lines\n in original order(replaced all lines not mentioned in diff file with blank line)\n\n \"\"\"\n change_numbs = []\n all_lines = []\n for line_data in lines_data:\n if line_data.line_type == change_type:\n change_numbs.append(line_data.line_numb)\n all_lines.append(line_data.line)\n return change_numbs, all_lines\n\n @staticmethod\n def patch2files_diff(raw_patch: List[str], change_type: DiffRowType) -> Dict[str, List[DiffDict]]:\n \"\"\"Generate files changes from patch for added or deleted filepaths.\n\n Args:\n raw_patch: git patch file content\n change_type: change type to select, DiffRowType.ADDED or DiffRowType.DELETED\n\n Return:\n return dict with ``{file paths: list of file row changes}``, where\n elements of list of file row changes represented as::\n\n {\n \"old\": line number before diff,\n \"new\": line number after diff,\n \"line\": line text,\n \"hunk\": diff hunk number\n }\n\n \"\"\"\n if not raw_patch:\n return {}\n\n added_files: Dict[str, List[DiffDict]] = {}\n deleted_files: Dict[str, List[DiffDict]] = {}\n try:\n for patch in whatthepatch.parse_patch(raw_patch):\n if patch.changes is None:\n logger.warning(\"Patch '%s' cannot be scanned\", str(patch.header))\n continue\n changes: List[DiffDict] = []\n for change in patch.changes:\n change_dict = cast(DiffDict, change._asdict())\n changes.append(change_dict)\n if patch.header:\n added_files[patch.header.new_path] = changes\n deleted_files[patch.header.old_path] = changes\n if change_type == DiffRowType.ADDED:\n return added_files\n if change_type == DiffRowType.DELETED:\n return deleted_files\n logger.error(\"Change type should be one of: '%s', '%s'; but received %s\", DiffRowType.ADDED,\n DiffRowType.DELETED, change_type)\n except Exception as exc:\n logger.warning(exc)\n return {}\n\n @staticmethod\n def preprocess_diff_rows(\n added_line_number: Optional[int], #\n deleted_line_number: Optional[int], #\n line: str) -> List[DiffRowData]:\n \"\"\"Auxiliary function to extend diff changes.\n\n Args:\n added_line_number: number of added line or None\n deleted_line_number: number of deleted line or None\n line: the text line\n\n Return:\n diff rows data with as list of row change type, line number, row content\n\n \"\"\"\n rows_data: List[DiffRowData] = []\n if isinstance(added_line_number, int):\n # indicates line was inserted\n rows_data.append(DiffRowData(DiffRowType.ADDED, added_line_number, line))\n if isinstance(deleted_line_number, int):\n # indicates line was removed\n rows_data.append(DiffRowData(DiffRowType.DELETED, deleted_line_number, line))\n return rows_data\n\n @staticmethod\n def wrong_change(change: DiffDict) -> bool:\n \"\"\"Returns True if the change is wrong\"\"\"\n for i in [\"line\", \"new\", \"old\"]:\n if i not in change:\n logger.warning(\"Skipping wrong change %s\", change)\n return True\n return False\n\n @staticmethod\n def preprocess_file_diff(changes: List[DiffDict]) -> List[DiffRowData]:\n \"\"\"Generate changed file rows from diff data with changed lines (e.g. marked + or - in diff).\n\n Args:\n changes: git diff by file rows data\n\n Return:\n diff rows data with as list of row change type, line number, row content\n\n \"\"\"\n if not changes:\n return []\n\n rows_data = []\n # process diff to restore lines and their positions\n for change in changes:\n if DiffContentProvider.wrong_change(change):\n continue\n if text := change[\"line\"]:\n if isinstance(text, str):\n diff_rows = DiffContentProvider.preprocess_diff_rows(change.get(\"new\"), change.get(\"old\"), text)\n rows_data.extend(diff_rows)\n elif isinstance(text, (bytes, bytearray)):\n logger.warning(\"The feature is available with the deep scan option\")\n else:\n logger.warning(\"Unknown type of line %s\", type(text))\n else:\n logger.debug(\"Change has no valuable text %s\", change)\n\n return rows_data\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Preprocess file diff data to scan.\n\n Args:\n min_len: minimal line length to scan\n\n Return:\n list of analysis targets of every row of file diff corresponding to change type \"self.change_type\"\n\n \"\"\"\n lines_data = DiffContentProvider.preprocess_file_diff(self.__diff)\n change_numbs, all_lines = self.parse_lines_data(self.__change_type, lines_data)\n return self.lines_to_targets(min_len, all_lines, change_numbs)\n" }, { "path": "credsweeper/file_handler/file_path_extractor.py", "content": "import io\nimport logging\nimport os\nfrom pathlib import Path\nfrom typing import List, Dict, Union, Tuple\n\nfrom git import InvalidGitRepositoryError, NoSuchPathError, Repo\n\nfrom credsweeper.common.constants import MIN_DATA_LEN\nfrom credsweeper.config.config import Config\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass FilePathExtractor:\n \"\"\"Util class to browse files in directories\"\"\"\n\n FIND_BY_EXT_RULE = \"Suspicious File Extension\"\n located_repos: Dict[Path, Repo] = {}\n\n @staticmethod\n def apply_gitignore(detected_files: List[str]) -> List[str]:\n \"\"\"Apply gitignore rules for each file.\n\n Args:\n detected_files: list of files to be checked\n\n Return:\n List of files with all files ignored by git removed\n\n \"\"\"\n filtered_files = [file_path for file_path in detected_files if FilePathExtractor.is_valid_path(file_path)]\n\n return filtered_files\n\n @staticmethod\n def get_file_paths(config: Config, path: Union[str, Path]) -> List[str]:\n \"\"\"Get all files in the directory. Automatically exclude files non-code or data files (such as .jpg).\n\n Args:\n config: credsweeper configuration\n path: path to the file or directory to be scanned\n\n Return:\n List all non-excluded files in the directory\n\n \"\"\"\n path = os.path.expanduser(path) # Replace ~ character with a full path to the home directory\n if not os.path.exists(path):\n logger.warning(\"Path '%s' does not exist\", path)\n file_paths = []\n if os.path.isfile(path):\n # suppose, the file is located outside and should be scanned\n if not FilePathExtractor.check_exclude_file(config, path):\n file_paths.append(path)\n elif os.path.isdir(path):\n for dirpath, _, filenames in os.walk(path):\n for filename in filenames:\n file_path = os.path.join(f\"{dirpath}\", f\"{filename}\")\n if FilePathExtractor.check_exclude_file(config, file_path) or os.path.islink(file_path):\n continue\n if os.path.isfile(file_path) and not FilePathExtractor.check_file_size(config, file_path):\n file_paths.append(file_path)\n else:\n pass # symbolic links and so on\n return file_paths\n\n @classmethod\n def is_valid_path(cls, path: str) -> bool:\n \"\"\"Locate nearest .git directory to the path and check if path is ignored.\n\n Args:\n path: path to the file or directory to check\n\n Return:\n False if file is ignored by git. True otherwise\n\n \"\"\"\n parent_directory = Path(path).parent\n\n # Iterate over file path to find nearest \".git\" directory\n while True:\n try:\n if parent_directory in cls.located_repos:\n repo = cls.located_repos[parent_directory]\n else:\n # The directory must have \".git\" in it. If not it occurs error.\n repo = Repo(parent_directory)\n\n # Cache already located repositories, so we would not need to load it for each new file\n cls.located_repos[parent_directory] = repo\n\n # Return True if there is no ignored file in 'path' and False if any.\n return len(repo.ignored(path)) == 0\n\n except (InvalidGitRepositoryError, NoSuchPathError):\n new_parent = parent_directory.parent\n # If we encountered root and cannot move further: no .git directory located in the entire path\n if new_parent == parent_directory:\n return True\n parent_directory = new_parent\n\n @staticmethod\n def is_find_by_ext_file(config: Config, extension: str) -> bool:\n \"\"\"\n Checks whether file has suspicious extension\n\n Args:\n config: Config\n extension: str - may be only file name with extension\n\n Return:\n True when the feature is configured and the file extension matches\n \"\"\"\n return config.find_by_ext and extension in config.find_by_ext_list\n\n @staticmethod\n def check_exclude_file(config: Config, path: str) -> bool:\n \"\"\"\n Checks whether file should be excluded\n\n Args:\n config: Config\n path: str - full path preferred\n\n Return:\n True when the file full path should be excluded according config\n \"\"\"\n if config.pedantic:\n return False\n path = path.replace('\\\\', '/')\n lower_path = path.lower()\n if config.not_allowed_path_pattern.match(lower_path):\n return True\n for exclude_pattern in config.exclude_patterns:\n if exclude_pattern.match(lower_path):\n return True\n for exclude_path in config.exclude_paths:\n # must be case-sensitive\n if exclude_path in path:\n return True\n file_extension = Util.get_extension(lower_path, lower=False)\n if file_extension in config.exclude_extensions:\n return True\n if not config.depth and file_extension in config.exclude_containers:\n return True\n # --depth or --doc enables scan for all documents extensions\n if not (config.depth or config.doc) and file_extension in config.exclude_documents:\n return True\n return False\n\n @staticmethod\n def check_file_size(config: Config, reference: Union[str, Path, io.BytesIO, Tuple[Union[str, Path],\n io.BytesIO]]) -> bool:\n \"\"\"\n Checks whether the file is over the size limit from configuration or less MIN_DATA_LEN\n\n Args:\n config: Config\n reference: various types of a file reference\n\n Return:\n True when the file is oversize or less than MIN_DATA_LEN, or unsupported\n \"\"\"\n path = reference[1] if isinstance(reference, tuple) else reference\n if isinstance(path, (str, Path)):\n file_size = os.path.getsize(path)\n elif isinstance(path, io.BytesIO):\n current_pos = path.tell()\n path.seek(0, io.SEEK_END)\n file_size = path.tell() - current_pos\n path.seek(current_pos, io.SEEK_SET)\n else:\n logger.error(\"Unknown path type: %s\", path)\n return True\n\n if MIN_DATA_LEN > file_size:\n logger.debug(\"Size (%s) of the file '%s' is too small\", file_size, path)\n return True\n if isinstance(config.size_limit, int) and config.size_limit < file_size:\n logger.warning(\"Size (%s) of the file '%s' is over limit (%s)\", file_size, path, config.size_limit)\n return True\n\n return False\n" }, { "path": "credsweeper/file_handler/files_provider.py", "content": "import io\nimport logging\nfrom pathlib import Path\nfrom typing import List, Optional, Union, Tuple, Sequence\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.file_handler.text_content_provider import TextContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass FilesProvider(AbstractProvider):\n \"\"\"Provider of plain os files to be analysed.\"\"\"\n\n def __init__(self,\n paths: Sequence[Union[str, Path, io.BytesIO, Tuple[Union[str, Path], io.BytesIO]]],\n skip_ignored: Optional[bool] = None) -> None:\n \"\"\"Initialize Files Text Provider for files from 'paths'.\n\n Args:\n paths: list of parent paths of files to scan\n OR tuple of path (info purpose) and io.BytesIO (reads the data from current pos)\n skip_ignored: boolean variable, Checking the directory to the list\n of ignored directories from the gitignore file\n\n \"\"\"\n super().__init__(paths)\n self.skip_ignored = skip_ignored\n\n def get_scannable_files(self, config: Config) -> Sequence[ContentProvider]:\n \"\"\"Get list of full text file object for analysis of files with parent paths from \"paths\".\n\n Args:\n config: dict of credsweeper configuration\n\n Return:\n preprocessed file objects for analysis\n\n \"\"\"\n text_content_provider_list: List[ContentProvider] = []\n for path in self.paths:\n if isinstance(path, (str, Path)):\n new_files = FilePathExtractor.get_file_paths(config, path)\n if self.skip_ignored:\n new_files = FilePathExtractor.apply_gitignore(new_files)\n for _file in new_files:\n text_content_provider_list.append(TextContentProvider(_file))\n elif isinstance(path, io.BytesIO):\n text_content_provider_list.append(TextContentProvider((\":memory:\", path)))\n elif isinstance(path, tuple) and (isinstance(path[0], (str, Path))) and isinstance(path[1], io.BytesIO):\n # suppose, all the files must be scanned\n text_content_provider_list.append(TextContentProvider(path))\n else:\n logger.error(\"Unknown path type: %s\", path)\n\n return text_content_provider_list\n" }, { "path": "credsweeper/file_handler/patches_provider.py", "content": "import io\nimport logging\nfrom pathlib import Path\nfrom typing import List, Union, Tuple, Sequence\n\nfrom credsweeper.common.constants import DiffRowType\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.file_handler.diff_content_provider import DiffContentProvider\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass PatchesProvider(AbstractProvider):\n \"\"\"Provide data from a list of `.patch` files.\n \"\"\"\n\n def __init__(self, paths: Sequence[Union[str, Path, io.BytesIO, Tuple[Union[str, Path], io.BytesIO]]],\n change_type: DiffRowType) -> None:\n \"\"\"Initialize Files Patch Provider for patch files from 'paths'.\n\n Args:\n paths: file paths list to scan. All files should be in `.patch` format\n change_type: DiffRowType, type of analyses changes in patch (added or deleted)\n of ignored directories from the gitignore file\n\n \"\"\"\n super().__init__(paths)\n self.change_type = change_type\n\n def load_patch_data(self, config: Config) -> List[List[str]]:\n \"\"\"Loads data from patch\"\"\"\n raw_patches = []\n for file_path in self.paths:\n if FilePathExtractor.check_file_size(config, file_path):\n continue\n if isinstance(file_path, (str, Path)):\n raw_patches.append(Util.read_file(file_path))\n elif isinstance(file_path, io.BytesIO):\n the_patch = Util.decode_bytes(file_path.read())\n raw_patches.append(the_patch)\n elif isinstance(file_path, tuple) and 1 < len(file_path) and isinstance(file_path[1], io.BytesIO):\n the_patch = Util.decode_bytes(file_path[1].read())\n raw_patches.append(the_patch)\n else:\n logger.error(\"Unknown path type: %s\", file_path)\n\n return raw_patches\n\n def get_files_sequence(self, raw_patches: List[List[str]]) -> Sequence[ContentProvider]:\n \"\"\"Returns sequence of files\"\"\"\n files: List[ContentProvider] = []\n for raw_patch in raw_patches:\n files_data = DiffContentProvider.patch2files_diff(raw_patch, self.change_type)\n for file_path, file_diff in files_data.items():\n files.append(DiffContentProvider(file_path=file_path, change_type=self.change_type, diff=file_diff))\n return files\n\n def get_scannable_files(self, config: Config) -> Sequence[ContentProvider]:\n \"\"\"Get files to scan. Output based on the `paths` field.\n\n Args:\n config: dict of credsweeper configuration\n\n Return:\n file objects for analysing\n\n \"\"\"\n diff_data = self.load_patch_data(config)\n files = self.get_files_sequence(diff_data)\n return files\n" }, { "path": "credsweeper/file_handler/string_content_provider.py", "content": "from functools import cached_property\nfrom typing import List, Optional, Generator\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\n\n\nclass StringContentProvider(ContentProvider):\n \"\"\"Provider performs scan simple text lines\"\"\"\n\n def __init__(\n self, #\n lines: List[str], #\n line_numbers: Optional[List[int]] = None, #\n file_path: Optional[str] = None, #\n file_type: Optional[str] = None, #\n info: Optional[str] = None) -> None:\n \"\"\"\n Parameters:\n lines: text lines to be processed\n line_numbers: matched line numbers for lines if the order is not natural.\n Otherwise, it will be filled with natural order from 1.\n\n \"\"\"\n super().__init__(file_path=file_path, file_type=file_type, info=info)\n self.__lines = lines\n # fill line numbers only when amounts are equal\n if line_numbers is None or len(lines) != len(line_numbers):\n self.__line_numbers = None\n else:\n self.__line_numbers = line_numbers\n\n @cached_property\n def data(self) -> bytes:\n \"\"\"data getter for StringContentProvider\"\"\"\n raise NotImplementedError(__name__)\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__lines = []\n if \"lines\" in self.__dict__:\n delattr(self, \"lines\")\n self.__line_numbers = []\n if \"line_numbers\" in self.__dict__:\n delattr(self, \"line_numbers\")\n\n @cached_property\n def lines(self) -> List[str]:\n \"\"\"line_numbers RO getter for StringContentProvider\"\"\"\n return self.__lines\n\n @cached_property\n def line_numbers(self) -> List[int]:\n \"\"\"line_numbers RO getter for StringContentProvider\"\"\"\n if self.__line_numbers is None or len(self.__lines) != len(self.__line_numbers):\n self.__line_numbers = list(range(1, 1 + len(self.__lines))) if self.__lines else []\n return self.__line_numbers\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Return lines to scan.\n\n Args:\n min_len: minimal line length to scan\n\n Return:\n list of analysis targets based on every row in file\n\n \"\"\"\n return self.lines_to_targets(min_len, self.lines, self.line_numbers)\n" }, { "path": "credsweeper/file_handler/struct_content_provider.py", "content": "import logging\nfrom functools import cached_property\nfrom typing import Optional, Any, Generator\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\n\nlogger = logging.getLogger(__name__)\n\n\nclass StructContentProvider(ContentProvider):\n \"\"\"Content provider to keep structured data\"\"\"\n\n def __init__(\n self, #\n struct: Any, #\n file_path: Optional[str] = None, #\n file_type: Optional[str] = None, #\n info: Optional[str] = None) -> None:\n \"\"\"\n Parameters:\n struct: Various structure (string, dictionary, list)\n\n \"\"\"\n super().__init__(file_path=file_path, file_type=file_type, info=info)\n self.__struct = struct\n\n @cached_property\n def data(self) -> bytes:\n \"\"\"data getter for StructContentProvider\"\"\"\n raise NotImplementedError(__name__)\n\n @cached_property\n def struct(self) -> Any:\n \"\"\"struct getter for StructContentProvider\"\"\"\n return self.__struct\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__struct = None\n if \"struct\" in self.__dict__:\n delattr(self, \"struct\")\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Return nothing. The class provides only data storage.\n\n Args:\n min_len: minimal line length to scan\n\n Raise:\n NotImplementedError\n\n \"\"\"\n raise NotImplementedError()\n" }, { "path": "credsweeper/file_handler/text_content_provider.py", "content": "import io\nimport logging\nfrom functools import cached_property\nfrom pathlib import Path\nfrom typing import List, Optional, Union, Tuple, Generator\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass TextContentProvider(ContentProvider):\n \"\"\"Provide access to analysis targets for full-text file scanning.\n\n Parameters:\n file_path: string, path to file\n\n \"\"\"\n\n def __init__(self,\n file_path: Union[str, Path, Tuple[Union[str, Path], io.BytesIO]],\n file_type: Optional[str] = None,\n info: Optional[str] = None) -> None:\n _path = str(file_path[0]) if isinstance(file_path, tuple) else str(file_path)\n self.__io = file_path[1] if isinstance(file_path, tuple) else None\n self.__data: Optional[bytes] = None\n self.__lines: Optional[List[str]] = None\n super().__init__(file_path=_path, file_type=file_type, info=info)\n\n @cached_property\n def data(self) -> Optional[bytes]:\n \"\"\"data RO getter for TextContentProvider\"\"\"\n if self.__data is None:\n if isinstance(self.__io, io.BytesIO) and self.__io:\n self.__data = self.__io.read()\n else:\n self.__data = Util.read_data(self.file_path)\n return self.__data\n\n def free(self) -> None:\n \"\"\"free data after scan to reduce memory usage\"\"\"\n self.__data = None\n if \"data\" in self.__dict__:\n delattr(self, \"data\")\n self.__lines = None\n if \"lines\" in self.__dict__:\n delattr(self, \"lines\")\n if isinstance(self.__io, io.BytesIO) and self.__io and not self.__io.closed:\n self.__io.close()\n\n @cached_property\n def lines(self) -> Optional[List[str]]:\n \"\"\"lines getter for TextContentProvider\"\"\"\n if self.__lines is None:\n text = Util.decode_text(self.data)\n if isinstance(text, str):\n self.__lines = Util.split_text(text)\n elif isinstance(self.__data, bytes):\n logger.warning(\"Binary file detected %s %s %s\", self.file_path, self.info,\n repr(self.__data[:32]) if isinstance(self.__data, bytes) else \"NONE\")\n self.__lines = []\n return self.__lines if self.__lines is not None else []\n\n def yield_analysis_target(self, min_len: int) -> Generator[AnalysisTarget, None, None]:\n \"\"\"Load and preprocess file content to scan.\n\n Args:\n min_len: minimal line length to scan\n\n Return:\n list of analysis targets based on every row in file\n\n \"\"\"\n lines: Optional[List[str]] = None\n line_nums: Optional[List[int]] = None\n\n if Util.get_extension(self.file_path) == \".xml\":\n try:\n # append line ending for correct xml line numeration\n xml_lines = [f\"{line}\\n\" for line in self.lines]\n lines, line_nums = Util.get_xml_from_lines(xml_lines)\n except Exception as exc:\n logger.warning(\"Cannot parse to xml %s\", exc)\n\n if lines is None:\n lines = self.lines\n\n return self.lines_to_targets(min_len, lines, line_nums)\n" }, { "path": "credsweeper/filters/__init__.py", "content": "from credsweeper.filters.line_git_binary_check import LineGitBinaryCheck\nfrom credsweeper.filters.line_specific_key_check import LineSpecificKeyCheck\nfrom credsweeper.filters.line_uue_part_check import LineUUEPartCheck\nfrom credsweeper.filters.value_allowlist_check import ValueAllowlistCheck\nfrom credsweeper.filters.value_array_dictionary_check import ValueArrayDictionaryCheck\nfrom credsweeper.filters.value_atlassian_token_check import ValueAtlassianTokenCheck\nfrom credsweeper.filters.value_azure_token_check import ValueAzureTokenCheck\nfrom credsweeper.filters.value_base32_data_check import ValueBase32DataCheck\nfrom credsweeper.filters.value_base64_data_check import ValueBase64DataCheck\nfrom credsweeper.filters.value_base64_encoded_pem_check import ValueBase64EncodedPem\nfrom credsweeper.filters.value_base64_key_check import ValueBase64KeyCheck\nfrom credsweeper.filters.value_base64_part_check import ValueBase64PartCheck\nfrom credsweeper.filters.value_basic_auth_check import ValueBasicAuthCheck\nfrom credsweeper.filters.value_blocklist_check import ValueBlocklistCheck\nfrom credsweeper.filters.value_camel_case_check import ValueCamelCaseCheck\nfrom credsweeper.filters.value_dictionary_keyword_check import ValueDictionaryKeywordCheck\nfrom credsweeper.filters.value_discord_bot_check import ValueDiscordBotCheck\nfrom credsweeper.filters.value_entropy_base32_check import ValueEntropyBase32Check\nfrom credsweeper.filters.value_entropy_base36_check import ValueEntropyBase36Check\nfrom credsweeper.filters.value_entropy_base64_check import ValueEntropyBase64Check\nfrom credsweeper.filters.value_file_path_check import ValueFilePathCheck\nfrom credsweeper.filters.value_github_check import ValueGitHubCheck\nfrom credsweeper.filters.value_grafana_check import ValueGrafanaCheck\nfrom credsweeper.filters.value_grafana_service_check import ValueGrafanaServiceCheck\nfrom credsweeper.filters.value_hex_number_check import ValueHexNumberCheck\nfrom credsweeper.filters.value_jfrog_token_check import ValueJfrogTokenCheck\nfrom credsweeper.filters.value_json_web_key_check import ValueJsonWebKeyCheck\nfrom credsweeper.filters.value_json_web_token_check import ValueJsonWebTokenCheck\nfrom credsweeper.filters.value_last_word_check import ValueLastWordCheck\nfrom credsweeper.filters.value_length_check import ValueLengthCheck\nfrom credsweeper.filters.value_method_check import ValueMethodCheck\nfrom credsweeper.filters.value_morphemes_check import ValueMorphemesCheck\nfrom credsweeper.filters.value_not_allowed_pattern_check import ValueNotAllowedPatternCheck\nfrom credsweeper.filters.value_not_part_encoded_check import ValueNotPartEncodedCheck\nfrom credsweeper.filters.value_number_check import ValueNumberCheck\nfrom credsweeper.filters.value_pattern_check import ValuePatternCheck\nfrom credsweeper.filters.value_sealed_secret_check import ValueSealedSecretCheck\nfrom credsweeper.filters.value_search_check import ValueSearchCheck\nfrom credsweeper.filters.value_similarity_check import ValueSimilarityCheck\nfrom credsweeper.filters.value_split_keyword_check import ValueSplitKeywordCheck\nfrom credsweeper.filters.value_string_type_check import ValueStringTypeCheck\nfrom credsweeper.filters.value_token_base32_check import ValueTokenBase32Check\nfrom credsweeper.filters.value_token_base36_check import ValueTokenBase36Check\nfrom credsweeper.filters.value_token_base64_check import ValueTokenBase64Check\nfrom credsweeper.filters.value_token_check import ValueTokenCheck\n" }, { "path": "credsweeper/filters/filter.py", "content": "from abc import abstractmethod, ABC\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\n\n\nclass Filter(ABC):\n \"\"\"Base class for all filters that operates on 'line_data' objects.\"\"\"\n\n @abstractmethod\n def __init__(self, config: Optional[Config], *args):\n \"\"\"Config is optional for a filter\"\"\"\n raise NotImplementedError()\n\n @abstractmethod\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n raise NotImplementedError()\n" }, { "path": "credsweeper/filters/group/__init__.py", "content": "from credsweeper.filters.group.general_keyword import GeneralKeyword\nfrom credsweeper.filters.group.general_pattern import GeneralPattern\nfrom credsweeper.filters.group.password_keyword import PasswordKeyword\nfrom credsweeper.filters.group.token_pattern import TokenPattern\nfrom credsweeper.filters.group.url_credentials_group import UrlCredentialsGroup\nfrom credsweeper.filters.group.weird_base36_token import WeirdBase36Token\nfrom credsweeper.filters.group.weird_base64_token import WeirdBase64Token\n" }, { "path": "credsweeper/filters/group/general_keyword.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueDictionaryKeywordCheck, ValueSealedSecretCheck\nfrom credsweeper.filters.group.group import Group\n\n\nclass GeneralKeyword(Group):\n \"\"\"GeneralKeyword\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.KEYWORD)\n self.filters.extend([ValueDictionaryKeywordCheck(), ValueSealedSecretCheck()])\n" }, { "path": "credsweeper/filters/group/general_pattern.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters.group.group import Group\n\n\nclass GeneralPattern(Group):\n \"\"\"GeneralPattern\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.PATTERN)\n" }, { "path": "credsweeper/filters/group/group.py", "content": "from abc import ABC\nfrom typing import List\n\nfrom credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.filters.line_specific_key_check import LineSpecificKeyCheck\nfrom credsweeper.filters.value_allowlist_check import ValueAllowlistCheck\nfrom credsweeper.filters.value_array_dictionary_check import ValueArrayDictionaryCheck\nfrom credsweeper.filters.value_blocklist_check import ValueBlocklistCheck\nfrom credsweeper.filters.value_camel_case_check import ValueCamelCaseCheck\nfrom credsweeper.filters.value_file_path_check import ValueFilePathCheck\nfrom credsweeper.filters.value_hex_number_check import ValueHexNumberCheck\nfrom credsweeper.filters.value_last_word_check import ValueLastWordCheck\nfrom credsweeper.filters.value_method_check import ValueMethodCheck\nfrom credsweeper.filters.value_not_allowed_pattern_check import ValueNotAllowedPatternCheck\nfrom credsweeper.filters.value_pattern_check import ValuePatternCheck\nfrom credsweeper.filters.value_similarity_check import ValueSimilarityCheck\nfrom credsweeper.filters.value_string_type_check import ValueStringTypeCheck\nfrom credsweeper.filters.value_token_check import ValueTokenCheck\n\n\nclass Group(ABC):\n \"\"\"Abstract Group class\"\"\"\n\n def __init__(self, config: Config, rule_type: GroupType = GroupType.DEFAULT) -> None:\n \"\"\"Config is required for filter group\"\"\"\n if rule_type == GroupType.KEYWORD:\n self.__filters = [ #\n ValueAllowlistCheck(), #\n ValueArrayDictionaryCheck(), #\n ValueBlocklistCheck(), #\n ValueCamelCaseCheck(), #\n ValueFilePathCheck(), #\n ValueHexNumberCheck(), #\n ValueLastWordCheck(), #\n ValueMethodCheck(), #\n ValueSimilarityCheck(), #\n ValueStringTypeCheck(check_for_literals=config.check_for_literals), #\n ValueTokenCheck(), #\n ]\n if not config.doc:\n self.__filters.extend([ValuePatternCheck(), ValueNotAllowedPatternCheck()])\n elif rule_type == GroupType.PATTERN:\n self.__filters = [ #\n LineSpecificKeyCheck(), #\n ValuePatternCheck(), #\n ]\n else:\n # GroupType.DEFAULT\n self.__filters = []\n\n @property\n def filters(self) -> List[Filter]:\n \"\"\"property getter\"\"\"\n return self.__filters\n\n @filters.setter\n def filters(self, filters: List[Filter]) -> None:\n \"\"\"property setter\"\"\"\n self.__filters = filters\n" }, { "path": "credsweeper/filters/group/password_keyword.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueLengthCheck, LineGitBinaryCheck, ValueSealedSecretCheck\nfrom credsweeper.filters import ValueSplitKeywordCheck\nfrom credsweeper.filters.group.group import Group\nfrom credsweeper.filters.line_uue_part_check import LineUUEPartCheck\n\n\nclass PasswordKeyword(Group):\n \"\"\"PasswordKeyword\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.KEYWORD)\n self.filters.extend([\n ValueLengthCheck(max_len=config.max_password_value_length),\n ValueSplitKeywordCheck(),\n ValueSealedSecretCheck(),\n LineGitBinaryCheck(),\n LineUUEPartCheck()\n ])\n" }, { "path": "credsweeper/filters/group/token_pattern.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueMorphemesCheck, ValueCamelCaseCheck, ValueNumberCheck, ValuePatternCheck\nfrom credsweeper.filters.group.group import Group\n\n\nclass TokenPattern(Group):\n \"\"\"Token Pattern\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.DEFAULT)\n self.filters = [\n ValueMorphemesCheck(),\n ValueNumberCheck(),\n ValueCamelCaseCheck(),\n ValuePatternCheck(),\n ]\n" }, { "path": "credsweeper/filters/group/url_credentials_group.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import (ValueAllowlistCheck, ValueArrayDictionaryCheck, ValueBlocklistCheck,\n ValueCamelCaseCheck, ValueLengthCheck, ValueFilePathCheck, ValueLastWordCheck,\n ValueMethodCheck, ValueNotAllowedPatternCheck, ValuePatternCheck, ValueStringTypeCheck,\n ValueTokenCheck)\nfrom credsweeper.filters.group.group import Group\n\n\nclass UrlCredentialsGroup(Group):\n \"\"\"UrlCredentialsGroup\"\"\"\n\n def __init__(self, config: Config) -> None:\n \"\"\"URL credentials group class.\n\n Similar to PasswordKeyword, but exclude all checks dependent on the variable name, as URL credentials have no\n explicitly defined variable\n \"\"\"\n super().__init__(config, GroupType.DEFAULT)\n self.filters = [\n ValueAllowlistCheck(),\n ValueArrayDictionaryCheck(),\n ValueBlocklistCheck(),\n ValueCamelCaseCheck(),\n ValueFilePathCheck(),\n ValueLastWordCheck(),\n ValueMethodCheck(),\n ValueStringTypeCheck(check_for_literals=config.check_for_literals),\n ValueNotAllowedPatternCheck(),\n ValueTokenCheck(),\n ValueLengthCheck(max_len=config.max_url_cred_value_length),\n ValuePatternCheck()\n ]\n" }, { "path": "credsweeper/filters/group/weird_base36_token.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueMorphemesCheck, ValuePatternCheck, ValueNumberCheck, ValueEntropyBase36Check, \\\n ValueTokenBase36Check\nfrom credsweeper.filters.group.group import Group\n\n\nclass WeirdBase36Token(Group):\n \"\"\"Structured Token\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.DEFAULT)\n self.filters = [\n ValueMorphemesCheck(threshold=1),\n ValuePatternCheck(),\n ValueNumberCheck(),\n ValueTokenBase36Check(),\n ValueEntropyBase36Check(),\n ]\n" }, { "path": "credsweeper/filters/group/weird_base64_token.py", "content": "from credsweeper.common.constants import GroupType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueMorphemesCheck, ValueNotPartEncodedCheck, \\\n ValueBase64DataCheck, ValueEntropyBase64Check, ValuePatternCheck, ValueNumberCheck, ValueTokenBase64Check, \\\n ValueBase64PartCheck\nfrom credsweeper.filters.group.group import Group\n\n\nclass WeirdBase64Token(Group):\n \"\"\"Structured Token\"\"\"\n\n def __init__(self, config: Config) -> None:\n super().__init__(config, GroupType.DEFAULT)\n self.filters = [\n ValueMorphemesCheck(threshold=1),\n ValueNumberCheck(),\n ValueBase64DataCheck(),\n ValueTokenBase64Check(),\n ValueEntropyBase64Check(),\n ValuePatternCheck(),\n ValueNotPartEncodedCheck(),\n ValueBase64PartCheck(),\n ]\n" }, { "path": "credsweeper/filters/line_git_binary_check.py", "content": "import base64\nimport contextlib\nimport re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass LineGitBinaryCheck(Filter):\n \"\"\"Checks that line is not a part of git binary patch\"\"\"\n base85string = re.compile(r\"^[A-Za-z][0-9A-Za-z!#$%&()*+;<=>?@^_`{|}~-]{6,65}$\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if not line_data.line:\n return True\n if 66 < target.line_strip_len:\n return False\n line = target.line_strip\n len_line = len(line)\n\n # https://github.com/git/git/blob/master/base85.c\n\n if 6 <= len_line and 0 == ((len_line - 1) % 5) and LineGitBinaryCheck.base85string.match(line):\n size = ord(line[0])\n if 65 <= size <= 90: # A-Z\n size -= 64\n elif 97 <= size <= 122: # a-z\n size -= 70\n else:\n return False\n with contextlib.suppress(Exception):\n decoded = base64.b85decode(line[1:])\n return len(decoded) == size\n\n return False\n" }, { "path": "credsweeper/filters/line_specific_key_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass LineSpecificKeyCheck(Filter):\n \"\"\"Check that values from list below is not in candidate line.\"\"\"\n\n NOT_ALLOWED = [r\"example\", r\"\\benc[\\(\\[]\", r\"\\btrue\\b\", r\"\\bfalse\\b\"]\n NOT_ALLOWED_PATTERN = re.compile(Util.get_regex_combine_or(NOT_ALLOWED), re.IGNORECASE)\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.line is None:\n return True\n if 0 <= line_data.variable_start:\n # variable may be defined too\n sub_line_start = 0 if ML_HUNK >= line_data.variable_start else line_data.variable_start - ML_HUNK\n else:\n sub_line_start = 0 if ML_HUNK >= line_data.value_start else line_data.value_start - ML_HUNK\n\n if self.NOT_ALLOWED_PATTERN.search(line_data.line, sub_line_start, line_data.value_end + ML_HUNK):\n return True\n\n return False\n" }, { "path": "credsweeper/filters/line_uue_part_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass LineUUEPartCheck(Filter):\n \"\"\"Checks that line is not a part of UU encoding only for maximal line\"\"\"\n uue_string = re.compile(r\"^M[!-`]{60}$\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if not line_data.line:\n return True\n if 61 != target.line_len:\n return False\n line = target.line\n if LineUUEPartCheck.uue_string.match(line):\n # to be sure - check two lines: before and/or after\n if 0 < line_data.line_pos:\n previous_line = target.lines[line_data.line_pos - 1]\n if LineUUEPartCheck.uue_string.match(previous_line):\n return True\n\n if len(target.lines) > 1 + line_data.line_pos:\n next_line = target.lines[line_data.line_pos + 1]\n if LineUUEPartCheck.uue_string.match(next_line):\n return True\n\n return False\n" }, { "path": "credsweeper/filters/value_allowlist_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueAllowlistCheck(Filter):\n \"\"\"Check that the patterns do not MATCH the candidate value.\"\"\"\n\n ALLOWED = [\n r\"ENC\\(.*\\)\", #\n r\"ENC\\[.*\\]\", #\n r\"\\$\\{(\\*|[0-9]+|[a-z_].*)\\}\", #\n r\"\\$[0-9]+(\\s|$)\", #\n r\"\\$\\$[a-z_]+(\\^%[0-9a-z_]+)?\", #\n r\"#\\{.+\\}\", # Ruby: String Interpolation\n r\"\\{\\{.+\\}\\}\", #\n r\".*@@@hl@@@(암호|비번|PW|PASS)@@@endhl@@@\", #\n ]\n\n ALLOWED_PATTERN = re.compile(Util.get_regex_combine_or(ALLOWED), flags=re.IGNORECASE)\n\n ALLOWED_QUOTED = [\n r\"\\$[a-z_][0-9a-z_]+((::|->|\\.)[a-z_]|\\[|$)\", #\n r\"\\$\\([^)]+\\)\", #\n r\".*\\*\\*\\*\", #\n ]\n\n ALLOWED_QUOTED_PATTERN = re.compile(Util.get_regex_combine_or(ALLOWED_QUOTED), flags=re.IGNORECASE)\n\n ALLOWED_UNQUOTED = [\n r\"[~a-z0-9_]+((\\.|->)[a-z0-9_]+)+\\(.*$\", #\n r\"\\$[a-z_][0-9a-z_]+((::|->|\\.)[a-z_]|\\[|$)\", #\n r\"\\$\\([.0-9a-z_-]+\", #\n r\".*\\*\\*\\*\\*\\*\", #\n ]\n\n ALLOWED_UNQUOTED_PATTERN = re.compile(Util.get_regex_combine_or(ALLOWED_UNQUOTED), flags=re.IGNORECASE)\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.is_well_quoted_value:\n if self.ALLOWED_PATTERN.match(line_data.value) or self.ALLOWED_QUOTED_PATTERN.match(line_data.value):\n return True\n else:\n value = line_data.wrap + line_data.value if line_data.wrap else line_data.value\n if self.ALLOWED_PATTERN.match(value) or self.ALLOWED_UNQUOTED_PATTERN.match(value):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_array_dictionary_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueArrayDictionaryCheck(Filter):\n \"\"\"Match call to dictionary or array element.\n\n This filter checks only calls, not declarations:\n `token = values[i]` would be filtered\n `token = {'root'}` would be kept\n \"\"\"\n\n PATTERN = re.compile(r\"\\[['\\\"]?[^,]+['\\\"]?]\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.is_well_quoted_value:\n return False\n # not well quoted value\n if line_data.wrap and \"byte\" in line_data.wrap.lower():\n return False\n if self.PATTERN.search(line_data.value):\n return True\n if line_data.wrap and (line_data.wrap.endswith('[') or line_data.wrap.endswith('(')):\n return True\n\n return False\n" }, { "path": "credsweeper/filters/value_atlassian_token_check.py", "content": "import binascii\nimport contextlib\nfrom typing import Optional\n\nfrom credsweeper.common.constants import LATIN_1, ASCII\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueAtlassianTokenCheck(Filter):\n \"\"\"Check that candidate have a known structure\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n with contextlib.suppress(Exception):\n # atlassian integer:bytes from base64\n if value.startswith(\"BBDC-\"):\n # Bitbucket HTTP Access Token\n return ValueAtlassianTokenCheck.check_atlassian_struct(value[5:])\n if value.startswith(\"AT\"):\n # Bitbucket App password\n while \"\\\\=\" in value or \"%3d\" in value or \"%3D\" in value:\n # = sign may be escaped in URL https://www.rfc-editor.org/rfc/rfc3986\n value = value.replace('\\\\', '')\n value = value.replace('%3d', '=')\n value = value.replace('%3D', '=')\n return ValueAtlassianTokenCheck.check_crc32_struct(value)\n # Jira / Confluence PAT token\n return ValueAtlassianTokenCheck.check_atlassian_struct(value)\n return True\n\n @staticmethod\n def check_crc32_struct(value: str) -> bool:\n \"\"\"Returns False if value is valid for bitbucket app password structure 'payload:crc32'\"\"\"\n crc32 = int(value[-8:], 16)\n data = value[:-8].encode(ASCII)\n data_crc32 = binascii.crc32(data)\n if crc32 == data_crc32:\n return False\n return True\n\n @staticmethod\n def check_atlassian_struct(value: str) -> bool:\n \"\"\"Returns False if value is valid for atlassian structure 'integer:bytes'\"\"\"\n decoded = Util.decode_base64(value, padding_safe=True, urlsafe_detect=True)\n delimiter_pos = decoded.find(b':')\n # there is limit for big integer value: math.log10(1<<64) = 19.265919722494797\n if 0 < delimiter_pos <= 20:\n val = decoded[:delimiter_pos].decode(LATIN_1)\n # at least 4 digits in the token\n if 1000 <= int(val):\n # test for ascii and Shannon entropy - there should be random data\n data = decoded[delimiter_pos + 1:]\n return Util.is_ascii_entropy_validate(data)\n return True\n" }, { "path": "credsweeper/filters/value_azure_token_check.py", "content": "import contextlib\nimport json\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.filters.value_entropy_base64_check import ValueEntropyBase64Check\nfrom credsweeper.utils.util import Util\n\n\nclass ValueAzureTokenCheck(Filter):\n \"\"\"\n Azure tokens contains header, payload and signature\n https://learn.microsoft.com/en-us/azure/active-directory-b2c/access-tokens\n \"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n parts = line_data.value.split('.')\n if 3 != len(parts):\n return True\n hdr = Util.decode_base64(parts[0], padding_safe=True, urlsafe_detect=True)\n header = json.loads(hdr)\n if not (\"alg\" in header and \"typ\" in header and \"kid\" in header):\n # must be all parts in header\n return True\n pld = Util.decode_base64(parts[1], padding_safe=True, urlsafe_detect=True)\n payload = json.loads(pld)\n if not (\"iss\" in payload and \"exp\" in payload and \"iat\" in payload):\n # must be all parts in payload\n return True\n min_entropy = ValueEntropyBase64Check.get_min_data_entropy(len(parts[2]))\n entropy = Util.get_shannon_entropy(parts[2])\n # good signature has to be like random bytes\n return entropy < min_entropy\n\n return True\n" }, { "path": "credsweeper/filters/value_base32_data_check.py", "content": "import base64\nimport contextlib\nimport string\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueBase32DataCheck(Filter):\n \"\"\"\n Check that candidate is NOT an ascii encoded string with entropy check\n \"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received weird base32 token which must be a random string\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n # check whether digits and upper cases present\n for string_set in [string.digits, string.ascii_uppercase]:\n for digit in string_set:\n if digit in value:\n break\n else:\n return True\n # check whether decoded bytes have enough entropy\n with contextlib.suppress(Exception):\n if pad_remain := len(value) % 8:\n value += '=' * (8 - pad_remain)\n decoded = base64.b32decode(value)\n return Util.is_ascii_entropy_validate(decoded)\n return True\n" }, { "path": "credsweeper/filters/value_base64_data_check.py", "content": "import contextlib\nimport string\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueBase64DataCheck(Filter):\n \"\"\"\n Check that candidate is NOT an ascii encoded string with entropy check\n \"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received weird base64 token which must be a random string\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n # check whether digits, lower and upper cases present\n for string_set in [string.digits, string.ascii_lowercase, string.ascii_uppercase]:\n for digit in string_set:\n if digit in value:\n break\n else:\n return True\n # check whether decoded bytes have enough entropy\n with contextlib.suppress(Exception):\n decoded = Util.decode_base64(value, padding_safe=True, urlsafe_detect=True)\n return Util.is_ascii_entropy_validate(decoded)\n return True\n" }, { "path": "credsweeper/filters/value_base64_encoded_pem_check.py", "content": "import logging\nfrom typing import Optional\n\nfrom credsweeper.common.constants import ASCII, PEM_BEGIN_PATTERN, MAX_LINE_LENGTH, PEM_END_PATTERN\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.pem_key_detector import PemKeyDetector\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass ValueBase64EncodedPem(Filter):\n \"\"\"Check that candidate contains base64 encoded pem private key\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n self.config = config\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n\n try:\n text = Util.decode_base64(line_data.value, padding_safe=True, urlsafe_detect=True).decode(ASCII)\n pem_text = ''\n pem_end_found = False\n for line in text.splitlines():\n if pem_text:\n pem_text += f\"\\n{line}\"\n if PEM_END_PATTERN in line:\n pem_end_found = True\n else:\n if PEM_BEGIN_PATTERN in line:\n if PemKeyDetector.RE_PEM_BEGIN.search(line, 0, MAX_LINE_LENGTH):\n pem_text = line\n if PEM_END_PATTERN in line:\n pem_end_found = True\n if pem_end_found:\n new_target = AnalysisTarget(0, [pem_text], [1], target.descriptor)\n first_line = LineData(self.config, pem_text, 0, 1, target.file_path, target.file_type, target.info,\n PemKeyDetector.RE_PEM_BEGIN)\n if PemKeyDetector(self.config).detect_pem_key(first_line, new_target):\n # obtained candidates are not used because not match text\n return False\n # drop the candidate and continue search\n pem_text = ''\n pem_end_found = False\n except Exception as exc:\n logger.warning(exc)\n return True\n" }, { "path": "credsweeper/filters/value_base64_key_check.py", "content": "import contextlib\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueBase64KeyCheck(Filter):\n \"\"\"Check that candidate contains base64 encoded private key\"\"\"\n\n EXTRA_TRANS_TABLE = str.maketrans('', '', \"\\\",'\\\\\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n self.config = config\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n\n with contextlib.suppress(Exception):\n # remove backslash escaping sequences\n text = Util.PEM_CLEANING_PATTERN.sub(r'', line_data.value)\n # remove whitespaces\n text = text.translate(Util.WHITESPACE_TRANS_TABLE)\n # clean sequence concatenation case:\n text = text.replace(\"'+'\", '')\n text = text.replace('\"+\"', '')\n # possibly url based escaping:\n text = text.replace('%2B', '+')\n text = text.replace('%2F', '/')\n text = text.replace('%3D', '=')\n # clean any other chars which should not appear\n text = text.translate(ValueBase64KeyCheck.EXTRA_TRANS_TABLE)\n # only PEM standard encoding supported in regex pattern to cut off ending of the key\n key = Util.decode_base64(text, padding_safe=True, urlsafe_detect=False)\n private_key = Util.load_pk(key, password=None)\n if Util.check_pk(private_key):\n return False\n return True\n" }, { "path": "credsweeper/filters/value_base64_part_check.py", "content": "import contextlib\nimport re\nimport statistics\nfrom itertools import takewhile\nfrom typing import Optional\n\nfrom credsweeper.common.constants import Chars\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.filters.value_entropy_base64_check import ValueEntropyBase64Check\nfrom credsweeper.utils.util import Util\n\n\nclass ValueBase64PartCheck(Filter):\n \"\"\"\n Check that candidate is NOT a part of base64 long line\n \"\"\"\n\n base64_pattern = re.compile(r\"^(\\\\{1,8}[0abfnrtv]|[0-9A-Za-z+/=]){1,4000}$\")\n base64_char_set = set(Chars.BASE64STDPAD_CHARS.value + '\\\\')\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received weird base64 token which must be a random string\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n\n with contextlib.suppress(Exception):\n line = line_data.line\n len_line = len(line)\n value = line_data.value\n len_value = len(value)\n if 0 == line_data.value_start and len_line >= 2 * len_value \\\n or 0 < line_data.value_start and line[line_data.value_start - 1] in ('/', '+', '\\\\', '%') \\\n or 0 < line_data.value_end < len_line and line[line_data.value_end] in ('/', '+', '\\\\', '%'):\n\n if '-' in value or '_' in value:\n # the value contains url-safe chars, so '/' or '+' is a delimiter\n return False\n\n left_start = line_data.value_start - len_value\n if 0 > left_start:\n left_start = 0\n right_end = line_data.value_end + len_value\n if len_line < right_end:\n right_end = len_line\n\n hunk_size = right_end - left_start\n\n if hunk_size == 3 * len_value:\n # simple analysis for maximal data size\n if self.base64_pattern.match(line[left_start:right_end]):\n # obvious case: all characters are base64 standard\n return True\n elif right_end - left_start >= 2 * len_value:\n # simple analysis for data too large to yield sensible insights\n part_set = set(line[left_start:right_end])\n if not part_set.difference(ValueBase64PartCheck.base64_char_set):\n # obvious case: all characters are base64 standard\n return True\n\n left_part = ''.join(\n takewhile(lambda x: x in ValueBase64PartCheck.base64_char_set,\n reversed(line[left_start:line_data.value_start])))\n\n right_part = ''.join(\n takewhile(lambda x: x in ValueBase64PartCheck.base64_char_set, line[line_data.value_end:right_end]))\n\n min_entropy_value = ValueEntropyBase64Check.get_min_data_entropy(len_value)\n\n left_entropy = Util.get_shannon_entropy(left_part)\n value_entropy = Util.get_shannon_entropy(value)\n right_entropy = Util.get_shannon_entropy(right_part)\n common = left_part + value + right_part\n common_entropy = Util.get_shannon_entropy(common)\n min_entropy_common = ValueEntropyBase64Check.get_min_data_entropy(len(common))\n if min_entropy_common < common_entropy:\n return True\n\n if left_entropy and right_entropy:\n data = [left_entropy, value_entropy, right_entropy, min_entropy_value, common_entropy]\n elif left_entropy and not right_entropy:\n data = [left_entropy, value_entropy, min_entropy_value, min_entropy_value, common_entropy]\n elif not left_entropy and right_entropy:\n data = [value_entropy, right_entropy, min_entropy_value, min_entropy_value, common_entropy]\n else:\n return False\n\n avg = statistics.mean(data)\n stdev = statistics.stdev(data, avg)\n avg_min = avg - 1.1 * stdev\n if (0. == left_entropy or avg_min < left_entropy or left_entropy < value_entropy < right_entropy) \\\n and (\n 0. == right_entropy or avg_min < right_entropy or right_entropy < value_entropy < left_entropy):\n # high entropy of bound parts looks like a part of base64 long line\n return True\n return False\n\n return False\n" }, { "path": "credsweeper/filters/value_basic_auth_check.py", "content": "import contextlib\nfrom typing import Optional\n\nfrom credsweeper.common.constants import DEFAULT_PATTERN_LEN, UTF_8\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueBasicAuthCheck(Filter):\n \"\"\"Check that candidate have a known structure\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n with contextlib.suppress(Exception):\n # Basic encoding -> login:password\n decoded = Util.decode_base64(value, padding_safe=True, urlsafe_detect=True)\n delimiter_pos = decoded.find(b':')\n # check whether the delimiter exists and all chars are decoded\n if 0 < delimiter_pos < len(decoded) - DEFAULT_PATTERN_LEN and decoded.decode(UTF_8):\n return False\n return True\n" }, { "path": "credsweeper/filters/value_blocklist_check.py", "content": "from typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueBlocklistCheck(Filter):\n \"\"\"Check that words from block list is lest that 70% of candidate value length.\"\"\"\n\n NOT_ALLOWED = [\n \"true\",\n \"false\",\n \"null\",\n \"none\",\n \"bearer\",\n \"string\",\n \"value\",\n \"undefined\",\n \"uuid\",\n ]\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n\n value = line_data.value.lower()\n for not_allowed in self.NOT_ALLOWED:\n if not_allowed in value and len(not_allowed) / len(value) >= 0.7:\n return True\n\n return False\n" }, { "path": "credsweeper/filters/value_camel_case_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueCamelCaseCheck(Filter):\n \"\"\"Check that candidate is not written in camel case.\"\"\"\n\n CAMEL_CASE = [\"[a-z]+([A-Z][a-z]+)+\", \"[A-Z][a-z]+([A-Z][a-z]+)+\"]\n CAMEL_CASE_PATTERN = re.compile(Util.get_regex_combine_or(CAMEL_CASE))\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.is_well_quoted_value:\n return False\n if self.CAMEL_CASE_PATTERN.fullmatch(line_data.value):\n return static_keyword_checklist.check_morphemes(line_data.value.lower(), 1)\n\n return False\n" }, { "path": "credsweeper/filters/value_dictionary_keyword_check.py", "content": "from typing import Optional\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueDictionaryKeywordCheck(Filter):\n \"\"\"Check that no word from dictionary present in the candidate value.\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n line_data_value_lower = line_data.value.lower()\n for keyword in static_keyword_checklist.keyword_list:\n if keyword in line_data_value_lower:\n line_data_value_lower = line_data_value_lower.replace(keyword, '\\x7F' * len(keyword))\n ratio = line_data_value_lower.count('\\x7F') / len(line_data_value_lower)\n if 0.33 < ratio:\n return True\n return False\n" }, { "path": "credsweeper/filters/value_discord_bot_check.py", "content": "import contextlib\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.filters.value_entropy_base64_check import ValueEntropyBase64Check\nfrom credsweeper.utils.util import Util\n\n\nclass ValueDiscordBotCheck(Filter):\n \"\"\"Discord bot Token\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n # . must be in value according regex\n dot_separator_index = line_data.value.index('.')\n id_part = line_data.value[:dot_separator_index]\n discord_id = int(Util.decode_base64(id_part, padding_safe=True, urlsafe_detect=True))\n entropy_part = line_data.value[dot_separator_index:]\n entropy = Util.get_shannon_entropy(entropy_part)\n min_entropy = ValueEntropyBase64Check.get_min_data_entropy(len(entropy_part))\n if 1000 <= discord_id and min_entropy <= entropy:\n return False\n return True\n" }, { "path": "credsweeper/filters/value_entropy_base32_check.py", "content": "import math\nfrom functools import cache\n\nfrom credsweeper.filters.value_entropy_base_check import ValueEntropyBaseCheck\n\n\nclass ValueEntropyBase32Check(ValueEntropyBaseCheck):\n \"\"\"Base32 entropy check\"\"\"\n\n @staticmethod\n @cache\n def get_min_data_entropy(x: int) -> float:\n \"\"\"Returns average entropy for size of random data. Precalculated data is applied for speedup\"\"\"\n if 8 <= x < 17:\n y = 0.80569236 * math.log2(x) + 0.13439734\n elif 17 <= x < 33:\n y = 0.66350481 * math.log2(x) + 0.71143862\n elif 33 <= x:\n y = 4.04\n else:\n y = 0\n return y\n" }, { "path": "credsweeper/filters/value_entropy_base36_check.py", "content": "import math\nfrom functools import cache\n\nfrom credsweeper.filters.value_entropy_base_check import ValueEntropyBaseCheck\n\n\nclass ValueEntropyBase36Check(ValueEntropyBaseCheck):\n \"\"\"Base36 entropy check\"\"\"\n\n @staticmethod\n @cache\n def get_min_data_entropy(x: int) -> float:\n \"\"\"Returns minimal entropy for size of random data. Precalculated data is applied for speedup\"\"\"\n if 15 == x:\n # workaround for Dropbox App secret\n y = 3.374\n elif 10 <= x < 26:\n y = 0.731566857 * math.log2(x) + 0.474132\n elif 26 <= x:\n y = 3.9\n else:\n y = 0\n return y\n" }, { "path": "credsweeper/filters/value_entropy_base64_check.py", "content": "import math\nfrom functools import cache\n\nfrom credsweeper.filters.value_entropy_base_check import ValueEntropyBaseCheck\n\n\nclass ValueEntropyBase64Check(ValueEntropyBaseCheck):\n \"\"\"Base64 entropy check\"\"\"\n\n @staticmethod\n @cache\n def get_min_data_entropy(x: int) -> float:\n \"\"\"Returns minimal average entropy for size of random data. Precalculated round data is applied for speedup\"\"\"\n if 12 <= x < 18:\n y = 0.915 * math.log2(x) - 0.047\n elif 18 <= x < 35:\n y = 0.767 * math.log2(x) + 0.5677\n elif 35 <= x < 65:\n y = 0.944 * math.log2(x) - 0.009 * x - 0.04\n elif 65 <= x < 256:\n y = 0.621 * math.log2(x) - 0.003 * x + 1.54\n elif 256 <= x:\n y = 6 - 64 / x\n else:\n y = 0\n return y\n" }, { "path": "credsweeper/filters/value_entropy_base_check.py", "content": "from abc import abstractmethod\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueEntropyBaseCheck(Filter):\n \"\"\"Check that candidate value has minimal Shanon Entropy for appropriated base\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n @staticmethod\n @abstractmethod\n def get_min_data_entropy(x: int) -> float:\n \"\"\"Returns minimal entropy for size of data\"\"\"\n raise NotImplementedError()\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n entropy = Util.get_shannon_entropy(line_data.value)\n min_entropy = self.get_min_data_entropy(len(line_data.value))\n if min_entropy > entropy or 0 == min_entropy:\n return True\n return False\n" }, { "path": "credsweeper/filters/value_file_path_check.py", "content": "from typing import Optional\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.common.constants import Chars\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.filters.value_entropy_base64_check import ValueEntropyBase64Check\nfrom credsweeper.utils.util import Util\n\n\nclass ValueFilePathCheck(Filter):\n \"\"\"Check that candidate value is a path or not.\n\n Check if a value contains either '/' or ':\\' separators (but not both)\n and do not have any special characters ( !$@`&*()+)\n \"\"\"\n base64stdpad_possible_set = set(Chars.BASE64STDPAD_CHARS.value)\n unusual_windows_symbols_in_path = \"\\t\\n\\r!$@`&*(){}<>+=;,~^\"\n unusual_linux_symbols_in_path = \"\\t\\n\\r!@`&*<>+=;,~^:\\\\\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n bit_length = len(value).bit_length()\n morpheme_threshold = 1 if 6 > bit_length else bit_length - 4\n contains_unix_separator = '/' in value\n if contains_unix_separator:\n if (\"://\" in value #\n or value.startswith(\"~/\") #\n or value.startswith(\"./\") #\n or \"../\" in value #\n or \"/..\" in value #\n or value.startswith(\"//\") and ':' == line_data.separator):\n # common case for url definition or aliases\n # or _keyword_://example.com where : is the separator\n return static_keyword_checklist.check_morphemes(value.lower(), morpheme_threshold)\n # base64 encoded data might look like linux path\n min_entropy = ValueEntropyBase64Check.get_min_data_entropy(len(value))\n # get minimal entropy to compare with shannon entropy of found value\n # min_entropy == 0 means that the value cannot be checked with the entropy due high variance\n for i in value:\n if i not in self.base64stdpad_possible_set:\n # value contains wrong BASE64STDPAD_CHARS symbols like -_.\n break\n else:\n # all symbols are from base64 alphabet\n entropy = Util.get_shannon_entropy(value)\n if 0 == min_entropy or min_entropy > entropy:\n contains_unix_separator = 1 < value.count('/')\n else:\n # high entropy means base64 encoded data\n contains_unix_separator = False\n\n # low shannon entropy points that the value maybe not a high randomized value in base64\n contains_windows_separator = ':\\\\' in value\n if contains_unix_separator or contains_windows_separator:\n unusual_symbols_in_path = self.unusual_linux_symbols_in_path if contains_unix_separator \\\n else self.unusual_windows_symbols_in_path\n for i in unusual_symbols_in_path:\n if i in value:\n # the symbols which not passed in a path usually\n break\n else:\n if contains_unix_separator ^ contains_windows_separator:\n return static_keyword_checklist.check_morphemes(value.lower(), morpheme_threshold)\n return False\n" }, { "path": "credsweeper/filters/value_github_check.py", "content": "import binascii\nimport contextlib\nfrom typing import Optional\n\nimport base62\n\nfrom credsweeper.common.constants import ASCII\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueGitHubCheck(Filter):\n \"\"\"NPM or GitHub Classic Token validation\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n # https://github.blog/2021-04-05-behind-githubs-new-authentication-token-formats/\n # https://github.blog/security/announcing-npms-new-access-token-format/\n with contextlib.suppress(Exception):\n if (line_data.value.startswith(\"gh\") and '_' == line_data.value[3]) or line_data.value.startswith(\"npm_\"):\n token = line_data.value[4:-6]\n data = token.encode(ASCII, errors=\"strict\")\n crc32sum = binascii.crc32(data)\n base62_crc32 = line_data.value[-6:]\n sign_b = base62.decodebytes(base62_crc32)\n crc32sign = int.from_bytes(sign_b, \"big\")\n if crc32sign == crc32sum:\n return False\n return True\n" }, { "path": "credsweeper/filters/value_grafana_check.py", "content": "import contextlib\nimport json\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueGrafanaCheck(Filter):\n \"\"\"Grafana Provisioned API Key and Access Policy Token\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n if line_data.value.startswith(\"glc_\"):\n # Grafana Access Policy Token\n decoded = Util.decode_base64(line_data.value[4:], padding_safe=True, urlsafe_detect=True)\n keys = [\"o\", \"n\", \"k\", \"m\"]\n else:\n # Grafana Provisioned API Key\n decoded = Util.decode_base64(line_data.value, padding_safe=True, urlsafe_detect=True)\n keys = [\"n\", \"k\", \"id\"]\n if payload := json.loads(decoded):\n for key in keys:\n if key not in payload:\n return True\n return False\n return True\n" }, { "path": "credsweeper/filters/value_grafana_service_check.py", "content": "import binascii\nimport contextlib\nimport struct\nfrom typing import Optional\n\nfrom credsweeper.common.constants import ASCII\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueGrafanaServiceCheck(Filter):\n \"\"\"Check that candidate have a known structure\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n checksum = struct.unpack(\" None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value.lower()\n if ValueHexNumberCheck.HEX_08_64_VALUE_REGEX.match(value):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_jfrog_token_check.py", "content": "import contextlib\nimport re\nfrom typing import Optional\n\nimport base58\n\nfrom credsweeper.common.constants import ASCII\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueJfrogTokenCheck(Filter):\n \"\"\"Check that candidate have a known structure JFROG token\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n # reftkn:01:0123456789:abcdefGhijklmnoPqrstuVwxyz0\n self._pattern = re.compile(r\"reftkn:\\d+:\\d+:[\\w_/+-]+\")\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value\n with contextlib.suppress(Exception):\n if value.startswith(\"cmVmdGtuO\"):\n decoded = Util.decode_base64(value, padding_safe=True, urlsafe_detect=True)\n if self._pattern.match(decoded.decode(ASCII)):\n # identity token\n return False\n if value.startswith(\"AKCp\"):\n decoded = base58.b58decode(value)\n # the check only for correct size decoding\n if 54 == len(decoded):\n # API key (deprecated) - a good integrity check solution was not found\n return False\n return True\n" }, { "path": "credsweeper/filters/value_json_web_key_check.py", "content": "import contextlib\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueJsonWebKeyCheck(Filter):\n \"\"\"\n Check that candidate is JWK which starts usually from 'e'\n and have private parts of the key\n https://datatracker.ietf.org/doc/html/rfc7517\n https://datatracker.ietf.org/doc/html/rfc7518\n \"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received key which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n if data := Util.decode_base64(line_data.value, padding_safe=True, urlsafe_detect=True):\n if b'\"kty\":' in data and (b'\"oct\"' in data and b'\"k\":' in data or\n (b'\"EC\"' in data or b'\"RSA\"' in data) and b'\"d\":' in data):\n return False\n return True\n" }, { "path": "credsweeper/filters/value_json_web_token_check.py", "content": "import contextlib\nimport json\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueJsonWebTokenCheck(Filter):\n \"\"\"\n Check that candidate is JWT which starts usually from 'eyJ'\n registered keys are checked to be in the JWT parts\n https://www.iana.org/assignments/jose/jose.xhtml\n \"\"\"\n header_keys = {\n \"kid\", \"x5u\", \"x5t\", \"x5t#S256\", \"typ\", \"cty\", \"crit\", \"alg\", \"enc\", \"zip\", \"jku\", \"jwk\", \"x5c\", \"epk\", \"apu\",\n \"apv\", \"iv\", \"tag\", \"p2s\", \"p2c\", \"iss\", \"sub\", \"aud\", \"b64\", \"ppt\", \"url\", \"nonce\", \"svt\"\n }\n payload_keys = {\n \"iss\", \"sub\", \"aud\", \"exp\", \"nbf\", \"iat\", \"jti\", \"kty\", \"use\", \"key_ops\", \"alg\", \"enc\", \"zip\", \"jku\", \"jwk\",\n \"kid\", \"x5u\", \"x5c\", \"x5t\", \"x5t#S256\", \"x\", \"y\", \"d\", \"n\", \"e\", \"p\", \"q\", \"dp\", \"dq\", \"qi\", \"oth\", \"k\", \"crv\",\n \"ext\", \"crit\", \"keys\", \"id\", \"role\", \"token\", \"secret\", \"password\", \"nonce\"\n }\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received token which might be structured.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n header_check = False\n payload_check = False\n signature_check = False\n with contextlib.suppress(Exception):\n jwt_parts = line_data.value.split('.')\n for part in jwt_parts:\n data = Util.decode_base64(part, padding_safe=True, urlsafe_detect=True)\n if part.startswith(\"eyJ\"):\n # open part - just base64 encoded\n json_keys = json.loads(data).keys()\n # header will be checked first\n if not header_check:\n header_check = bool(ValueJsonWebTokenCheck.header_keys.intersection(json_keys))\n # payload follows the header\n elif not payload_check:\n payload_check = bool(ValueJsonWebTokenCheck.payload_keys.intersection(json_keys))\n # any other payloads are allowed\n elif header_check and payload_check and not signature_check:\n # signature check or skip encrypted part\n signature_check = not Util.is_ascii_entropy_validate(data)\n else:\n break\n if header_check and payload_check and signature_check:\n return False\n return True\n" }, { "path": "credsweeper/filters/value_last_word_check.py", "content": "from typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueLastWordCheck(Filter):\n \"\"\"Check that secret is not short value that ends with `:`.\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if 16 > len(line_data.value) and not line_data.is_well_quoted_value and line_data.value.endswith(':'):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_length_check.py", "content": "from typing import Optional\n\nfrom credsweeper.common.constants import MIN_VALUE_LENGTH, MAX_LINE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueLengthCheck(Filter):\n \"\"\"Check that candidate value length is between MIN and MAX.\"\"\"\n\n def __init__(self,\n config: Optional[Config] = None,\n min_len: int = MIN_VALUE_LENGTH,\n max_len: int = MAX_LINE_LENGTH) -> None:\n self.min_len = min_len\n self.max_len = max_len\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if self.min_len <= len(line_data.value) <= self.max_len:\n return False\n return True\n" }, { "path": "credsweeper/filters/value_method_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueMethodCheck(Filter):\n \"\"\"Check if potential candidate value is a function.\n\n Check if potential candidate value is a function by looking for '(', ')' or 'function' sub-strings in it\n \"\"\"\n\n PATTERN = re.compile(r\"^[~.\\->:0-9A-Za-z_]+\\(.*\\)\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.is_well_quoted_value:\n return False\n if \"function\" in line_data.value or self.PATTERN.search(line_data.value):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_morphemes_check.py", "content": "from typing import Optional\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueMorphemesCheck(Filter):\n \"\"\"Check value for a threshold of morphemes count\"\"\"\n\n THRESHOLDS_X3 = int(MAX_LINE_LENGTH).bit_length()\n # one morpheme is very likely to be random generated even for 3 symbols\n MAX_MORPHEMES_LIMIT = max(1, THRESHOLDS_X3 - 4)\n\n def __init__(self, config: Optional[Config] = None, threshold: Optional[int] = None) -> None:\n # threshold - minimum morphemes number in a value\n if threshold is None:\n # use dynamic thresholds\n self.thresholds = [max(1, x - 4) for x in range(ValueMorphemesCheck.THRESHOLDS_X3)]\n elif isinstance(threshold, int) and 0 <= threshold:\n # constant thresholds for any pattern\n self.thresholds = [threshold] * ValueMorphemesCheck.THRESHOLDS_X3\n else:\n raise ValueError(f\"Wrong type of pattern length {type(threshold)} = {repr(threshold)}\")\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n threshold_id = len(line_data.value).bit_length()\n # use the last (max) threshold in very huge value\n threshold = self.thresholds[threshold_id] if len(self.thresholds) > threshold_id else self.thresholds[-1]\n return static_keyword_checklist.check_morphemes(line_data.value.lower(), threshold)\n" }, { "path": "credsweeper/filters/value_not_allowed_pattern_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.util import Util\n\n\nclass ValueNotAllowedPatternCheck(Filter):\n \"\"\"Check that secret doesn't open or closes brackets or a new line.\"\"\"\n\n NOT_ALLOWED = [r\"[<>\\[\\]{}]\\s+\", r\"\\\\u00(26|3c)gt;?(\\s|\\\\+[nrt])?\", r\"^\\s*\\\\\", r\"^\\s*\\\\n\\s*\"]\n NOT_ALLOWED_PATTERN = re.compile( #\n f\"{Util.get_regex_combine_or(NOT_ALLOWED)}$\", #\n flags=re.IGNORECASE)\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if not line_data.is_well_quoted_value and self.NOT_ALLOWED_PATTERN.search(line_data.value):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_not_part_encoded_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueNotPartEncodedCheck(Filter):\n \"\"\"Check that token is not a part of encoded data.\"\"\"\n\n BASE64_ENCODED_DATA_PATTERN_BEFORE = re.compile(\n r\"(^|[^A-Za-z0-9]+)(?P(([A-Za-z0-9_-]{4}){16,64})|(([A-Za-z0-9+/]{4}){16,64}))([^=A-Za-z0-9+/|_-]+|$)\")\n BASE64_ENCODED_DATA_PATTERN_AFTER = re.compile(\n r\"(^|[^A-Za-z0-9]+)(?P(([A-Za-z0-9=_-]{4}){4,64})|(([A-Za-z0-9=+/]{4}){4,64}))([^=A-Za-z0-9+/|_-]+|$)\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n @staticmethod\n def check_line_target_fit(line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Verifies whether line data fit to be a part of many lines\"\"\"\n return line_data.line_num == target.line_num \\\n and len(line_data.line) == target.line_len \\\n and line_data.line == target.line \\\n and 0 < target.line_num <= target.lines_len \\\n and line_data.line == target.lines[target.line_num - 1]\n\n @staticmethod\n def check_val(line: str, pattern: re.Pattern) -> Optional[bool]:\n \"\"\"Verifies whether the line looks like a base64 pattern\"\"\"\n if match_obj := pattern.match(line):\n val = match_obj.group(\"val\")\n # not a path-like\n if not val.startswith('/') \\\n or not static_keyword_checklist.check_morphemes(val.lower(), 2) \\\n or '=' == val[-1]:\n # padding char is a marker too\n return True\n return None\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n\n if ValueNotPartEncodedCheck.check_line_target_fit(line_data, target):\n # suppose, there is plain lines order\n if 1 < target.line_num:\n result = ValueNotPartEncodedCheck.check_val(target.lines[line_data.line_num - 2],\n ValueNotPartEncodedCheck.BASE64_ENCODED_DATA_PATTERN_BEFORE)\n if result is not None:\n return result\n if target.lines_len > target.line_num:\n result = ValueNotPartEncodedCheck.check_val(target.lines[line_data.line_num],\n ValueNotPartEncodedCheck.BASE64_ENCODED_DATA_PATTERN_AFTER)\n if result is not None:\n return result\n else:\n # otherwise - need to iterate for all lines\n for i in range(target.lines_len):\n if line_data.line == target.lines[i]:\n if 0 < i:\n result = ValueNotPartEncodedCheck.check_val(\n target.lines[i - 1], ValueNotPartEncodedCheck.BASE64_ENCODED_DATA_PATTERN_BEFORE)\n if result is not None:\n return result\n i += 1\n if target.lines_len > i:\n result = ValueNotPartEncodedCheck.check_val(\n target.lines[i], ValueNotPartEncodedCheck.BASE64_ENCODED_DATA_PATTERN_AFTER)\n if result is not None:\n return result\n break\n return False\n" }, { "path": "credsweeper/filters/value_number_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueNumberCheck(Filter):\n \"\"\"Check value if it a value in hex or decimal representation\"\"\"\n\n HEX_VALUE_REGEX = re.compile(\"^(0x)?[0-9a-f]{1,128}[ul]{0,3}$\")\n DEC_VALUE_REGEX = re.compile(\"^-?[0-9]{1,20}[ul]{0,3}$\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n value = line_data.value.lower()\n if 22 > len(value) and ValueNumberCheck.HEX_VALUE_REGEX.match(value):\n return True\n if ValueNumberCheck.DEC_VALUE_REGEX.match(value):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_pattern_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.common.constants import DEFAULT_PATTERN_LEN, MAX_LINE_LENGTH, MIN_DATA_LEN\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValuePatternCheck(Filter):\n \"\"\"Check if candidate value contain specific pattern.\n\n Similar to linguistic sequences of characters, random strings shouldn't contain math sequences of\n characters. Based on \"How Bad Can It Git? Characterizing Secret Leakage in Public GitHub Repositories\", details:\n https://www.ndss-symposium.org/ndss-paper/how-bad-can-it-git-characterizing-secret-leakage-in-public-github-repositories/\n PatternCheck checks the occurrence in \"line_data.value\" of three types of sequence:\n\n - N or more identical characters in sequence, example: \"AAAA\", \"1111\" ...\n - N or more increasing characters sequentially, example: \"abcd\", \"1234\" ...\n - N or more decreasing characters sequentially, example: \"dcba\", \"4321\" ...\n\n Default pattern LEN is 4\n \"\"\"\n\n MAX_PATTERN_LENGTH = int(MAX_LINE_LENGTH).bit_length()\n\n def __init__(self, config: Optional[Config] = None, pattern_len: Optional[int] = None):\n \"\"\"Create ValuePatternCheck with a specific pattern_len to check.\n\n Args:\n config: pattern len to use during check. DEFAULT_PATTERN_LEN by default\n pattern_len: size of constant pattern length for any value size or None for dynamic pattern size\n\n \"\"\"\n patterns_count = 1 + ValuePatternCheck.MAX_PATTERN_LENGTH\n if pattern_len is None:\n self.pattern_len = -1\n # pattern length depends on value length\n self.pattern_lengths = [max(x, DEFAULT_PATTERN_LEN) for x in range(patterns_count)]\n self.patterns = [ValuePatternCheck.get_pattern(x) for x in range(patterns_count)]\n elif isinstance(pattern_len, int) and DEFAULT_PATTERN_LEN <= pattern_len:\n self.pattern_len = pattern_len\n # constant pattern for any value length\n self.pattern_lengths = [pattern_len] * patterns_count\n self.patterns = [ValuePatternCheck.get_pattern(pattern_len)] * patterns_count\n else:\n raise ValueError(f\"Wrong type of pattern length {type(pattern_len)} = {repr(pattern_len)}\")\n\n @staticmethod\n def get_pattern(pattern_len: int) -> re.Pattern:\n \"\"\"Creates regex pattern to find N or more identical characters in sequence\"\"\"\n pattern_length = max(DEFAULT_PATTERN_LEN, pattern_len)\n if MIN_DATA_LEN <= pattern_length:\n # base64 long sequences may contain 0x00 or 0xFF inside\n pattern = fr\"([^\\sA/_])\\1{{{str(pattern_length-1)},}}\"\n else:\n # up to 256 symbols length\n pattern = fr\"(\\S)\\1{{{str(pattern_length-1)},}}\"\n return re.compile(pattern)\n\n def equal_pattern_check(self, value: str, bit_length: int) -> bool:\n \"\"\"Check if candidate value contain 4 and more same chars or numbers sequences.\n\n Args:\n value: string variable, credential candidate value\n bit_length: speedup for len(value).bit_length()\n\n Return:\n True if contain and False if not\n\n \"\"\"\n if self.patterns[bit_length].search(value):\n return True\n return False\n\n def ascending_pattern_check(self, value: str, bit_length: int) -> bool:\n \"\"\"Check if candidate value contain 4 and more ascending chars or numbers sequences.\n\n Arg:\n value: credential candidate value\n bit_length: speedup for len(value).bit_length()\n\n Return:\n True if contain and False if not\n\n \"\"\"\n count = 1\n for key in range(len(value) - 1):\n if ord(value[key + 1]) - ord(value[key]) == 1:\n count += 1\n else:\n count = 1\n continue\n if count == self.pattern_lengths[bit_length]:\n return True\n return False\n\n def descending_pattern_check(self, value: str, bit_length: int) -> bool:\n \"\"\"Check if candidate value contain 4 and more descending chars or numbers sequences.\n\n Arg:\n value: string variable, credential candidate value\n bit_length: speedup for len(value).bit_length()\n\n Return:\n boolean variable. True if contain and False if not\n\n \"\"\"\n count = 1\n for key in range(len(value) - 1):\n if ord(value[key]) - ord(value[key + 1]) == 1:\n count += 1\n else:\n count = 1\n continue\n if count == self.pattern_lengths[bit_length]:\n return True\n return False\n\n def check_val(self, value: str, bit_length: int) -> bool:\n \"\"\"Cumulative value check.\n\n Arg:\n value: string variable, credential candidate value\n bit_length: speedup for len(value).bit_length()\n\n Return:\n boolean variable. True if contain and False if not\n\n \"\"\"\n if self.equal_pattern_check(value, bit_length):\n return True\n if self.ascending_pattern_check(value, bit_length):\n return True\n if self.descending_pattern_check(value, bit_length):\n return True\n return False\n\n def duple_pattern_check(self, value: str, bit_length: int) -> bool:\n \"\"\"Check if candidate value is a duplet value with possible patterns.\n\n Arg:\n value: string variable, credential candidate value\n bit_length: speedup for len(value).bit_length()\n\n Return:\n boolean variable. True if contain and False if not\n\n \"\"\"\n even_value = value[0::2]\n if self.check_val(even_value, bit_length):\n odd_value = value[1::2]\n if self.check_val(odd_value, bit_length):\n return True\n return False\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Arg:\n line_data: LineData object, credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n boolean variable. True, if need to filter candidate and False if left\n\n \"\"\"\n value_length = len(line_data.value)\n bit_length = max(DEFAULT_PATTERN_LEN, value_length.bit_length())\n\n if ValuePatternCheck.MAX_PATTERN_LENGTH < bit_length:\n # huge values may contain anything\n return False\n\n if 0 <= value_length < self.pattern_len or value_length < self.pattern_lengths[bit_length]:\n # too short value\n return True\n\n if self.check_val(line_data.value, bit_length):\n return True\n\n if 2 * self.pattern_lengths[bit_length] <= value_length \\\n and self.duple_pattern_check(line_data.value, bit_length):\n return True\n\n return False\n" }, { "path": "credsweeper/filters/value_sealed_secret_check.py", "content": "from typing import Optional\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueSealedSecretCheck(Filter):\n \"\"\"\n Check that candidate may be a sealed secret\n https://github.com/bitnami-labs/sealed-secrets/blob/main/docs/developer/crypto.md\n \"\"\"\n MAX_SEARCH_MARGIN = 100\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received value and check context for sealed secret markers.\n Can be applied effective for plain scan when the value is full and the target has lines around.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, when need to filter candidate and False if left\n\n \"\"\"\n\n if (value := line_data.value) and (value.startswith('Ag') and 700 < len(value) and 'A' <= value[2] <= 'D'\n or value.startswith('AQ') and 350 < len(value) and 'A' <= value[2] <= 'D'):\n from_line = max(0, line_data.line_pos - ValueSealedSecretCheck.MAX_SEARCH_MARGIN)\n to_line = min(len(target.lines), line_data.line_pos + ValueSealedSecretCheck.MAX_SEARCH_MARGIN)\n sealed_secret_marker = encrypted_data_marker = bitnami_marker = False\n for line in target.lines[from_line:to_line]:\n if not sealed_secret_marker and 0 <= line.find(\"SealedSecret\", 0, MAX_LINE_LENGTH):\n sealed_secret_marker = True\n if not encrypted_data_marker and 0 <= line.find(\"encryptedData\", 0, MAX_LINE_LENGTH):\n encrypted_data_marker = True\n if not bitnami_marker and 0 <= line.find(\"bitnami\", 0, MAX_LINE_LENGTH):\n bitnami_marker = True\n if sealed_secret_marker and encrypted_data_marker and bitnami_marker:\n return True\n return False\n" }, { "path": "credsweeper/filters/value_search_check.py", "content": "from typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueSearchCheck(Filter):\n \"\"\"Check whether a candidate value contains a pattern - useful for multi rules\"\"\"\n\n def __init__(self, config: Optional[Config] = None, pattern: Optional[str] = None) -> None:\n self.pattern = pattern\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if self.pattern and line_data.value:\n if len(self.pattern) < len(line_data.value):\n if self.pattern in line_data.value:\n return True\n else:\n if line_data.value in self.pattern:\n return True\n return False\n" }, { "path": "credsweeper/filters/value_similarity_check.py", "content": "from difflib import SequenceMatcher\nfrom typing import Optional\n\nfrom credsweeper.common.constants import MIN_VALUE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueSimilarityCheck(Filter):\n \"\"\"Check if candidate value is over 75% similarity as candidate variable. Like: `secret = \"mysecret\"` (0.8571).\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.variable and line_data.value:\n variable_lower = line_data.variable.lower()\n value_lower = line_data.value.lower()\n if len(value_lower) <= len(variable_lower):\n if value_lower in variable_lower:\n return True\n elif MIN_VALUE_LENGTH <= len(variable_lower):\n # `api` and `key` may be in the value\n if variable_lower in value_lower:\n return True\n if 0.75 < SequenceMatcher(None, variable_lower, value_lower).ratio():\n return True\n return False\n" }, { "path": "credsweeper/filters/value_split_keyword_check.py", "content": "from typing import Optional\nfrom typing import Union\n\nfrom credsweeper.common import static_keyword_checklist\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueSplitKeywordCheck(Filter):\n \"\"\"Check value by splitting with standard whitespace separators and any word is not matched in checklist.\"\"\"\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n words: Union[set, list] = line_data.value.lower().split()\n keyword_set = static_keyword_checklist.keyword_set\n for word in words:\n if word in keyword_set:\n return True\n return False\n" }, { "path": "credsweeper/filters/value_string_type_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueStringTypeCheck(Filter):\n r\"\"\"Check if line_data is in source code file that require quotes for string declaration.\n\n If it is, then checks if line_data really have string literal declaration.\n Comment rows in source files (start with //, /\\*, etc) ignored.\n Multiple bytes scenario allowed [123,23,54,67,78,89] or {0xae, 0x54, 0x55, 0xff}\n\n True if:\n\n - line_data have no value\n - line_data have no path\n - line_data is in source code file (.cpp, .py, etc.) and is not comment\n and contain no quotes (so no string literal declared)\n\n False otherwise\n \"\"\"\n\n MULTIBYTE_PATTERN = re.compile(r\"((0x)?[0-9a-f]{1,16}[UL]*)(\\s*,\\s*((0x)?[0-9a-f]{1,16}[UL]*)){3}\",\n flags=re.IGNORECASE)\n\n def __init__(self, config: Optional[Config] = None, check_for_literals=True) -> None:\n self.check_for_literals = check_for_literals\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if not self.check_for_literals or line_data.url_part:\n return False\n\n if ValueStringTypeCheck.MULTIBYTE_PATTERN.search(line_data.value):\n return False\n\n if line_data.is_source_file_with_quotes() \\\n and not line_data.is_comment() \\\n and not line_data.is_well_quoted_value \\\n and not line_data.is_quoted \\\n and not '0' <= line_data.value[0] <= '9' \\\n and line_data.separator and '=' in line_data.separator:\n # heterogeneous code e.g. YAML in Python uses colon sign instead equals\n return True\n\n return False\n" }, { "path": "credsweeper/filters/value_token_base32_check.py", "content": "from typing import Tuple\n\nfrom credsweeper.filters.value_token_base_check import ValueTokenBaseCheck\n\n\nclass ValueTokenBase32Check(ValueTokenBaseCheck):\n \"\"\"Check that candidate have good randomization\"\"\"\n\n RANGE_DICT = {\n 8: ((3.480934, 0.8482364556537906), (1.9280820731422028, 0.5833143826506801)),\n 10: ((3.4801753333333334, 0.7508676237320747), (1.9558544090983234, 0.5119385414964345)),\n 15: ((3.4803549285714284, 0.603220270918794), (1.9896690734372564, 0.40640877687972476)),\n 16: ((3.4798649333333334, 0.5837818960141307), (1.9938368543943692, 0.392547066949958)),\n 20: ((3.4809878947368422, 0.518785674729997), (2.0058661928593517, 0.34692788889724946)),\n 24: ((3.480511086956522, 0.4726670109337228), (2.0131379532992537, 0.31476354168931936)),\n 25: ((3.480877375, 0.4626150412368404), (2.0147828593929953, 0.3075894753390553)),\n 32: ((3.4809023548387095, 0.4072672632996217), (2.0231609118646867, 0.2700344059876962)),\n 40: ((3.4801929743589746, 0.36361457820793436), (2.027858606807074, 0.2401498396303172)),\n 50: ((3.4798551224489795, 0.323708167297437), (2.0318808048208794, 0.2138098551294688)),\n 64: ((3.4805990476190476, 0.28572156450556774), (2.035756800745673, 0.18815721535870078)),\n }\n\n @staticmethod\n def get_stat_range(size: int) -> Tuple[Tuple[float, float], Tuple[float, float]]:\n \"\"\"Returns minimal, maximal for hop and deviation. Precalculated data is applied for speedup\"\"\"\n if result := ValueTokenBase32Check.RANGE_DICT.get(size):\n ppf = ValueTokenBaseCheck.get_ppf(size)\n return ((result[0][0] - ppf * result[0][1], result[0][0] + ppf * result[0][1]),\n (result[1][0] - ppf * result[1][1], result[1][0] + ppf * result[1][1]))\n # not calculated\n raise ValueError(f\"Not calculated for {size}\")\n" }, { "path": "credsweeper/filters/value_token_base36_check.py", "content": "from typing import Tuple\n\nfrom credsweeper.filters.value_token_base_check import ValueTokenBaseCheck\n\n\nclass ValueTokenBase36Check(ValueTokenBaseCheck):\n \"\"\"Check that candidate have good randomization\"\"\"\n\n RANGE_DICT = {\n 8: ((3.7190542428571427, 0.8995506118495411), (2.066095086865182, 0.609210293352161)),\n 10: ((3.719109611111111, 0.7956463384852813), (2.0946299036665494, 0.5322004874842623)),\n 15: ((3.719274257142857, 0.6401989313894239), (2.129437216268589, 0.42108786288993155)),\n 16: ((3.7192072666666665, 0.6188627491757901), (2.1336109506109366, 0.4064699817331141)),\n 20: ((3.719249815789474, 0.5506473627709657), (2.145293932511567, 0.3591543917048417)),\n 24: ((3.7191934304347827, 0.50051922802262), (2.152858549996053, 0.3252064160191062)),\n 25: ((3.7192351583333334, 0.4904181410613897), (2.1543202565038735, 0.31823801389315026)),\n 32: ((3.7190408419354837, 0.4315967526660196), (2.1620321219700767, 0.2788634701820312)),\n 40: ((3.7191682666666668, 0.3852248727988986), (2.16746680811131, 0.24802261318501675)),\n 50: ((3.718913744897959, 0.3436564880405547), (2.1715676118603806, 0.22070510537297627)),\n 64: ((3.7190009761904763, 0.30325954360127116), (2.1751172797904093, 0.1942582237461476)),\n }\n\n @staticmethod\n def get_stat_range(size: int) -> Tuple[Tuple[float, float], Tuple[float, float]]:\n \"\"\"Returns minimal, maximal for hop and deviation. Precalculated data is applied for speedup\"\"\"\n if result := ValueTokenBase36Check.RANGE_DICT.get(size):\n ppf = ValueTokenBaseCheck.get_ppf(size)\n return ((result[0][0] - ppf * result[0][1], result[0][0] + ppf * result[0][1]),\n (result[1][0] - ppf * result[1][1], result[1][0] + ppf * result[1][1]))\n # not calculated\n raise ValueError(f\"Not calculated for {size}\")\n" }, { "path": "credsweeper/filters/value_token_base64_check.py", "content": "from typing import Tuple\n\nfrom credsweeper.filters.value_token_base_check import ValueTokenBaseCheck\n\n\nclass ValueTokenBase64Check(ValueTokenBaseCheck):\n \"\"\"Check that candidate have good randomization\"\"\"\n\n RANGE_DICT = {\n 8: ((3.7627115714285715, 0.9413431166706269), (2.1378378843992736, 0.6394596814295781)),\n 10: ((3.7617393333333333, 0.8327986018456262), (2.168873183866972, 0.5605393324056347)),\n 15: ((3.7619624285714286, 0.6698092646328063), (2.2080058406286702, 0.4447698491992352)),\n 16: ((3.7618573333333334, 0.6471500119793832), (2.2116826642934453, 0.4288377928263507)),\n 20: ((3.7618887368421055, 0.575813792926031), (2.224384985667721, 0.37985781543221253)),\n 24: ((3.7621449565217393, 0.5243297908608613), (2.2326041329976607, 0.34397389723600613)),\n 25: ((3.762616791666667, 0.5137934920050976), (2.234571917211925, 0.3366547036535176)),\n 32: ((3.761885838709677, 0.4521158322065318), (2.2426375800006153, 0.29506039075960255)),\n 40: ((3.7622649487179487, 0.4031261511824518), (2.2485911621253574, 0.2622954601051068)),\n 50: ((3.762087693877551, 0.3597404118023357), (2.2533774423872956, 0.23384524947332655)),\n 64: ((3.7625271746031745, 0.31733579704946846), (2.257532519514275, 0.20571908142867643)),\n }\n\n @staticmethod\n def get_stat_range(size: int) -> Tuple[Tuple[float, float], Tuple[float, float]]:\n \"\"\"Returns minimal, maximal for hop and deviation. Precalculated data is applied for speedup\"\"\"\n if result := ValueTokenBase64Check.RANGE_DICT.get(size):\n ppf = ValueTokenBaseCheck.get_ppf(size)\n return ((result[0][0] - ppf * result[0][1], result[0][0] + ppf * result[0][1]),\n (result[1][0] - ppf * result[1][1], result[1][0] + ppf * result[1][1]))\n # not calculated\n raise ValueError(f\"Not calculated for {size}\")\n" }, { "path": "credsweeper/filters/value_token_base_check.py", "content": "import contextlib\nfrom abc import abstractmethod\nfrom typing import Optional\nfrom typing import Tuple\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.utils.hop_stat import HopStat\n\n\nclass ValueTokenBaseCheck(Filter):\n \"\"\"Check that candidate have good randomization\"\"\"\n\n MUL_DICT = {\n 8: 2.61619746,\n 10: 2.48685659,\n 15: 2.34025271,\n 16: 2.32370290,\n 20: 2.27614996,\n 24: 2.24609586,\n 25: 2.24023515,\n 32: 2.21025277,\n 40: 2.18961571,\n 50: 2.17355282,\n 64: 2.15981241,\n }\n\n def __init__(self, config: Optional[Config] = None) -> None:\n self.__hop_stat = HopStat()\n\n @staticmethod\n @abstractmethod\n def get_stat_range(size: int) -> Tuple[Tuple[float, float], Tuple[float, float]]:\n \"\"\"Returns minimal strength. Precalculated data is applied for speedup\"\"\"\n raise NotImplementedError\n\n @staticmethod\n def get_ppf(n: int) -> float:\n \"\"\"Code used to produce the values\"\"\"\n # from scipy.stats import t\n # print('\\n'.join(f'{n}: {t.ppf(0.9827, n-1):.8f},' for n in [8,10,15,16,20,24,25,32,40,50,64]))\n return ValueTokenBaseCheck.MUL_DICT[n]\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n with contextlib.suppress(Exception):\n hop, dev = self.__hop_stat.stat(line_data.value)\n (min_hop, max_hop), (min_dev, max_dev) = self.get_stat_range(len(line_data.value))\n if not (min_hop <= hop <= max_hop and min_dev <= dev <= max_dev):\n return True\n return False\n" }, { "path": "credsweeper/filters/value_token_check.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\n\n\nclass ValueTokenCheck(Filter):\n \"\"\"Check if first substring of token is shorter than 5.\n\n Split candidate value into substrings using ` ;`{})(<>[]` separators. Check if first substring is shorter than 5\n\n Examples:\n \"my password\"\n \"12);password\"\n\n \"\"\"\n\n SPLIT_PATTERN = re.compile(r\"(?[\\]`]\")\n\n def __init__(self, config: Optional[Config] = None) -> None:\n pass\n\n def run(self, line_data: LineData, target: AnalysisTarget) -> bool:\n \"\"\"Run filter checks on received credential candidate data 'line_data'.\n\n Args:\n line_data: credential candidate data\n target: multiline target from which line data was obtained\n\n Return:\n True, if need to filter candidate and False if left\n\n \"\"\"\n if line_data.is_well_quoted_value:\n return False\n tokens = re.split(self.SPLIT_PATTERN, line_data.value, maxsplit=1)\n # If tokens have length of 1 - pattern is not present in the value and original value returned from `.split(`\n if len(tokens) < 2:\n return False\n\n token = tokens[0]\n if len(token) < 5:\n return True\n\n return False\n" }, { "path": "credsweeper/logger/__init__.py", "content": "" }, { "path": "credsweeper/logger/logger.py", "content": "import logging\nimport logging.config\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.utils.util import Util\n\n\nclass Logger:\n \"\"\"Class that used to configure logging in CredSweeper.\"\"\"\n\n SILENCE = 60\n\n LEVELS = {\n \"DEBUG\": logging.DEBUG,\n \"INFO\": logging.INFO,\n \"WARN\": logging.WARNING,\n \"WARNING\": logging.WARNING,\n \"ERROR\": logging.ERROR,\n \"FATAL\": logging.CRITICAL,\n \"CRITICAL\": logging.CRITICAL,\n \"SILENCE\": SILENCE\n }\n\n @staticmethod\n def init_logging(log_level: str, file_path: Optional[str] = None) -> None:\n \"\"\"Init logger.\n\n Init logging with configuration from file 'credsweeper_path/secret/log.yaml'. For configure log level of\n console output used 'log_level' args\n\n Args:\n log_level: log level for console output\n file_path: path of custom log config\n\n \"\"\"\n try:\n level = Logger.LEVELS.get(log_level.upper())\n if level is None:\n raise ValueError(f\"log level given: {log_level} -- must be one of: {' | '.join(Logger.LEVELS.keys())}\")\n logging_config = Util.yaml_load(file_path) if file_path else None\n if not logging_config:\n logging_config = Util.yaml_load(APP_PATH / \"secret\" / \"log.yaml\")\n log_dir = Path(logging_config[\"handlers\"][\"logfile\"][\"filename\"]).resolve().parent\n log_dir.mkdir(exist_ok=True)\n logging_config[\"handlers\"][\"console\"][\"level\"] = level\n logging.config.dictConfig(logging_config)\n for module in logging_config[\"ignore\"]:\n logging.getLogger(module).setLevel(logging.ERROR)\n except OSError:\n logging.basicConfig(level=logging.WARNING)\n" }, { "path": "credsweeper/main.py", "content": "import binascii\nimport contextlib\nimport logging\nimport os\nimport sys\nimport time\nfrom argparse import ArgumentParser, ArgumentTypeError, Namespace, BooleanOptionalAction\nfrom pathlib import Path\nfrom typing import Any, Union, Dict, Tuple, Sequence\n\nfrom git import Repo, Commit\n\nfrom credsweeper import __version__\nfrom credsweeper.app import APP_PATH, CredSweeper\nfrom credsweeper.common.constants import ThresholdPreset, Severity, RuleType, DiffRowType, ML_HUNK\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom credsweeper.file_handler.patches_provider import PatchesProvider\nfrom credsweeper.logger.logger import Logger\nfrom credsweeper.utils.util import Util\n\nEXIT_SUCCESS = 0\nEXIT_FAILURE = 1\n\nlogger = logging.getLogger(__name__)\n\n\ndef positive_int(value: Any) -> int:\n \"\"\"Check if number of parallel processes is not a positive number.\"\"\"\n int_value = int(value)\n if int_value <= 0:\n logger.error(\"Number of parallel processes should be a positive number: %s\", value)\n raise ArgumentTypeError(f\"{value} should be greater than 0\")\n return int_value\n\n\ndef threshold_or_float_or_zero(arg: str) -> Union[int, float, ThresholdPreset]:\n \"\"\"Return ThresholdPreset or a float from the input string\n\n Args:\n arg: string that either a float or one of allowed values in ThresholdPreset\n\n Returns:\n int = 0 to disable ML validator, float if arg convertible to float, ThresholdPreset if one of the allowed values\n\n Raises:\n ArgumentTypeError: if arg cannot be interpreted as float or ThresholdPreset\n\n \"\"\"\n allowed_presents = [e.value for e in ThresholdPreset]\n if '0' == arg:\n return 0\n with contextlib.suppress(ValueError):\n return float(arg) # try convert to float\n if arg in allowed_presents:\n return ThresholdPreset[arg]\n raise ArgumentTypeError(f\"value must be a float or one of {allowed_presents}\")\n\n\ndef logger_levels(log_level: str) -> str:\n \"\"\"Logger level correctness verification and transformation\n\n Args:\n log_level: string with level\n\n Returns True if log_level UPPERCASE is one of keys\n \"\"\"\n val = log_level.upper()\n if val in Logger.LEVELS:\n return val\n raise ArgumentTypeError(f\"Log level provided: {log_level} -- must be one of: {' | '.join(Logger.LEVELS.keys())}\")\n\n\ndef severity_levels(severity_level: str) -> Severity:\n \"\"\"Severity level correctness verification and transformation\n\n Args:\n severity_level: string with level\n\n Returns Severity matched provided string or throws ArgumentTypeError exception\n \"\"\"\n\n if severity := Severity.get(severity_level):\n return severity\n raise ArgumentTypeError(\n f\"Severity level provided: {severity_level} -- must be one of: {' | '.join([i.value for i in Severity])}\")\n\n\ndef check_integrity() -> int:\n \"\"\"Calculates CRC32 of program files\n\n Returns CRC32 of files in integer\n \"\"\"\n crc32 = 0\n for root, _dirs, files in os.walk(APP_PATH):\n for file_name in files:\n if Util.get_extension(file_name) in [\".py\", \".json\", \".txt\", \".yaml\", \".onnx\"]:\n file_path = Path(root) / file_name\n if data := Util.read_data(file_path):\n crc32 ^= binascii.crc32(data)\n return crc32\n\n\ndef get_arguments() -> Namespace:\n \"\"\"All CLI arguments are defined here\"\"\"\n parser = ArgumentParser(prog=\"python -m credsweeper\")\n single_banner_argument = 2 == len(sys.argv) and \"--banner\" == sys.argv[1]\n group = parser.add_mutually_exclusive_group(required=not single_banner_argument)\n group.add_argument(\"--path\", nargs=\"+\", help=\"file or directory to scan\", dest=\"path\", metavar=\"PATH\")\n group.add_argument(\"--diff_path\", nargs=\"+\", help=\"git diff file to scan\", dest=\"diff_path\", metavar=\"PATH\")\n group.add_argument(\"--export_config\",\n nargs=\"?\",\n help=\"exporting default config to file (default: config.json)\",\n const=\"config.json\",\n dest=\"export_config\",\n metavar=\"PATH\")\n group.add_argument(\"--export_log_config\",\n nargs=\"?\",\n help=\"exporting default logger config to file (default: log.yaml)\",\n const=\"log.yaml\",\n dest=\"export_log_config\",\n metavar=\"PATH\")\n group.add_argument(\"--git\", help=\"git repo to scan\", dest=\"git\", metavar=\"PATH\")\n parser.add_argument(\"--ref\",\n help=\"scan git repo from the ref, otherwise - all branches were scanned (slow)\",\n dest=\"ref\",\n type=str)\n parser.add_argument(\"--rules\",\n help=\"path of rule config file (default: credsweeper/rules/config.yaml). \"\n f\"severity:{[i.value for i in Severity]} \"\n f\"type:{[i.value for i in RuleType]}\",\n default=None,\n dest=\"rule_path\",\n metavar=\"PATH\")\n parser.add_argument(\"--severity\",\n help=f\"set minimum level for rules to apply {[i.value for i in Severity]}\"\n f\"(default: '{Severity.INFO}', case insensitive)\",\n default=Severity.INFO,\n dest=\"severity\",\n type=severity_levels)\n parser.add_argument(\"--config\",\n help=\"use custom config (default: built-in)\",\n default=None,\n dest=\"config_path\",\n metavar=\"PATH\")\n parser.add_argument(\"--log_config\",\n help=\"use custom log config (default: built-in)\",\n default=None,\n dest=\"log_config_path\",\n metavar=\"PATH\")\n parser.add_argument(\"--denylist\",\n help=\"path to a plain text file with lines or secrets to ignore\",\n default=None,\n dest=\"denylist_path\",\n metavar=\"PATH\")\n parser.add_argument(\"--find-by-ext\",\n help=\"find files by predefined extension\",\n dest=\"find_by_ext\",\n action=\"store_true\")\n parser.add_argument(\"--pedantic\",\n help=\"process files without extension\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--depth\",\n help=\"additional recursive search in data (experimental)\",\n type=positive_int,\n dest=\"depth\",\n default=0,\n required=False,\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"--no-filters\", help=\"disable filters\", dest=\"no_filters\", action=\"store_false\")\n parser.add_argument(\"--doc\", help=\"document-specific scanning\", dest=\"doc\", action=\"store_true\")\n parser.add_argument(\"--ml_threshold\",\n help=\"setup threshold for the ml model. \"\n \"The lower the threshold - the more credentials will be reported. \"\n f\"Allowed values: float between 0 and 1, or any of {[e.value for e in ThresholdPreset]} \"\n \"(default: medium)\",\n type=threshold_or_float_or_zero,\n default=ThresholdPreset.medium,\n dest=\"ml_threshold\",\n required=False,\n metavar=\"THRESHOLD_OR_FLOAT_OR_ZERO\")\n parser.add_argument(\"--ml_batch_size\",\n \"-b\",\n help=\"batch size for model inference (default: 16)\",\n type=positive_int,\n dest=\"ml_batch_size\",\n default=16,\n required=False,\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"--ml_config\",\n help=\"use external config for ml model\",\n type=str,\n default=None,\n dest=\"ml_config\",\n required=False,\n metavar=\"PATH\")\n parser.add_argument(\"--ml_model\",\n help=\"use external ml model\",\n type=str,\n default=None,\n dest=\"ml_model\",\n required=False,\n metavar=\"PATH\")\n parser.add_argument(\"--ml_providers\",\n help=\"comma separated list of providers for onnx (CPUExecutionProvider is used by default)\",\n type=str,\n default=None,\n dest=\"ml_providers\",\n required=False,\n metavar=\"STR\")\n parser.add_argument(\"--jobs\",\n \"-j\",\n help=\"number of parallel processes to use (default: 1)\",\n type=positive_int,\n dest=\"jobs\",\n default=1,\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"--thrifty\",\n help=\"clear objects after scan to reduce memory consumption\",\n action=BooleanOptionalAction,\n default=True)\n parser.add_argument(\"--skip_ignored\",\n help=\"parse .gitignore files and skip credentials from ignored objects\",\n dest=\"skip_ignored\",\n action=\"store_true\")\n parser.add_argument(\"--error\",\n help=\"produce error code if credentials are found\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--save-json\",\n nargs=\"?\",\n help=\"save result to json file (default: output.json)\",\n const=\"output.json\",\n dest=\"json_filename\",\n metavar=\"PATH\")\n parser.add_argument(\"--save-xlsx\",\n nargs=\"?\",\n help=\"save result to xlsx file (default: output.xlsx)\",\n const=\"output.xlsx\",\n dest=\"xlsx_filename\",\n metavar=\"PATH\")\n parser.add_argument(\"--stdout\", help=\"print results to stdout\", action=BooleanOptionalAction, default=True)\n parser.add_argument(\"--color\", help=\"print results with colorization\", action=BooleanOptionalAction, default=False)\n parser.add_argument(\"--hashed\",\n help=\"line, variable, value will be hashed in output\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--subtext\",\n help=f\"line text will be stripped in {2 * ML_HUNK} symbols but value and variable are kept\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--sort\",\n help=\"enable output sorting\",\n dest=\"sort_output\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--log\",\n \"-l\",\n help=(f\"provide logging level of {list(Logger.LEVELS.keys())}\"\n f\" (default: 'warning', case insensitive)\"),\n default=\"warning\",\n dest=\"log\",\n metavar=\"LOG_LEVEL\",\n type=logger_levels)\n parser.add_argument(\"--size_limit\",\n help=\"set size limit of files that for scanning (eg. 1GB / 10MiB / 1000)\",\n dest=\"size_limit\",\n default=None)\n parser.add_argument(\"--banner\",\n help=\"show version and crc32 sum of CredSweeper files at start\",\n action=\"store_const\",\n const=True)\n parser.add_argument(\"--version\",\n \"-V\",\n help=\"show program's version number and exit\",\n action=\"version\",\n version=f\"CredSweeper {__version__}\")\n return parser.parse_args()\n\n\ndef get_credsweeper(args: Namespace) -> CredSweeper:\n \"\"\"Common function to create the instance\"\"\"\n if args.denylist_path is not None:\n denylist = [line for line in Util.read_file(args.denylist_path) if line]\n else:\n denylist = []\n return CredSweeper(rule_path=args.rule_path,\n config_path=args.config_path,\n json_filename=args.json_filename,\n xlsx_filename=args.xlsx_filename,\n stdout=args.stdout,\n color=args.color,\n hashed=args.hashed,\n subtext=args.subtext,\n sort_output=args.sort_output,\n use_filters=args.no_filters,\n pool_count=args.jobs,\n ml_batch_size=args.ml_batch_size,\n ml_threshold=args.ml_threshold,\n ml_config=args.ml_config,\n ml_model=args.ml_model,\n ml_providers=args.ml_providers,\n find_by_ext=args.find_by_ext,\n pedantic=args.pedantic,\n depth=args.depth,\n doc=args.doc,\n severity=args.severity,\n size_limit=args.size_limit,\n exclude_lines=denylist,\n exclude_values=denylist,\n thrifty=args.thrifty,\n log_level=args.log)\n\n\ndef scan(args: Namespace, content_provider: AbstractProvider) -> int:\n \"\"\"Scan content_provider data, print results or save them to json_filename is not None\n\n Args:\n args: arguments of the application\n content_provider: FilesProvider instance to scan data from\n\n Returns:\n Number of detected credentials\n\n Warnings:\n DeprecationWarning: Using 'json_filename' and/or 'xlsx_filename' will issue a warning.\n\n \"\"\"\n try:\n credsweeper = get_credsweeper(args)\n return credsweeper.run(content_provider=content_provider)\n except Exception as exc:\n logger.critical(exc, exc_info=True)\n logger.exception(exc)\n return -1\n\n\ndef get_commit_providers(commit: Commit, repo: Repo) -> Sequence[ByteContentProvider]:\n \"\"\"Process a commit and for providers\"\"\"\n result = {}\n # use the hardcoded sha1 until sha256 objects are not supported by GitPython\n ancestors = commit.parents or [repo.tree(\"4b825dc642cb6eb9a060e54bf8d69288fbee4904\")]\n for parent in ancestors:\n for diff in parent.diff(commit):\n # only result files\n blob_b = diff.b_blob\n if blob_b and blob_b.path not in result:\n try:\n result[blob_b.path] = ByteContentProvider(content=blob_b.data_stream.read(),\n file_path=str(blob_b.path),\n info=DiffRowType.ADDED.value)\n except Exception as exc:\n logger.warning(\"A submodule was not properly initialized or commit was removed: %s\", exc)\n return list(result.values())\n\n\ndef drill(args: Namespace) -> Tuple[int, int]:\n \"\"\"Scan repository for branches and commits\n\n Args:\n args: arguments of the application\n\n Returns:\n total credentials found\n total scanned commits\n\n \"\"\"\n total_credentials = 0\n total_commits = 0\n try:\n # repo init first\n repo = Repo(args.git)\n if args.ref:\n commits_sha1 = set(x.commit.hexsha for x in repo.refs if x.name == args.ref)\n if not commits_sha1:\n commits_sha1 = {args.ref} # single commit sha1 reference\n else:\n commits_sha1 = set(x.commit.hexsha for x in repo.refs\n if x.name.startswith('origin/') or x.name.startswith('refs/heads/'))\n logger.info(\"Git repository %s with commits: %s\", args.git, commits_sha1)\n # then - credsweeper\n credsweeper = get_credsweeper(args)\n # use flat iterations to avoid recursive limits\n to_scan = set(commits_sha1)\n # local speedup for already scanned commits - avoid file system interactive\n scanned = set()\n # to avoid double-check\n skipped = set()\n while to_scan:\n commit_sha1 = to_scan.pop()\n if commit_sha1 in scanned:\n # the commit was scanned in this launch\n continue\n commit = repo.commit(commit_sha1)\n if commit.parents:\n # add parents only when they were not skipped or scanned previously\n to_scan.update(x.hexsha for x in commit.parents if x.hexsha not in skipped and x.hexsha not in scanned)\n # check whether the commit has been checked and the report is present\n skip_already_scanned = False\n if args.json_filename:\n json_path = Path(args.json_filename)\n json_path = json_path.with_suffix(f\".{commit_sha1}{json_path.suffix}\")\n if json_path.exists():\n skip_already_scanned = True\n else:\n credsweeper.json_filename = json_path\n if args.xlsx_filename:\n xlsx_path = Path(args.xlsx_filename)\n xlsx_path = xlsx_path.with_suffix(f\".{commit_sha1}{xlsx_path.suffix}\")\n if xlsx_path.exists():\n skip_already_scanned = True\n else:\n credsweeper.xlsx_filename = xlsx_path\n if skip_already_scanned:\n skipped.add(commit_sha1)\n logger.info(\"Skip already scanned commit: %s %s\", commit_sha1, commit.committed_datetime.isoformat())\n continue\n logger.info(\"Scan commit: %s %s\", commit_sha1, commit.committed_datetime.isoformat())\n # prepare all files to scan in the commit with bytes->IO transformation to avoid a multiprocess issue\n if providers := get_commit_providers(commit, repo):\n credsweeper.credential_manager.candidates.clear()\n credsweeper.scan(providers)\n credsweeper.post_processing()\n credsweeper.export_results()\n total_credentials += credsweeper.credential_manager.len_credentials()\n total_commits += 1\n scanned.add(commit_sha1)\n except Exception as exc:\n logger.critical(exc, exc_info=True)\n return -1, total_commits\n return total_credentials, total_commits\n\n\ndef main() -> int:\n \"\"\"Main function\"\"\"\n start_time = time.perf_counter()\n result = EXIT_FAILURE\n credentials_number = 0\n args = get_arguments()\n if args.banner:\n print(f\"CredSweeper {__version__} crc32:{check_integrity():08x}\")\n Logger.init_logging(args.log, args.log_config_path)\n logger.info(\"Init CredSweeper object with arguments: %s CWD: %s\", args, os.getcwd())\n summary: Dict[str, int] = {}\n if args.path:\n logger.info(\"Run analyzer on path: %s\", args.path)\n content_provider: AbstractProvider = FilesProvider(args.path, skip_ignored=args.skip_ignored)\n credentials_number = scan(args, content_provider)\n summary[\"Detected Credentials\"] = credentials_number\n if 0 <= credentials_number:\n result = EXIT_SUCCESS\n elif args.diff_path:\n # Analyze added data\n logger.info(\"Run analyzer on added rows from patch files: %s\", args.diff_path)\n content_provider = PatchesProvider(args.diff_path, change_type=DiffRowType.ADDED)\n add_credentials_number = scan(args, content_provider)\n summary[\"Added File Credentials\"] = add_credentials_number\n # Analyze deleted data\n logger.info(\"Run analyzer on deleted rows from patch files: %s\", args.diff_path)\n content_provider = PatchesProvider(args.diff_path, change_type=DiffRowType.DELETED)\n del_credentials_number = scan(args, content_provider)\n summary[\"Deleted File Credentials\"] = del_credentials_number\n if 0 <= add_credentials_number and 0 <= del_credentials_number:\n # it means the scan was successful done\n result = EXIT_SUCCESS\n # collect number of all found credential to produce error code when necessary\n credentials_number = add_credentials_number + del_credentials_number\n elif args.git:\n logger.info(\"Run analyzer on GIT: %s\", args.git)\n credentials_number, commits_number = drill(args)\n summary[f\"Detected Credentials in {args.git} for {commits_number} commits \"] = credentials_number\n if 0 <= credentials_number:\n result = EXIT_SUCCESS\n elif args.export_config:\n logger.info(\"Exporting default config to file: %s\", args.export_config)\n config_dict = Util.json_load(APP_PATH / \"secret\" / \"config.json\")\n Util.json_dump(config_dict, args.export_config)\n result = EXIT_SUCCESS\n elif args.export_log_config:\n logger.info(\"Exporting default logger config to file: %s\", args.export_log_config)\n config_dict = Util.yaml_load(APP_PATH / \"secret\" / \"log.yaml\")\n Util.yaml_dump(config_dict, args.export_log_config)\n result = EXIT_SUCCESS\n elif args.banner and 2 == len(sys.argv):\n # only extend version invocation\n result = EXIT_SUCCESS\n else:\n logger.error(\"Not specified 'path' or 'diff_path'\")\n\n if EXIT_SUCCESS == result and len(summary):\n for k, v in summary.items():\n print(f\"{k}: {v}\")\n print(f\"Time Elapsed: {time.perf_counter() - start_time}\")\n\n if args.error and EXIT_SUCCESS == result and 0 < credentials_number:\n # override result when credentials were found with the requirement\n result = EXIT_FAILURE\n\n return result\n" }, { "path": "credsweeper/ml_model/__init__.py", "content": "" }, { "path": "credsweeper/ml_model/features/__init__.py", "content": "from credsweeper.ml_model.features.entropy_evaluation import EntropyEvaluation\nfrom credsweeper.ml_model.features.file_extension import FileExtension\nfrom credsweeper.ml_model.features.has_html_tag import HasHtmlTag\nfrom credsweeper.ml_model.features.is_secret_numeric import IsSecretNumeric\nfrom credsweeper.ml_model.features.length_of_attribute import LengthOfAttribute\nfrom credsweeper.ml_model.features.morpheme_dense import MorphemeDense\nfrom credsweeper.ml_model.features.rule_name import RuleName\nfrom credsweeper.ml_model.features.rule_severity import RuleSeverity\nfrom credsweeper.ml_model.features.search_in_attribute import SearchInAttribute\nfrom credsweeper.ml_model.features.word_in_path import WordInPath\nfrom credsweeper.ml_model.features.word_in_postamble import WordInPostamble\nfrom credsweeper.ml_model.features.word_in_preamble import WordInPreamble\nfrom credsweeper.ml_model.features.word_in_transition import WordInTransition\nfrom credsweeper.ml_model.features.word_in_value import WordInValue\nfrom credsweeper.ml_model.features.word_in_variable import WordInVariable\n" }, { "path": "credsweeper/ml_model/features/entropy_evaluation.py", "content": "import math\nfrom typing import Dict, List, Set\n\nimport numpy as np\n\nfrom credsweeper.common.constants import Chars, ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.data_content_provider import MIN_DATA_LEN\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass EntropyEvaluation(Feature):\n \"\"\"\n Renyi, Shannon entropy evaluation with Hartley entropy normalization.\n Augmentation with possible set of chars (hex, base64, etc.)\n Analyse only begin of the value\n\n See next link for details:\n https://digitalassets.lib.berkeley.edu/math/ucb/text/math_s4_v1_article-27.pdf\n\n \"\"\"\n\n # Max size of ML analyzed value is ML_HUNK but value may be bigger\n HUNK_SIZE = 4 * ML_HUNK\n LOG2_CACHE: Dict[int, float] = {x: math.log2(x) for x in range(4, 4 * ML_HUNK + 1)}\n CHAR_SET: List[Set[str]] = [set(x.value) for x in Chars]\n RESULT_SIZE = 3 + len(Chars)\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns real entropy and possible sets of characters\"\"\"\n # only head of value will be analyzed\n result: np.ndarray = np.zeros(shape=EntropyEvaluation.RESULT_SIZE, dtype=np.float32)\n value = candidate.line_data_list[0].value[:EntropyEvaluation.HUNK_SIZE]\n size = len(value)\n uniq, counts = np.unique(list(value), return_counts=True)\n if MIN_DATA_LEN <= size:\n # evaluate the entropy for a value of at least 4\n probabilities = counts / size\n hartley_entropy = EntropyEvaluation.LOG2_CACHE.get(size, -1.0)\n\n # renyi_entropy alpha=0.5\n sum_prob_05 = np.sum(probabilities**0.5)\n renyi_entropy_05 = 2 * np.log2(sum_prob_05)\n result[0] = renyi_entropy_05 / hartley_entropy\n\n # shannon_entropy or renyi_entropy alpha=1\n shannon_entropy = -np.sum(probabilities * np.log2(probabilities))\n result[1] = shannon_entropy / hartley_entropy\n\n # renyi_entropy alpha=2\n sum_prob_2 = np.sum(probabilities**2)\n renyi_entropy_2 = -1 * np.log2(sum_prob_2)\n result[2] = renyi_entropy_2 / hartley_entropy\n\n if 0 < size:\n # check charset for non-zero value\n # use the new variable to deal with mypy\n uniq_set = set(uniq)\n for n, i in enumerate(EntropyEvaluation.CHAR_SET, start=3):\n if not uniq_set.difference(i):\n result[n] = 1.0\n\n return result\n" }, { "path": "credsweeper/ml_model/features/feature.py", "content": "from abc import ABC, abstractmethod\nfrom typing import List, Any\n\nimport numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\n\n\nclass Feature(ABC):\n \"\"\"Base class for features.\"\"\"\n\n def __init__(self):\n pass\n\n def __call__(self, candidates: List[Candidate]) -> np.ndarray:\n \"\"\"Call base class for features.\n\n Args:\n candidates: list of candidates to extract features\n\n \"\"\"\n return np.array([self.extract(candidate) for candidate in candidates])\n\n @abstractmethod\n def extract(self, candidate: Candidate) -> Any:\n \"\"\"Abstract method of base class\"\"\"\n raise NotImplementedError\n" }, { "path": "credsweeper/ml_model/features/file_extension.py", "content": "from typing import List, Any\n\nimport numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass FileExtension(WordIn):\n \"\"\"Categorical feature of file type.\n\n Parameters:\n extensions: extension labels\n\n \"\"\"\n\n def __init__(self, extensions: List[str]) -> None:\n super().__init__(words=extensions)\n\n def __call__(self, candidates: List[Candidate]) -> np.ndarray:\n extension_set = set(candidate.line_data_list[0].file_type.lower() for candidate in candidates)\n return self.word_in_(extension_set)\n\n def extract(self, candidate: Candidate) -> Any:\n raise NotImplementedError\n" }, { "path": "credsweeper/ml_model/features/has_html_tag.py", "content": "from credsweeper.common.constants import CHUNK_SIZE\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\nfrom credsweeper.utils.util import Util\n\n\nclass HasHtmlTag(WordIn):\n \"\"\"Feature is true if line has HTML tags (HTML file).\"\"\"\n\n HTML_WORDS = [\n '< img', ' None:\n super().__init__(HasHtmlTag.HTML_WORDS)\n\n def extract(self, candidate: Candidate) -> float:\n subtext = Util.subtext(candidate.line_data_list[0].line, candidate.line_data_list[0].value_start, CHUNK_SIZE)\n candidate_line_data_list_0_line_lower = subtext.lower()\n if '<' not in candidate_line_data_list_0_line_lower:\n # early check\n return -1.0\n for i in self.words:\n if i in candidate_line_data_list_0_line_lower:\n return 1.0\n if \"/>\" in candidate_line_data_list_0_line_lower or \" float:\n with contextlib.suppress(ValueError):\n float(candidate.line_data_list[0].value)\n return 1.0\n return -1.0\n" }, { "path": "credsweeper/ml_model/features/length_of_attribute.py", "content": "import numpy as np\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass LengthOfAttribute(Feature):\n \"\"\"Abstract class for obtain a normalized value of length with max size of hunk\"\"\"\n\n def __init__(self, attribute: str):\n super().__init__()\n if \"line\" == attribute:\n self.hunk_plus = 2 * ML_HUNK + 1\n elif \"value\" == attribute or \"variable\" == attribute:\n self.hunk_plus = ML_HUNK + 1\n else:\n raise ValueError(f\"Not supported attribute '{attribute}'\")\n self.attribute = attribute\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns boolean for first LineData member\"\"\"\n if attribute := getattr(candidate.line_data_list[0], self.attribute, None):\n if len(attribute) < self.hunk_plus:\n # should be in (0, 1)\n return np.array([len(attribute) / self.hunk_plus])\n # 1.0 means the attribute is oversize\n return np.array([1.0])\n # the attribute is empty\n return np.array([0.0])\n" }, { "path": "credsweeper/ml_model/features/morpheme_dense.py", "content": "from credsweeper.common import static_keyword_checklist\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass MorphemeDense(Feature):\n \"\"\"Feature calculates morphemes density for a value\"\"\"\n\n def extract(self, candidate: Candidate) -> float:\n density = 0.0\n if value := candidate.line_data_list[0].value.lower():\n morphemes_length = 0\n for morpheme in static_keyword_checklist.morpheme_set:\n morpheme_pos = value.find(morpheme)\n if 0 <= morpheme_pos:\n morpheme_len = len(morpheme)\n while 0 <= morpheme_pos:\n morphemes_length += morpheme_len\n morpheme_pos += morpheme_len\n morpheme_pos = value.find(morpheme, morpheme_pos)\n # normalization: minimal morpheme length is 3\n density = morphemes_length / len(value)\n if 1.0 < density:\n # overlap morpheme case\n density = 1.0\n return density\n" }, { "path": "credsweeper/ml_model/features/rule_name.py", "content": "from typing import List, Any\n\nimport numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass RuleName(WordIn):\n \"\"\"Categorical feature that corresponds to rule name.\n\n Parameters:\n rule_names: rule name labels\n\n \"\"\"\n\n def __init__(self, rule_names: List[str]) -> None:\n super().__init__(words=rule_names)\n\n def __call__(self, candidates: List[Candidate]) -> np.ndarray:\n candidate_rule_set = set(x.rule_name for x in candidates)\n return self.word_in_(candidate_rule_set)\n\n def extract(self, candidate: Candidate) -> Any:\n raise NotImplementedError\n" }, { "path": "credsweeper/ml_model/features/rule_severity.py", "content": "from credsweeper.common.constants import Severity\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass RuleSeverity(Feature):\n \"\"\"Categorical feature that corresponds to rule name.\"\"\"\n\n def extract(self, candidate: Candidate) -> float:\n if Severity.CRITICAL == candidate.severity:\n return 1.0\n if Severity.HIGH == candidate.severity:\n return 0.75\n if Severity.MEDIUM == candidate.severity:\n return 0.5\n if Severity.LOW == candidate.severity:\n return 0.25\n if Severity.INFO == candidate.severity:\n return 0.0\n raise ValueError(f\"Unknown type of severity: {candidate.severity}\")\n" }, { "path": "credsweeper/ml_model/features/search_in_attribute.py", "content": "import re\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass SearchInAttribute(Feature):\n \"\"\"Abstract feature returns boolean for matched pattern in member of first LineData\"\"\"\n\n def __init__(self, pattern: str, attribute: str):\n super().__init__()\n self.pattern = re.compile(pattern)\n self.attribute = attribute\n\n def extract(self, candidate: Candidate) -> float:\n \"\"\"Returns boolean for first LineData member\"\"\"\n if attribute := getattr(candidate.line_data_list[0], self.attribute, None):\n if self.pattern.search(attribute):\n return 1.0\n return -1.0\n" }, { "path": "credsweeper/ml_model/features/word_in.py", "content": "from abc import abstractmethod\nfrom typing import List, Any, Set, Union\n\nimport numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.feature import Feature\n\n\nclass WordIn(Feature):\n \"\"\"Abstract feature returns array with all matched words in a string\"\"\"\n\n def __init__(self, words: List[str]):\n super().__init__()\n self.dimension = len(words)\n self.words = sorted(list(set(words)))\n self.enumerated_words = list(enumerate(self.words))\n if len(self.enumerated_words) != self.dimension:\n raise RuntimeError(f\"Check duplicates:{words}\")\n\n @abstractmethod\n def extract(self, candidate: Candidate) -> Any:\n raise NotImplementedError\n\n @property\n def zero(self) -> np.ndarray:\n \"\"\"Returns zero filled array for case of empty input\"\"\"\n return np.zeros(shape=[self.dimension], dtype=np.int8)\n\n def word_in_(self, iterable_data: Union[str, List[str], Set[str]]) -> np.ndarray:\n \"\"\"Returns array with words included in a string\"\"\"\n result: np.ndarray = self.zero\n for i, word in self.enumerated_words:\n if word in iterable_data:\n result[i] = 1\n return np.array([result])\n" }, { "path": "credsweeper/ml_model/features/word_in_path.py", "content": "import os.path\nfrom pathlib import Path\nfrom typing import List, Any\n\nimport numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInPath(WordIn):\n \"\"\"Categorical feature that corresponds to words in path (POSIX, lowercase)\"\"\"\n\n def __call__(self, candidates: List[Candidate]) -> np.ndarray:\n # actually there must be one path because the candidates are grouped before\n if file_path := candidates[0].line_data_list[0].path:\n path = Path(file_path)\n # apply ./ for normalised path to detect \"/src\" for relative path\n posix_lower_path = path.as_posix().lower() if path.is_absolute() else f\"./{path.as_posix().lower()}\"\n # prevent extra confusion from the same word in extension\n path_without_extension, _ = os.path.splitext(posix_lower_path)\n return self.word_in_(path_without_extension)\n return np.array([self.zero])\n\n def extract(self, candidate: Candidate) -> Any:\n raise NotImplementedError\n" }, { "path": "credsweeper/ml_model/features/word_in_postamble.py", "content": "import numpy as np\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInPostamble(WordIn):\n \"\"\"Feature is true if line contains at least one word from predefined list.\"\"\"\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns true if any words in a part of line after value\"\"\"\n postamble_end = len(candidate.line_data_list[0].line) \\\n if len(candidate.line_data_list[0].line) < candidate.line_data_list[0].value_end + ML_HUNK \\\n else candidate.line_data_list[0].value_end + ML_HUNK\n postamble = candidate.line_data_list[0].line[candidate.line_data_list[0].value_end:postamble_end].strip()\n\n return self.word_in_(postamble.lower()) if postamble else np.array([self.zero])\n" }, { "path": "credsweeper/ml_model/features/word_in_preamble.py", "content": "import numpy as np\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInPreamble(WordIn):\n \"\"\"Feature is true if line contains at least one word from predefined list.\"\"\"\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns true if any words in line before variable or value\"\"\"\n if 0 <= candidate.line_data_list[0].variable_start:\n preamble_start = 0 if ML_HUNK >= candidate.line_data_list[0].variable_start \\\n else candidate.line_data_list[0].variable_start - ML_HUNK\n preamble = candidate.line_data_list[0].line[preamble_start:candidate.line_data_list[0].\n variable_start].strip()\n else:\n preamble_start = 0 if ML_HUNK >= candidate.line_data_list[0].value_start \\\n else candidate.line_data_list[0].value_start - ML_HUNK\n preamble = candidate.line_data_list[0].line[preamble_start:candidate.line_data_list[0].value_start].strip()\n\n return self.word_in_(preamble.lower()) if preamble else np.array([self.zero])\n" }, { "path": "credsweeper/ml_model/features/word_in_transition.py", "content": "import numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInTransition(WordIn):\n \"\"\"Feature is true if line contains at least one word from predefined list.\"\"\"\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns true if any words between variable and value\"\"\"\n if 0 <= candidate.line_data_list[0].variable_end < candidate.line_data_list[0].value_start:\n transition = candidate.line_data_list[0].line[candidate.line_data_list[0].variable_end:candidate.\n line_data_list[0].value_start].strip()\n else:\n transition = ''\n\n return self.word_in_(transition.lower()) if transition else np.array([self.zero])\n" }, { "path": "credsweeper/ml_model/features/word_in_value.py", "content": "import numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInValue(WordIn):\n \"\"\"Feature returns true if candidate value contains at least one word from predefined list.\"\"\"\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns array of matching words for first line\"\"\"\n if value := candidate.line_data_list[0].value:\n return self.word_in_(value.lower())\n return np.array([self.zero])\n" }, { "path": "credsweeper/ml_model/features/word_in_variable.py", "content": "import numpy as np\n\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.ml_model.features.word_in import WordIn\n\n\nclass WordInVariable(WordIn):\n \"\"\"Feature returns array of words matching in variable\"\"\"\n\n def extract(self, candidate: Candidate) -> np.ndarray:\n \"\"\"Returns array of matching words for first line\"\"\"\n if variable := candidate.line_data_list[0].variable:\n return self.word_in_(variable.lower())\n return np.array([self.zero])\n" }, { "path": "credsweeper/ml_model/ml_config.json", "content": "{\n \"char_set\": \"\\u001b\\t\\n\\r !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~\",\n \"thresholds\": {\n \"lowest\": 0.22917,\n \"low\": 0.35739,\n \"medium\": 0.62204,\n \"high\": 0.79791,\n \"highest\": 0.92996\n },\n \"features\": [\n {\n \"type\": \"RuleSeverity\",\n \"comment\": \"INFO=0.0, LOW=0.25, MEDIUM=0.5, HIGH=0.75, CRITICAL=1.0\",\n \"kwargs\": {}\n },\n {\n \"type\": \"EntropyEvaluation\",\n \"kwargs\": {}\n },\n {\n \"type\": \"LengthOfAttribute\",\n \"kwargs\": {\n \"attribute\": \"line\"\n }\n },\n {\n \"type\": \"LengthOfAttribute\",\n \"kwargs\": {\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"LengthOfAttribute\",\n \"kwargs\": {\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"Bash variable\",\n \"kwargs\": {\n \"pattern\": \"^\\\\$([A-Za-z_][0-9A-Za-z_]*|\\\\{[A-Za-z_][0-9A-Za-z_]*\\\\})\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"PossibleComment replacing\",\n \"kwargs\": {\n \"pattern\": \"^\\\\s*(#|\\\\*|/\\\\*|//|--\\\\s)\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"Example pattern\",\n \"kwargs\": {\n \"pattern\": \"^<[\\\\w\\\\s.-]*>\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"Repeated symbol\",\n \"kwargs\": {\n \"pattern\": \"(?:(\\\\S)(\\\\S))((\\\\1.)|(.\\\\2)){7,}\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"SHA marker\",\n \"kwargs\": {\n \"pattern\": \"(?i:sha)[_-]?(224|256|384|512)\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"ASN1 prefix for PEM keys\",\n \"kwargs\": {\n \"pattern\": \"\\\\b(MII|LS0t)\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"camelStyle naming detection\",\n \"kwargs\": {\n \"pattern\": \"^[a-z][a-z]{1,16}[0-9]*([A-Z]([a-z]{1,16}[0-9]*|[0-9]{1,16})){1,8}$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"PascalStyle naming detection\",\n \"kwargs\": {\n \"pattern\": \"^([A-Z]([a-z]{1,16}[0-9]*|[0-9]{1,16})){1,8}$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"UPPERCASE naming detection\",\n \"kwargs\": {\n \"pattern\": \"^(_+[0-9]{1,16}|_*[A-Z]{1,16}[0-9]*)(_+([0-9]{1,16}|[A-Z]{1,16}[0-9]*)){1,8}_*$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"lowercase naming detection\",\n \"kwargs\": {\n \"pattern\": \"^(_+[0-9]{1,16}|_*[a-z]{1,16}[0-9]*)(_+([0-9]{1,16}|[a-z]{1,16}[0-9]*)){1,8}_*$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"VariableNotAllowedPatternCheck\",\n \"kwargs\": {\n \"pattern\": \"(^(@|<|\\\\{\\\\{))|([!><+*/^|)](\\\\s)?$)\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"VariableNotAllowedNameCheck - hash mentioned\",\n \"kwargs\": {\n \"pattern\": \"(?i:( h1$|md5|sha[_-]?(224|256|384|512)))\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"VariableNotAllowedNameCheck - ID detect\",\n \"kwargs\": {\n \"pattern\": \"(guid|[^a-z](?i:u?id)|([^A-Z](G?U)?I[dD])s?)$\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"AWS Key ID - true ID\",\n \"kwargs\": {\n \"pattern\": \"^A[0-9A-Z]{19,20}$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"UUID pattern\",\n \"kwargs\": {\n \"pattern\": \"^(?i:[0-9a-f]{8}(-[0-9a-f]{4}){3}-[0-9a-f]{12})$\",\n \"attribute\": \"value\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"VariableNotAllowedNameCheck - key rule\",\n \"kwargs\": {\n \"pattern\": \"(?i:(?:uniq(?:ue)?|escap(?:e|ing)|resources?|projects?|filters?|pub(?:lic)?)_?keys?)\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"VariableNotAllowedNameCheck - word at end\",\n \"kwargs\": {\n \"pattern\": \"(?i:(icon|label|mode|field|format|number|sum|size|len(gth)?|name|type|manager|algorithm|pattern|view|error|date(time)?|time(stamp)?|tag|version|hash|rate|code|fingerprint)s?$)\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"SearchInAttribute\",\n \"comment\": \"PWD invocation\",\n \"kwargs\": {\n \"pattern\": \"(?i:(^\\\\$pwd$)|(^\\\\$\\\\{#?pwd[^}]*\\\\}$)|(^\\\\$\\\\(pwd\\\\)$)|(^`pwd`$))\",\n \"attribute\": \"variable\"\n }\n },\n {\n \"type\": \"WordInVariable\",\n \"kwargs\": {\n \"words\": [\n \" \",\n \".\",\n \",\",\n \"]\",\n \"#\",\n \"@\",\n \"/\",\n \"\\\\\",\n \"!!!\",\n \"_at\",\n \"_len\",\n \"256\",\n \"512\",\n \"access\",\n \"assert\",\n \"cache\",\n \"client\",\n \"control\",\n \"crypt\",\n \"crypted\",\n \"decrypt\",\n \"encrypt\",\n \"dummy\",\n \"disable\",\n \"example\",\n \"expect\",\n \"expir\",\n \"fake\",\n \"file\",\n \"filter\",\n \"fingerprint\",\n \"guid\",\n \"hash\",\n \"keyguid\",\n \"keyid\",\n \"key_id\",\n \"label\",\n \"length\",\n \"md5\",\n \"manager\",\n \"mock\",\n \"name\",\n \"native\",\n \"obj\",\n \"opt\",\n \"p/w\",\n \"param\",\n \"pass\",\n \"path\",\n \"project\",\n \"public\",\n \"pw\",\n \"query\",\n \"secret\",\n \"size\",\n \"sha\",\n \"space\",\n \"status\",\n \"sword\",\n \"temp\",\n \"test\",\n \"thumbprint\",\n \"time\",\n \"timestamp\",\n \"title\",\n \"token\",\n \"type\",\n \"uniq\",\n \"valid\",\n \"version\",\n \"view\"\n ]\n }\n },\n {\n \"type\": \"WordInValue\",\n \"kwargs\": {\n \"words\": [\n \"%\",\n \" \",\n \":\",\n \"=\",\n \"$(\",\n \"${\",\n \"{$\",\n \"(\",\n \"->\",\n \".\",\n \"...\",\n \"123\",\n \"141592653\",\n \"718281828\",\n \"<\",\n \">\",\n \"[\",\n \"_id\",\n \"abc\",\n \"aaaa\",\n \"asdf\",\n \"allow\",\n \"arn:aws:\",\n \"bar\",\n \"disable\",\n \"changeme\",\n \"crypt\",\n \"crypted\",\n \"decrypt\",\n \"edited\",\n \"encrypt\",\n \"example\",\n \"expir\",\n \"fake\",\n \"file\",\n \"foo\",\n \"hash\",\n \"hex\",\n \"key\",\n \"min\",\n \"mock\",\n \"my\",\n \"nil\",\n \"oprst\",\n \"other\",\n \"pass\",\n \"public\",\n \"pwd\",\n \"redacted\",\n \"rsa\",\n \"salt\",\n \"secret\",\n \"sha\",\n \"ssh\",\n \"test\",\n \"word\",\n \"xxx\",\n \"xyz\"\n ]\n }\n },\n {\n \"type\": \"WordInPreamble\",\n \"kwargs\": {\n \"words\": [\n \"$\",\n \"%2\",\n \"%3\",\n \"&\",\n \"&\",\n \"(\",\n \"->\",\n \".\",\n \"://\",\n \"?\",\n \"@\",\n \"[\",\n \"approval\",\n \"arn:aws:\",\n \"assert\",\n \"case\",\n \"circle\",\n \"color\",\n \"e.g.\",\n \"equal\",\n \"example\",\n \"expect\",\n \"fake\",\n \"false\",\n \"height\",\n \"image\",\n \"line\",\n \"media\",\n \"nil\",\n \"none\",\n \"null\",\n \"pass\",\n \"path\",\n \"pwd\",\n \"sqa\",\n \"test\",\n \"true\",\n \"undefined\",\n \"unit\",\n \"where\",\n \"width\",\n \"word\"\n ]\n }\n },\n {\n \"type\": \"WordInTransition\",\n \"kwargs\": {\n \"words\": [\n \"%2\",\n \"%3\",\n \"&\",\n \"(\",\n \"->\",\n \"=>\",\n \"'\",\n \"\\\"\",\n \".\",\n \",\",\n \"?\",\n \"@\",\n \"[\",\n \"{\",\n \"basic\",\n \"bearer\",\n \"get\",\n \"e.g.\",\n \"equal\",\n \"env\",\n \"example\",\n \"expect\",\n \"line\",\n \"media\",\n \"pass\",\n \"password\",\n \"path\",\n \"test\",\n \"unit\"\n ]\n }\n },\n {\n \"type\": \"WordInPostamble\",\n \"kwargs\": {\n \"words\": [\n \"$\",\n \"%2\",\n \"%3\",\n \"&\",\n \"&\",\n \"(\",\n \"->\",\n \"'\",\n \"\\\"\",\n \".\",\n \"://\",\n \"?\",\n \"@\",\n \"[\",\n \"]\",\n \"}\",\n \"\\\\\",\n \"assert\",\n \"case\",\n \"circle\",\n \"color\",\n \"e.g.\",\n \"equal\",\n \"example\",\n \"expect\",\n \"fake\",\n \"false\",\n \"height\",\n \"image\",\n \"line\",\n \"media\",\n \"nil\",\n \"none\",\n \"null\",\n \"pass\",\n \"path\",\n \"pwd\",\n \"sqa\",\n \"test\",\n \"true\",\n \"undefined\",\n \"unit\",\n \"width\",\n \"word\"\n ]\n }\n },\n {\n \"type\": \"WordInPath\",\n \"kwargs\": {\n \"words\": [\n \"test\",\n \"mock\",\n \"/src\",\n \"code\",\n \"/include\",\n \"internal\",\n \"tool\",\n \"util\",\n \"example\",\n \"sample\",\n \"conf\",\n \"secret\",\n \"setting\",\n \"security\",\n \"secure\",\n \"resource\",\n \"fixture\",\n \"docker\",\n \"/docs\",\n \"/doc/\",\n \"document\",\n \"/lang\",\n \"/local/\",\n \"/locale\",\n \"/lib\",\n \"/spec\",\n \"/pkg\",\n \"/api\",\n \"/rest\",\n \"/opt\",\n \"/sys\",\n \"kube\",\n \"kafka\",\n \"cluster\",\n \"template\",\n \"other\",\n \"public\",\n \"init\",\n \"client\",\n \"server\",\n \"/model\",\n \"/modul\",\n \"browser\",\n \"/env/\",\n \"/app\",\n \"/assets/\",\n \"vendor\",\n \"readme\",\n \"build\",\n \"/dist-packages\",\n \"/record\",\n \"/script\",\n \"/site-packages\",\n \"python\",\n \"/usr\",\n \"/etc\",\n \"/fuzz\"\n ]\n }\n },\n {\n \"type\": \"MorphemeDense\"\n },\n {\n \"type\": \"HasHtmlTag\"\n },\n {\n \"type\": \"IsSecretNumeric\"\n },\n {\n \"type\": \"FileExtension\",\n \"kwargs\": {\n \"extensions\": [\n \"\",\n \".04\",\n \".1\",\n \".adoc\",\n \".asciidoc\",\n \".axaml\",\n \".bash\",\n \".bat\",\n \".bats\",\n \".bazel\",\n \".bin\",\n \".build\",\n \".bundle\",\n \".bzl\",\n \".c\",\n \".cast\",\n \".cc\",\n \".cf\",\n \".cjs\",\n \".cljc\",\n \".cmd\",\n \".cnf\",\n \".coffee\",\n \".conf\",\n \".config\",\n \".cpp\",\n \".crt\",\n \".cs\",\n \".csp\",\n \".csv\",\n \".dart\",\n \".dist\",\n \".dockerfile\",\n \".edited\",\n \".eex\",\n \".env\",\n \".erb\",\n \".erl\",\n \".ex\",\n \".example\",\n \".exs\",\n \".ext\",\n \".fsproj\",\n \".g4\",\n \".gml\",\n \".go\",\n \".golden\",\n \".gradle\",\n \".graphql\",\n \".groovy\",\n \".gtpl\",\n \".h\",\n \".haml\",\n \".har\",\n \".hpp\",\n \".hs\",\n \".html\",\n \".idl\",\n \".iml\",\n \".in\",\n \".inc\",\n \".ini\",\n \".ipynb\",\n \".j\",\n \".j2\",\n \".java\",\n \".jenkinsfile\",\n \".js\",\n \".json\",\n \".jsp\",\n \".jsx\",\n \".ks\",\n \".kt\",\n \".kts\",\n \".las\",\n \".ldif\",\n \".ldml\",\n \".less\",\n \".libsonnet\",\n \".lkml\",\n \".lock\",\n \".log\",\n \".lua\",\n \".m\",\n \".manifest\",\n \".markdown\",\n \".markerb\",\n \".md\",\n \".mdx\",\n \".mjs\",\n \".mk\",\n \".ml\",\n \".mlir\",\n \".mod\",\n \".moo\",\n \".ndjson\",\n \".nolint\",\n \".odd\",\n \".onnx\",\n \".oracle\",\n \".original\",\n \".pan\",\n \".patch\",\n \".php\",\n \".pl\",\n \".pm\",\n \".po\",\n \".pod\",\n \".postinst\",\n \".pp\",\n \".ppk\",\n \".proj\",\n \".properties\",\n \".proto\",\n \".ps1\",\n \".purs\",\n \".pxd\",\n \".py\",\n \".pyi\",\n \".pyx\",\n \".r\",\n \".rake\",\n \".rb\",\n \".re\",\n \".response\",\n \".resx\",\n \".rexx\",\n \".rrc\",\n \".rs\",\n \".rsa\",\n \".rsp\",\n \".rst\",\n \".rules\",\n \".sample\",\n \".sbt\",\n \".scala\",\n \".secrets\",\n \".sh\",\n \".snap\",\n \".sql\",\n \".storyboard\",\n \".strings\",\n \".sty\",\n \".swift\",\n \".t\",\n \".td\",\n \".tdf\",\n \".template\",\n \".test\",\n \".testsettings\",\n \".tf\",\n \".tfstate\",\n \".tfvars\",\n \".tl\",\n \".tmpl\",\n \".token\",\n \".toml\",\n \".travis\",\n \".ts\",\n \".tsx\",\n \".txt\",\n \".var\",\n \".vsmdi\",\n \".vue\",\n \".xaml\",\n \".xib\",\n \".xml\",\n \".yaml\",\n \".yml\",\n \".zsh\"\n ]\n }\n },\n {\n \"type\": \"RuleName\",\n \"kwargs\": {\n \"rule_names\": [\n \"API\",\n \"Auth\",\n \"CMD ConvertTo-SecureString\",\n \"CMD Password\",\n \"CMD Secret\",\n \"CMD Token\",\n \"CURL User Password\",\n \"Credential\",\n \"Key\",\n \"Nonce\",\n \"Password\",\n \"SQL Password\",\n \"Salt\",\n \"Secret\",\n \"Token\",\n \"URL Credentials\"\n ]\n }\n }\n ]\n}\n" }, { "path": "credsweeper/ml_model/ml_validator.py", "content": "import hashlib\nimport json\nimport logging\nfrom pathlib import Path\nfrom typing import List, Tuple, Union, Optional, Dict\n\nimport numpy as np\nfrom onnxruntime import InferenceSession\n\nfrom credsweeper.common.constants import ThresholdPreset, ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.candidate_key import CandidateKey\nfrom credsweeper.ml_model import features\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass MlValidator:\n \"\"\"ML validation class\"\"\"\n MAX_LEN = 2 * ML_HUNK # for whole line limit\n # used for initial fill\n ZERO_CHAR = '\\x00'\n # applied for unknown characters\n FAKE_CHAR = '\\x01'\n\n _dir_path = Path(__file__).parent\n\n def __init__(\n self, #\n threshold: Union[float, ThresholdPreset], #\n ml_config: Union[None, str, Path] = None, #\n ml_model: Union[None, str, Path] = None, #\n ml_providers: Optional[str] = None) -> None:\n \"\"\"Init\n\n Args:\n threshold: decision threshold\n ml_config: path to ml config\n ml_model: path to ml model\n ml_providers: coma separated list of providers https://onnxruntime.ai/docs/execution-providers/\n \"\"\"\n self.__session: Optional[InferenceSession] = None\n\n if ml_config:\n ml_config_path = Path(ml_config)\n else:\n ml_config_path = MlValidator._dir_path / \"ml_config.json\"\n with open(ml_config_path, \"rb\") as f:\n __ml_config_data = f.read()\n\n model_config = json.loads(__ml_config_data)\n\n if ml_model:\n ml_model_path = Path(ml_model)\n else:\n ml_model_path = MlValidator._dir_path / \"ml_model.onnx\"\n with open(ml_model_path, \"rb\") as f:\n self.__ml_model_data = f.read()\n\n if ml_providers:\n self.providers = ml_providers.split(',')\n else:\n self.providers = [\"CPUExecutionProvider\"]\n\n if isinstance(threshold, float):\n self.threshold = threshold\n elif isinstance(threshold, ThresholdPreset) and \"thresholds\" in model_config:\n self.threshold = model_config[\"thresholds\"][threshold.value]\n else:\n self.threshold = 0.5\n logger.warning(\"Use fallback threshold value: %s\", self.threshold)\n\n char_set = set(model_config[\"char_set\"])\n if len(char_set) != len(model_config[\"char_set\"]):\n logger.warning('Duplicated symbols in \"char_set\"?')\n if self.ZERO_CHAR in char_set or self.FAKE_CHAR in char_set:\n raise ValueError(f'Unacceptable symbols 0x00 or 0x01 in \"char_set\"={char_set}')\n self.char_dict = {self.ZERO_CHAR: 0, self.FAKE_CHAR: 1}\n self.char_dict.update({\n char: index\n for index, char in enumerate(sorted(list(char_set)), start=len(self.char_dict))\n })\n self.num_classes = len(self.char_dict)\n\n self.common_feature_list = []\n self.unique_feature_list = []\n if logger.isEnabledFor(logging.INFO):\n config_md5 = hashlib.md5(__ml_config_data).hexdigest()\n model_md5 = hashlib.md5(self.__ml_model_data).hexdigest()\n logger.info(\"Init ML validator with providers: '%s' ; model:'%s' md5:%s ; config:'%s' md5:%s\",\n self.providers, ml_config_path, config_md5, ml_model_path, model_md5)\n logger.debug(str(model_config))\n for feature_definition in model_config[\"features\"]:\n feature_class = feature_definition[\"type\"]\n kwargs = feature_definition.get(\"kwargs\", {})\n feature_constructor = getattr(features, feature_class, None)\n if feature_constructor is None:\n raise ValueError(f\"Error while parsing model details. Cannot create feature '{feature_class}'\"\n f\" from {feature_definition}\")\n try:\n feature = feature_constructor(**kwargs)\n except TypeError:\n logger.error(\"Error while parsing model details. Cannot create feature '%s' from %s\", feature_class,\n feature_definition)\n raise\n if feature_definition[\"type\"] in [\"RuleName\"]:\n self.unique_feature_list.append(feature)\n else:\n self.common_feature_list.append(feature)\n\n def __reduce__(self):\n # TypeError: cannot pickle 'onnxruntime.capi.onnxruntime_pybind11_state.InferenceSession' object\n self.__session = None\n return super().__reduce__()\n\n @property\n def session(self) -> InferenceSession:\n \"\"\"session getter to prevent pickle error\"\"\"\n if not self.__session:\n self.__session = InferenceSession(self.__ml_model_data, providers=self.providers)\n if not self.__session:\n raise RuntimeError(\"InferenceSession was not initialized!\")\n return self.__session\n\n def encode(self, text: str, limit: int) -> np.ndarray:\n \"\"\"Encodes prepared text to array\"\"\"\n result_array: np.ndarray = np.zeros(shape=(limit, self.num_classes), dtype=np.float32)\n if text is None:\n return result_array\n for i, c in enumerate(text):\n if i >= limit:\n break\n if c in self.char_dict:\n result_array[i, self.char_dict[c]] = 1.0\n else:\n result_array[i, self.char_dict[MlValidator.FAKE_CHAR]] = 1.0\n return result_array\n\n def encode_line(self, text: str, position: int):\n \"\"\"Encodes line with balancing for position\"\"\"\n offset = len(text) - len(text.lstrip())\n pos = position - offset\n stripped = text.strip()\n if MlValidator.MAX_LEN < len(stripped):\n stripped = Util.subtext(stripped, pos, ML_HUNK)\n return self.encode(stripped, MlValidator.MAX_LEN)\n\n def encode_value(self, text: str) -> np.ndarray:\n \"\"\"Encodes line with balancing for position\"\"\"\n stripped = text.strip()\n return self.encode(stripped[:ML_HUNK], ML_HUNK)\n\n def _call_model(self, line_input: np.ndarray, variable_input: np.ndarray, value_input: np.ndarray,\n feature_input: np.ndarray) -> np.ndarray:\n input_feed: Dict[str, np.ndarray] = {\n \"line_input\": line_input.astype(np.float32),\n \"variable_input\": variable_input.astype(np.float32),\n \"value_input\": value_input.astype(np.float32),\n \"feature_input\": feature_input.astype(np.float32),\n }\n result = self.session.run(output_names=None, input_feed=input_feed)\n if result and isinstance(result[0], np.ndarray):\n return result[0]\n raise RuntimeError(f\"Unexpected type {type(result[0])}\")\n\n def extract_common_features(self, candidates: List[Candidate]) -> np.ndarray:\n \"\"\"Extract features that are guaranteed to be the same for all candidates on the same line with same value.\"\"\"\n feature_array: np.ndarray = np.array([], dtype=np.float32)\n # Extract features from credential candidate\n default_candidate = candidates[0]\n for feature in self.common_feature_list:\n new_feature = feature([default_candidate])[0]\n if not isinstance(new_feature, np.ndarray):\n new_feature = np.array([new_feature])\n feature_array = np.append(feature_array, new_feature)\n return feature_array\n\n def extract_unique_features(self, candidates: List[Candidate]) -> np.ndarray:\n \"\"\"Extract features that can be different between candidates. Join them with or operator.\"\"\"\n feature_array: np.ndarray = np.array([], dtype=np.int8)\n default_candidate = candidates[0]\n for feature in self.unique_feature_list:\n new_feature = feature([default_candidate])[0]\n if not isinstance(new_feature, np.ndarray):\n new_feature = np.array([new_feature])\n feature_array = np.append(feature_array, new_feature)\n for candidate in candidates[1:]:\n for feature in self.unique_feature_list:\n new_feature = feature([candidate])[0]\n if not isinstance(new_feature, np.ndarray):\n new_feature = np.array([new_feature])\n feature_array = feature_array | new_feature\n return feature_array\n\n def get_group_features(self, candidates: List[Candidate]) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n \"\"\"\n `np.newaxis` used to add new dimension if front, so input will be treated as a batch\n \"\"\"\n # all candidates are from the same line\n default_candidate = candidates[0]\n line_input = self.encode_line(default_candidate.line_data_list[0].line,\n default_candidate.line_data_list[0].value_start)[np.newaxis]\n variable = ''\n value = ''\n for candidate in candidates:\n if not variable and candidate.line_data_list[0].variable:\n variable = candidate.line_data_list[0].variable\n if not value and candidate.line_data_list[0].value:\n value = candidate.line_data_list[0].value\n if variable and value:\n break\n variable_input = self.encode_value(variable)[np.newaxis]\n value_input = self.encode_value(value)[np.newaxis]\n feature_array = self.extract_features(candidates)\n return line_input, variable_input, value_input, feature_array\n\n def extract_features(self, candidates: List[Candidate]) -> np.ndarray:\n \"\"\"extracts common and unique features from list of candidates\"\"\"\n common_features = self.extract_common_features(candidates)\n unique_features = self.extract_unique_features(candidates)\n feature_hstack = np.hstack([common_features, unique_features])\n feature_array = np.array([feature_hstack])\n return feature_array\n\n def _batch_call_model(self, line_input_list, variable_input_list, value_input_list, features_list) -> np.ndarray:\n \"\"\"auxiliary method to invoke twice\"\"\"\n line_inputs_vstack = np.vstack(line_input_list)\n variable_inputs_vstack = np.vstack(variable_input_list)\n value_inputs_vstack = np.vstack(value_input_list)\n feature_array_vstack = np.vstack(features_list)\n result_call = self._call_model(line_inputs_vstack, variable_inputs_vstack, value_inputs_vstack,\n feature_array_vstack)\n result = result_call[:, 0]\n return result\n\n def validate_groups(self, group_list: List[Tuple[CandidateKey, List[Candidate]]],\n batch_size: int) -> Tuple[np.ndarray, np.ndarray]:\n \"\"\"Use ml model on list of candidate groups.\n\n Args:\n group_list: List of tuples (value, group)\n batch_size: ML model batch\n\n Return:\n Boolean numpy array with decision based on the threshold,\n and numpy array with probability predicted by the model\n\n \"\"\"\n line_input_list = []\n variable_input_list = []\n value_input_list = []\n features_list = []\n probability: np.ndarray = np.zeros(len(group_list), dtype=np.float32)\n head = tail = 0\n for _group_key, candidates in group_list:\n line_input, variable_input, value_input, feature_array = self.get_group_features(candidates)\n line_input_list.append(line_input)\n variable_input_list.append(variable_input)\n value_input_list.append(value_input)\n features_list.append(feature_array)\n tail += 1\n if 0 == tail % batch_size:\n # use the approach to reduce memory consumption for huge candidates list\n probability[head:tail] = self._batch_call_model(line_input_list, variable_input_list, value_input_list,\n features_list)\n head = tail\n line_input_list.clear()\n variable_input_list.clear()\n value_input_list.clear()\n features_list.clear()\n if head != tail:\n probability[head:tail] = self._batch_call_model(line_input_list, variable_input_list, value_input_list,\n features_list)\n is_cred = self.threshold <= probability\n if logger.isEnabledFor(logging.DEBUG):\n for i, decision in enumerate(is_cred):\n logger.debug(\"ML decision: %s with prediction: %s for value: %s\", decision, probability[i],\n group_list[i][0])\n # apply cast to float to avoid json export issue\n return is_cred, probability.astype(float)\n" }, { "path": "credsweeper/py.typed", "content": "" }, { "path": "credsweeper/rules/__init__.py", "content": "" }, { "path": "credsweeper/rules/config.yaml", "content": "- name: DOC_GET\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P(\\w*(?i:비밀번호|비번|패스워드|키|암호화?|토큰|(?(\\\\*([\\\"']|&(quot|apos|#3[49]);)){1,4})(?P(.(?!(?P=lq))){4,8000}.?)\n filter_type:\n - ValueAllowlistCheck\n - ValueBlocklistCheck\n - LineGitBinaryCheck\n - LineUUEPartCheck\n - ValueFilePathCheck\n - ValuePatternCheck(5)\n min_line_len: 8\n required_substrings:\n - pass\n - pw\n - token\n - secret\n - key\n - cred\n - 비밀번호\n - 비번\n - 패스워드\n - 암호\n - 키\n - 토큰\n target:\n - doc\n use_ml: true\n\n- name: DOC_CREDENTIALS\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P[\\\"'`(])?\\s*(?P(\\w*(?i:(?설정은|:=|:(?!:)|=(>|>|(\\\\\\\\*u00|%)26gt;)|!==|!=|===|==|=~|=|%3[Dd])\\s*)(?P[\\\"'`]{1,6})?(?P(?(quote)(?(wrap)[^\\\"'`)]{4,8000}|[^\\\"'`]{4,8000})|(?(wrap)[^\\\"'`)]{4,8000}|\\S{4,8000})))\n filter_type:\n - ValueAllowlistCheck\n - ValueBlocklistCheck\n - LineGitBinaryCheck\n - LineUUEPartCheck\n - ValueFilePathCheck\n - ValuePatternCheck(5)\n - ValueSealedSecretCheck\n min_line_len: 8\n required_substrings:\n - pass\n - sword\n - pw\n - p/w\n - paasw\n - 비밀번호\n - 비번\n - 패스워드\n - 암호\n - token\n - secret\n - key\n - credential\n - 키\n - 토큰\n target:\n - doc\n use_ml: true\n\n- name: SECRET_PAIR\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P[\\\"'`]?(?i:token|secret|key|키|암호화?|토큰)[\\\"'`]?)((\\s)*(?P설정은|:=|:(?!:)|=(>|>|(\\\\\\\\*u00|%)26gt;)|!==|!=|===|==|=~|=|%3[Dd])(\\s)*)(?P[\\\"'`(])?(?P(?-i:(?P    [A-Z])|(?P[a-z])|(?P[0-9/_+=~!@#$%^&*;:?-])){8,80}(?(a)(?(b)(?(c)((?(quote)[^)\\\"'`]{1,8000}|([0-9A-Za-z/_+=~!@#$%^&*;:?-]{1,8000}|\\b))|$)|(?!x)x)|(?!x)x)|(?!x)x))(?(quote)[)\\\"'`])\n filter_type:\n - ValueAllowlistCheck\n - ValuePatternCheck(4)\n - ValueEntropyBase64Check\n - ValueMorphemesCheck\n - ValueSealedSecretCheck\n min_line_len: 16\n required_substrings:\n - token\n - secret\n - key\n - 키\n - 암호\n - 토큰\n target:\n - doc\n use_ml: true\n\n- name: PASSWD_PAIR\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P[\\\"'`]?(?i:(?설정은|:=|:(?!:)|=(>|>|(\\\\\\\\*u00|%)26gt;)|!==|!=|===|==|=~|=|%3[Dd])(\\s)*)(?P[\\\"'`(])?(?P(?-i:(?P[A-Z])|(?P[a-z])|(?P[0-9/_+=~!@#$%^&*;:?-])){8,64}(?(a)(?(b)(?(c)((?(quote)[^)\\\"'`]{1,8000}|([0-9A-Za-z/_+=~!@#$%^&*;:?-]{1,8000}|\\b))|$)|(?!x)x)|(?!x)x)|(?!x)x))(?(quote)[)\\\"'`])\n filter_type:\n - ValueAllowlistCheck\n - ValuePatternCheck(4)\n - ValueDictionaryKeywordCheck\n - LineGitBinaryCheck\n - LineUUEPartCheck\n - ValueFilePathCheck\n - ValueHexNumberCheck\n - ValueSealedSecretCheck\n min_line_len: 10\n required_substrings:\n - pass\n - sword\n - pw\n - p/w\n - paasw\n - 비밀번호\n - 비번\n - 패스워드\n - 암호\n target:\n - doc\n use_ml: true\n\n- name: IP_ID_PASSWORD_TRIPLE\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (^|\\s|(?P(?i:\\bip[\\s/]{1,80}id[\\s/]{1,80}pw[\\s/:]{0,80}))|(?P://))(?P(?(?(url)(?-i:(?P[A-Z])|(?P[a-z])|(?P[0-9_+=~!@#$%^&*;?-])){7,64}(?(a)(?(b)(?(c)(\\S|$)|(?!x)x)|(?!x)x)|(?!x)x)|(?-i:(?P[A-Z])|(?P[a-z])|(?P[0-9/_+=~!@#$%^&*;?-])){7,64}(?(e)(?(f)(?(g)(\\S|$)|(?!x)x)|(?!x)x)|(?!x)x)))(?:\\s|[^/]|$)\n filter_type:\n - ValueAllowlistCheck\n - ValuePatternCheck(4)\n - ValueDictionaryKeywordCheck\n min_line_len: 10\n required_substrings:\n - \".\"\n target:\n - doc\n use_ml: true\n\n- name: ID_PAIR_PASSWD_PAIR\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P--)?(?P\\w*(?i:pa[as]swords?|passwd?|pwd|\\bp/w|\\bpw|비밀번호|비번|패스워드|암호))\\s*?(?(ddash)[ =]|[:=/>-]{1,2})\\s*(?P[\\\"'`]{1,8})?(?P(?-i:(?P[A-Z])|(?P[a-z])|(?P[0-9/_+=~!@#$%^&*;:?-])){4,64}(?(a)(?(b)(?(c)(\\S|$)|(?!x)x)|(?!x)x)|(?!x)x))(?(quote)(?P=quote)|(\\s|$))\n - (?P--)?(?P(?i:user\\s*)?(?i:id|login|account|root|admin|user|name|wifi|role|host|default|계정|아이디))\\s*?(?(ddash)[ =]|[ :=])\\s*?(?P\\S+)\n filter_type:\n - ValueAllowlistCheck\n - ValuePatternCheck(4)\n min_line_len: 10\n required_substrings:\n - pass\n - sword\n - p/w\n - pw\n - 비밀번호\n - 비번\n - 패스워드\n - 암호\n target:\n - doc\n use_ml: true\n\n- name: ID_PASSWD_PAIR\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P[\\w.-]{0,80}(?i:(?P\\bid\\b)|id\\b|user|name|계정|아이디)[\\w.-]{0,80}(?(id)[ :(/]{1,80}|[:(/]{1,80})(?i:pa[as]swo?r?ds?|pwd?|비밀번호|비번|패스워드|암호))\\)?(\\s*->\\s*|[ =:)(/]{1,80}|\\s+is\\s+|\\s+are\\s+|\\s*는\\s*|\\s*은\\s*|\\s*설정은\\s*)\\(?(?P[\\w.-]{2,64})[ :\\(/\\\"',]{1,80}(?P(?-i:(?P[A-Z])|(?P[a-z])|(?P[0-9/_+=~!@#$%^&*;:?-])){4,64}(?(a)(?(b)(?(c)(\\S|$)|(?!x)x)|(?!x)x)|(?!x)x))\n filter_type:\n - ValueAllowlistCheck\n - ValuePatternCheck(4)\n - ValueDictionaryKeywordCheck\n min_line_len: 10\n required_substrings:\n - pw\n - pass\n - sword\n - 비밀번호\n - 비번\n - 패스워드\n - 암호\n target:\n - doc\n use_ml: true\n\n- name: UUID\n severity: info\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9A-F]{8}(-[0-9A-F]{4}){3}-[0-9A-F]{12}|[0-9a-f]{8}(-[0-9a-f]{4}){3}-[0-9a-f]{12})(?![0-9A-Za-z_+-])\n min_line_len: 36\n required_substrings:\n - \"-\"\n filter_type:\n - ValuePatternCheck(4)\n use_ml: false\n target:\n - code\n - doc\n\n- name: Akamai Credentials\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pakab-[0-9a-z]{16}-[0-9a-z]{16})(?!\\.[0-9a-z-]{1,80}\\.akamaiapis\\.net)\n filter_type: GeneralPattern\n required_substrings:\n - akab-\n min_line_len: 38\n target:\n - code\n - doc\n\n- name: Amazon Bedrock API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P(ABSK|bedrock-api-key-)[0-9A-Za-z/+]{28,800})(?![0-9A-Za-z/+])\n filter_type: GeneralPattern\n required_substrings:\n - ABSK\n - bedrock-api-key-\n min_line_len: 44\n target:\n - code\n - doc\n\n- name: AWS Client ID\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P(A3T[0-9A-Z]|ABIA|ACCA|AGPA|AIDA|AIPA|AKIA|ANPA|ANVA|AROA|APKA|ASCA|ASIA)[0-9A-Z]{16,17})(?![0-9A-Za-z_+-])\n filter_type: GeneralPattern\n required_substrings:\n - A3T\n - ABIA\n - ACCA\n - AGPA\n - AIDA\n - AIPA\n - AKIA\n - ANPA\n - ANVA\n - AROA\n - APKA\n - ASCA\n - ASIA\n min_line_len: 20\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: AWS Multi\n severity: high\n confidence: moderate\n type: multi\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PA(KIA|SIA)[0-9A-Z]{16})(?![0-9A-Za-z_])\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P((?P[A-Z])|(?P[a-z])|(?P[0-9/+])){40,44}(?(a)(?(b)(?(c)\\b|(?!x)x)|(?!x)x)|(?!x)x))(?![0-9A-Za-z/+])\n filter_type:\n - LineSpecificKeyCheck\n - ValuePatternCheck\n - ValueBase64PartCheck\n - ValueMorphemesCheck\n required_substrings:\n - AKIA\n - ASIA\n min_line_len: 20\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: AWS MWS Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pamzn\\.mws\\.[0-9a-z]{8}-[0-9a-z]{4}-[0-9a-z]{4}-[0-9a-z]{4}-[0-9a-z]{12})(?![0-9A-Za-z_-])\n filter_type: GeneralPattern\n required_substrings:\n - amzn.mws.\n min_line_len: 30\n target:\n - code\n - doc\n\n- name: Dynatrace API Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pdt0[A-Za-z]{1}[0-9]{2}\\.[0-9A-Z]{24}\\.[0-9A-Z]{64})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - dt0\n min_line_len: 90\n target:\n - code\n - doc\n\n- name: Facebook Access Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PEAA[0-9A-Za-z]{80,800})\n filter_type:\n - ValuePatternCheck\n - ValueBase64PartCheck\n - ValueNotPartEncodedCheck\n required_substrings:\n - EAA\n min_line_len: 80\n target:\n - code\n - doc\n\n- name: Facebook App Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9]{12,18}\\|[0-9A-Za-z_-]{24,28})(?![0-9A-Za-z_+-])\n filter_type: TokenPattern\n required_substrings:\n - \"|\"\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n min_line_len: 33\n target:\n - code\n - doc\n\n- name: Google API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PAIza[0-9A-Za-z_-]{35})\n filter_type: TokenPattern\n required_substrings:\n - AIza\n min_line_len: 39\n target:\n - code\n - doc\n\n- name: Google Multi\n severity: high\n confidence: moderate\n type: multi\n values:\n - (?P[0-9]{3,80}-[0-9a-z_]{32}\\.apps\\.googleusercontent\\.com)\n - \\b(?PGOCSPX-[0-9A-Za-z_-]{28}|((?P[A-Z])|(?P[a-z])|(?P[0-9_-])){24,80}(?(a)(?(b)(?(c)\\b|(?!x)x)|(?!x)x)|(?!x)x))\n filter_type: GeneralPattern\n required_substrings:\n - .apps.googleusercontent.com\n min_line_len: 40\n target:\n - code\n - doc\n\n- name: Google OAuth Secret\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PGOCSPX-[0-9A-Za-z_-]{28})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - GOCSPX-\n min_line_len: 40\n target:\n - code\n - doc\n\n- name: Google OAuth Access Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?Pya29\\.[0-9A-Za-z_-]{22,8000})\n filter_type: TokenPattern\n required_substrings:\n - ya29.\n min_line_len: 27\n target:\n - code\n - doc\n\n- name: Google OAuth Refresh Token\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P1//0[0-9A-Za-z_-]{80,8000})\n filter_type: TokenPattern\n required_substrings:\n - 1//0\n min_line_len: 84\n target:\n - code\n - doc\n\n- name: Heroku Credentials\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PHRKU-([0-9A-Za-z_-]{60}|[0-9A-Fa-f]{8}(-[0-9A-Fa-f]{4}){3}-[0-9A-Fa-f]{12}))\n filter_type: TokenPattern\n required_substrings:\n - HRKU-\n min_line_len: 41\n target:\n - code\n - doc\n\n- name: Instagram Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PIGQVJ[=0-9A-Za-z_-]{100,8000})(?![=0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - IGQVJ\n min_line_len: 105\n target:\n - code\n - doc\n\n- name: JSON Web Token\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?PeyJ[=0-9A-Za-z_+/-]{15,8000}(\\.[=0-9A-Za-z_+/-]{0,8000}){2,16})(?![=0-9A-Za-z_-])\n filter_type:\n - ValueJsonWebTokenCheck\n required_substrings:\n - eyJ\n min_line_len: 64\n target:\n - code\n - doc\n\n- name: JSON Web Key\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?P\\b(e(yJ|yAi|woi|wog|w0K)|W(yJ|3si|wp7|wog|w0K|3sK))[0-9A-Za-z_+/-]{60,8000})\n filter_type:\n - ValueJsonWebKeyCheck\n required_substrings:\n - eyJ\n - eyAi\n - ewoi\n - ewog\n - ew0K\n - WyJ\n - W3si\n - Wwp7\n - Wwog\n - Ww0K\n - W3sK\n min_line_len: 64\n target:\n - code\n - doc\n\n- name: JWK\n severity: medium\n confidence: moderate\n type: multi\n values:\n - (?P['\"]?\\b(?Pkty)[^0-9A-Za-z_-]{1,8}(RSA|EC|oct)\\b['\"]?)\n - (?P\\b[dk])[^0-9A-Za-z_-]{1,8}(?P[0-9A-Za-z_-]{22,8000})(?![=0-9A-Za-z_-])\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n required_substrings:\n - kty\n min_line_len: 8\n target:\n - code\n - doc\n\n- name: MailChimp API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9A-Za-z_-]{32}-us[0-9]{1,2})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - -us\n min_line_len: 35\n target:\n - code\n - doc\n\n- name: MailGun API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pkey-[0-9a-z]{32}|[0-9a-f]{32}-[0-9a-f]{8}-[0-9a-f]{8})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n min_line_len: 36\n target:\n - code\n - doc\n\n- name: PayPal Braintree Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Paccess_token\\$production\\$[0-9a-z]{16}\\$[0-9a-z]{32})(?![0-9A-Za-z_-])\n filter_type: GeneralPattern\n required_substrings:\n - access_token$production$\n min_line_len: 72\n target:\n - code\n - doc\n\n- name: PEM Private Key\n severity: high\n confidence: strong\n type: pem_key\n values:\n - (?P-----BEGIN(?![^-]*ENCRYPTED)[^-]*PRIVATE[^-]*KEY[^-]*-----)\n min_line_len: 27\n target:\n - code\n - doc\n\n- name: BASE64 encoded PEM Private Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P[0-9A-Za-z_/+-]{0,8000}LS0t(LS1CRUdJTiB|LUJFR0lOI|QkVHSU4g)[0-9A-Za-z_/+-]{0,11}(UFJJVkFURSBLRVkt|QUklWQVRFIEtFWS0t|FBSSVZBVEUgS0VZ)[0-9A-Za-z_/+-]{1,8000}LS0t[0-9A-Za-z_/+-]{1,8000})\n filter_type:\n - ValueBase64EncodedPem\n min_line_len: 300\n required_substrings:\n - UFJJVkFURSBLRVkt\n - QUklWQVRFIEtFWS0t\n - FBSSVZBVEUgS0VZ\n target:\n - code\n - doc\n\n- name: BASE64 Private Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PMII[A-Za-f][0-9A-Za-z/+]{8}(?s:[^!#$&()*\\-.:;<=>?@\\[\\]^_{|}~]{8,8000}))\n filter_type:\n - ValueBase64KeyCheck\n min_line_len: 160\n required_substrings:\n - MII\n target:\n - code\n - doc\n\n- name: Picatic API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Psk_live_[0-9a-z]{32})(?![0-9A-Za-z_-])\n filter_type: GeneralPattern\n required_substrings:\n - sk_live_\n min_line_len: 40\n target:\n - code\n - doc\n\n- name: SendGrid API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PSG\\.[0-9A-Za-z_-]{16,32}\\.[0-9A-Za-z_-]{16,64})\n filter_type: TokenPattern\n required_substrings:\n - SG.\n min_line_len: 34\n target:\n - code\n - doc\n\n- name: Shopify Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pshp(at|ca|pa|ss|tka)_[0-9A-Fa-f]{32})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - shp\n min_line_len: 38\n target:\n - code\n - doc\n\n- name: Slack Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P(xapp|xox[a-z])\\-[0-9A-Za-z-]{10,250})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - xox\n - xapp\n min_line_len: 15\n target:\n - code\n - doc\n\n- name: Slack Webhook\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?Phooks\\.slack\\.com/services)(?P/T[0-9A-Z]{8,16}/B[0-9A-Z]{8,16}/[0-9A-Za-z_]{24})\n filter_type: GeneralPattern\n required_substrings:\n - hooks.slack.com/services/T\n min_line_len: 61\n target:\n - code\n - doc\n\n- name: Stripe Credentials\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P(whsec|[prs]k_(test|live))_[0-9A-Za-z]{24,160})\n filter_type: GeneralPattern\n required_substrings:\n - k_live_\n - k_test_\n - whsec_\n min_line_len: 32\n target:\n - code\n - doc\n\n- name: Square Access Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PEAAA[0-9A-Za-z_-]{60})(?![0-9A-Za-z_-])\n filter_type:\n - ValuePatternCheck\n - ValueBase64PartCheck\n required_substrings:\n - EAAA\n min_line_len: 64\n target:\n - code\n - doc\n\n- name: Square Credentials\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Psq0[a-z]{3}-[0-9A-Za-z_-]{22}([0-9A-Za-z_-]{21})?)(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - sq0\n min_line_len: 29\n target:\n - code\n - doc\n\n- name: Twilio Credentials\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P(AC|AD|AL|CA|CF|CL|CN|CR|FW|IP|KS|MM|NO|PK|PN|QU|RE|SC|SD|SK|SM|TR|UT|XE|XR)[0-9A-Fa-f]{32})(?![0-9A-Za-z_+-])\n filter_type: TokenPattern\n required_substrings:\n - AC\n - AD\n - AL\n - CA\n - CF\n - CL\n - CN\n - CR\n - FW\n - IP\n - KS\n - MM\n - \"NO\"\n - PK\n - PN\n - QU\n - RE\n - SC\n - SD\n - SK\n - SM\n - TR\n - UT\n - XE\n - XR\n min_line_len: 34\n target:\n - code\n - doc\n\n- name: Telegram Bot API Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9]{8,10}:[0-9A-Za-z_-]{35})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n required_substrings:\n - :AA\n min_line_len: 45\n target:\n - code\n - doc\n\n- name: PyPi API Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Ppypi-[0-9A-Za-z_-]{150,255})\n filter_type: TokenPattern\n required_substrings:\n - pypi-\n min_line_len: 155\n target:\n - code\n - doc\n\n- name: NPM Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pnpm_[0-9A-Za-z_-]{36,255})\n filter_type:\n - ValueGitHubCheck\n required_substrings:\n - npm_\n min_line_len: 40\n target:\n - code\n - doc\n\n- name: Github Classic Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pgh[pousr]_[0-9A-Za-z_-]{36,255})\n filter_type:\n - ValueGitHubCheck\n required_substrings:\n - ghp_\n - gho_\n - ghu_\n - ghs_\n - ghr_\n min_line_len: 40\n target:\n - code\n - doc\n\n- name: Github Fine-granted Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pgithub_pat_[0-9A-Za-z_]{80,255})\n filter_type: GeneralPattern\n required_substrings:\n - github_pat_\n min_line_len: 90\n target:\n - code\n - doc\n\n- name: Firebase Domain\n severity: info\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[a-z0-9.-]{1,80}\\.firebaseio\\.com|[a-z0-9.-]{1,80}\\.firebaseapp\\.com)\n filter_type: GeneralPattern\n required_substrings:\n - .firebase\n min_line_len: 16\n target:\n - code\n - doc\n\n- name: AWS S3 Bucket\n severity: info\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[a-z0-9.-]{3,63}\\.s3\\.amazonaws\\.com|[a-z0-9.-]{3,63}\\.s3-website[.-](eu|ap|us|ca|sa|cn))\n filter_type: GeneralPattern\n required_substrings:\n - .s3-website\n - .s3.amazonaws.com\n min_line_len: 14\n target:\n - code\n - doc\n\n- name: Jfrog Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P(cmVmdGtuO[0-9A-Za-z_-]{55}|AKCp[0-9A-Za-z_-]{69}))(?![0-9A-Za-z_-])\n filter_type:\n - ValueJfrogTokenCheck\n required_substrings:\n - cmVmdGtuO\n - AKCp\n min_line_len: 64\n target:\n - code\n - doc\n\n- name: Azure Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PeyJ[=0-9A-Za-z_-]{50,500}\\.eyJ[=0-9A-Za-z_-]{8,8000}\\.[=0-9A-Za-z_-]{18,800})\n filter_type:\n - ValueAzureTokenCheck\n required_substrings:\n - eyJ\n min_line_len: 148\n target:\n - code\n - doc\n\n- name: Azure Secret Value\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9A-Za-z_~.-]{3}8Q~[0-9A-Za-z_~.-]{34})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n min_line_len: 40\n required_substrings:\n - 8Q~\n target:\n - code\n - doc\n\n- name: Azure Storage Account Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[0-9A-Za-z]{52}JQQJ9[9DH][0-9A-Za-z]{26}([0-9A-Za-z=]{4})?)(?![0-9A-Za-z_/+-])\n min_line_len: 80\n filter_type:\n - ValuePatternCheck(17)\n required_substrings:\n - JQQJ99\n - JQQJ9D\n - JQQJ9H\n target:\n - code\n - doc\n\n- name: Bitbucket App Password\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PATBB[0-9A-Za-z]{24}[A-F0-9]{8})(?![0-9A-Za-z_])\n filter_type:\n - ValueAtlassianTokenCheck\n min_line_len: 28\n required_substrings:\n - ATBB\n target:\n - code\n - doc\n\n- name: Bitbucket Repository Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PATCTT3xFfGN0[0-9A-Za-z_-]{80,800}(\\\\?=|%3[dD])[A-F0-9]{8})\n filter_type:\n - ValueAtlassianTokenCheck\n min_line_len: 160\n required_substrings:\n - ATCTT3xFfGN0\n target:\n - code\n - doc\n\n- name: Bitbucket HTTP Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PBBDC-[MNO][ADQTgjwz][AEIMQUYcgk][012345wxyz][0-9A-Za-z_-]{40})\n filter_type:\n - ValueAtlassianTokenCheck\n min_line_len: 49\n required_substrings:\n - BBDC-\n target:\n - code\n - doc\n\n- name: Jira / Confluence PAT token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?[MNO][ADQTgjwz][AEIMQUYcgk][012345wxyz][0-9A-Za-z_-]{40})(?![0-9A-Za-z_-])\n filter_type:\n - ValueAtlassianTokenCheck\n min_line_len: 44\n required_substrings:\n - M\n - N\n - O\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: Atlassian PAT token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PATATT3xFfGF0[0-9A-Za-z_-]{80,800}(\\\\?=|%3[dD])[A-F0-9]{8})\n filter_type:\n - ValueAtlassianTokenCheck\n min_line_len: 160\n required_substrings:\n - ATATT3xFfGF0\n target:\n - code\n - doc\n\n- name: Digital Ocean Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pdo[opr]_v1_[a-f0-9]{64})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n min_line_len: 71\n required_substrings:\n - doo_v1_\n - dop_v1_\n - dor_v1_\n target:\n - code\n - doc\n\n- name: Dropbox OAuth2 API Access Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Psl\\.(u\\.)?[0-9A-Za-z_-]{77,177})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n min_line_len: 80\n required_substrings:\n - sl.\n target:\n - code\n - doc\n\n- name: NuGet API key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Poy2[a-z0-9]{43})(?![0-9A-Za-z_-])\n filter_type: TokenPattern\n min_line_len: 46\n required_substrings:\n - oy2\n target:\n - code\n - doc\n\n- name: Gitlab Prefix Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P(_gitlab_session=|GR1348941|gl(agent|soat|ffct|p[at]t|oas|cbt|imt|rtr|[dfrw]t)-)[0-9A-Za-z_-]{20,64}(\\.[0-9A-Za-z_-]{2,16}){0,2})(?![0-9A-Za-z_-])\n filter_type:\n - ValuePatternCheck\n min_line_len: 25\n required_substrings:\n - _gitlab_session=\n - GR1348941\n - glagent-\n - glsoat-\n - glffct-\n - glpat-\n - gloas-\n - glptt-\n - glcbt-\n - glimt-\n - gldt-\n - glft-\n - glrt-\n - glrtr-\n - glwt-\n target:\n - code\n - doc\n\n- name: Grafana Provisioned API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PeyJ[=0-9A-Za-z_-]{64,360})(?![=0-9A-Za-z_-])\n filter_type:\n - ValueGrafanaCheck\n min_line_len: 67\n required_substrings:\n - eyJ\n target:\n - code\n - doc\n\n- name: Grafana Access Policy Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pglc_eyJ[0-9A-Za-z_-]{80,360})(?![0-9A-Za-z_-])\n filter_type:\n - ValueGrafanaCheck\n min_line_len: 87\n required_substrings:\n - glc_eyJ\n target:\n - code\n - doc\n\n- name: Grafana Service Account Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pglsa_[0-9A-Za-z_-]{32}_[0-9A-Fa-f]{8})\n min_line_len: 46\n filter_type:\n - ValueGrafanaServiceCheck\n required_substrings:\n - glsa_\n target:\n - code\n - doc\n\n- name: Dropbox API secret (long term)\n severity: high\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?=[0-9A-Za-z]{64})(?P[0-9A-Za-z]{10,12}[B-Za-z0-9]A{10,12}[B-Za-z0-9][0-9A-Za-z]{40,44})(?![=0-9A-Za-z_/+-])\n filter_type: [ ]\n min_line_len: 43\n required_substrings:\n - AAAAAAAAAA\n target:\n - code\n - doc\n\n- name: Dropbox App secret\n severity: info\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P[a-z0-9]{15})(?![=0-9A-Za-z_/+-])\n filter_type: WeirdBase36Token\n min_line_len: 15\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: Hashicorp Vault Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Phv[brs]\\.[0-9A-Za-z_-]{80,160})\n filter_type:\n - ValuePatternCheck\n - ValueEntropyBase64Check\n min_line_len: 90\n required_substrings:\n - hvb.\n - hvr.\n - hvs.\n target:\n - code\n - doc\n\n- name: Hashicorp Terraform Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P[0-9A-Za-z_-]{14}\\.atlasv1\\.[0-9A-Za-z_-]{67})(?![0-9A-Za-z_-])\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n min_line_len: 90\n required_substrings:\n - .atlasv1.\n target:\n - code\n - doc\n\n- name: NKEY Seed\n severity: high\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?PS[ACNOPUX][A-Z2-7]{40,200})(?![=0-9A-Za-z_+-])\n min_line_len: 42\n filter_type:\n - ValueMorphemesCheck\n - ValuePatternCheck\n - ValueEntropyBase32Check\n - ValueBase32DataCheck\n - ValueTokenBase32Check\n required_substrings:\n - SA\n - SC\n - SN\n - SO\n - SP\n - SU\n - SX\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: OTP / 2FA Secret\n severity: info\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P([A-Z2-7]{16}){1,2})(?![=0-9A-Za-z_+-])\n filter_type:\n - ValueMorphemesCheck\n - ValuePatternCheck\n - ValueEntropyBase32Check\n - ValueBase32DataCheck\n - ValueTokenBase32Check\n - ValueBase64PartCheck\n min_line_len: 16\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: OpenAI Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Psk-[0-9A-Za-z_-]{16,160}(T3BlbkFJ|9wZW5BS|PcGVuQU)[0-9A-Za-z_-]{16,160})\n min_line_len: 51\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n required_substrings:\n - T3BlbkFJ\n - 9wZW5BS\n - PcGVuQU\n target:\n - code\n - doc\n\n- name: Docker Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pdckr_[op]at_[0-9A-Za-z_-]{27,32})\n min_line_len: 36\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n required_substrings:\n - dckr_pat_\n - dckr_oat_\n target:\n - code\n - doc\n\n- name: Docker Swarm Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PSWMTKN-1-[0-9a-z]{50}-[0-9a-z]{25})\n min_line_len: 85\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n required_substrings:\n - SWMTKN-1-\n target:\n - code\n - doc\n\n- name: Docker Swarm Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?PSWMKEY-1-[0-9A-Za-z]{43})\n min_line_len: 52\n filter_type:\n - ValuePatternCheck\n - ValueMorphemesCheck\n required_substrings:\n - SWMKEY-1-\n target:\n - code\n - doc\n\n- name: Groq API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pgsk_[0-9A-Za-z_-]{8,40}(WGdyb3FY|hncm9xW|YZ3JvcV)[0-9A-Za-z_-]{8,40})(?![0-9A-Za-z_-])\n min_line_len: 56\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - WGdyb3FY\n - hncm9xW\n - YZ3JvcV\n target:\n - code\n - doc\n\n- name: X AI API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pxai-[0-9A-Za-z_-]{80})(?![0-9A-Za-z_-])\n min_line_len: 84\n filter_type:\n - ValuePatternCheck\n - ValueEntropyBase64Check\n required_substrings:\n - xai-\n target:\n - code\n - doc\n\n- name: Notion Integration Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pntn_[0-9]{9}[0-9A-Za-z_-]{36,255})\n filter_type:\n - ValuePatternCheck\n - ValueEntropyBase64Check\n required_substrings:\n - ntn_\n min_line_len: 50\n target:\n - code\n - doc\n\n- name: Hugging Face User Access Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Phf_[0-9A-Za-z_-]{34})(?![0-9A-Za-z_-])\n min_line_len: 37\n filter_type:\n - ValuePatternCheck\n - ValueEntropyBase64Check\n required_substrings:\n - hf_\n target:\n - code\n - doc\n\n- name: Anthropic API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Psk-ant-api03-[0-9A-Za-z_-]{64,128})(?![0-9A-Za-z_-])\n min_line_len: 77\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - sk-ant-api03-\n target:\n - code\n - doc\n\n- name: Perplexity API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Ppplx-[0-9A-Za-z_-]{40,64})(?![0-9A-Za-z_-])\n min_line_len: 45\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - pplx-\n target:\n - code\n - doc\n\n- name: DeepSeek API Key\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Psk-[0-9a-f]{32,64})(?![0-9A-Za-z_-])\n min_line_len: 35\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - sk-\n target:\n - code\n - doc\n\n- name: Tavily API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Ptvly-[0-9A-Za-z_-]{32,40})(?![0-9A-Za-z_-])\n min_line_len: 37\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - tvly-\n target:\n - code\n - doc\n\n- name: Figma Personal Access Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pfigd_[0-9A-Za-z_-]{40})(?![0-9A-Za-z_-])\n min_line_len: 45\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - figd_\n target:\n - code\n - doc\n\n- name: 1Password Account Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pops_eyJ[0-9A-Za-z_-]{168,8000})\n min_line_len: 192\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - InNlY3JldEtleSI6\n - JzZWNyZXRLZXkiO\n - ic2VjcmV0S2V5Ij\n target:\n - code\n - doc\n\n- name: Brevo API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Pxkeysib-[0-9a-f]{64}-[0-9A-Za-z_-]{16})\n min_line_len: 89\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - xkeysib-\n target:\n - code\n - doc\n\n- name: Together AI API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Ptgp_v1_[0-9A-Za-z_-]{43})\n min_line_len: 50\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - tgp_v1_\n target:\n - code\n - doc\n\n- name: LLAMA API Key\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pllx-[0-9A-Za-z_-]{48})\n min_line_len: 52\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - llx-\n target:\n - code\n - doc\n\n- name: SonarQube Credentials\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?Psq[apu]_[0-9a-f]{40})(?![0-9A-Za-z_-])\n min_line_len: 44\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - sqa_\n - sqp_\n - squ_\n target:\n - code\n - doc\n\n- name: Sentry Organization Auth Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Psntrys_eyJ[0-9A-Za-z_-]{80,8000}=*([0-9A-Za-z_-]{32,256})?)(?![0-9A-Za-z_-])\n min_line_len: 37\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - sntrys_eyJ\n target:\n - code\n - doc\n\n- name: Sentry User Auth Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?Psntryu_[0-9a-f]{64})(?![0-9A-Za-z_-])\n min_line_len: 37\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - sntryu_\n target:\n - code\n - doc\n\n- name: Discord Bot Token\n severity: high\n confidence: strong\n type: pattern\n values:\n - (?P[MNO][ADQTgjwz][AEIMQUYcgk][012345wxyz][0-9A-Za-z_-]{20,24}\\.[0-9A-Za-z_-]{6}\\.[0-9A-Za-z_-]{30,40})(?![0-9A-Za-z_-])\n min_line_len: 62\n filter_type:\n - ValueDiscordBotCheck\n required_substrings:\n - M\n - N\n - O\n required_regex: \"[0-9A-Za-z_/+-]{15}\"\n target:\n - code\n - doc\n\n- name: Discord Webhook\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?Pdiscord(?:app)?\\.com/api/webhooks)(?P/[0-9]{16,22}/[0-9A-Za-z_-]{40,100})\n filter_type:\n - ValueMorphemesCheck\n required_substrings:\n - discordapp.com/api/webhooks\n - discord.com/api/webhooks\n min_line_len: 61\n target:\n - code\n - doc\n\n- name: Vercel Token\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pvcp_[0-9A-Za-z]{56})(?![0-9A-Za-z_-])\n min_line_len: 60\n filter_type: TokenPattern\n required_substrings:\n - vcp_\n target:\n - code\n - doc\n\n- name: Netlify Token\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pnfp_[0-9A-Za-z]{36})(?![0-9A-Za-z_-])\n min_line_len: 40\n filter_type: TokenPattern\n required_substrings:\n - nfp_\n target:\n - code\n - doc\n\n- name: PostHog Credentials\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pph[acrsx]_[0-9A-Za-z]{40,60})(?![0-9A-Za-z_-])\n min_line_len: 44\n filter_type: TokenPattern\n required_substrings:\n - phx_\n - phs_\n - phr_\n - pha_\n - phc_\n target:\n - code\n - doc\n\n- name: RubyGems API Key\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?Prubygems_[0-9a-f]{48})\n min_line_len: 57\n filter_type: TokenPattern\n required_substrings:\n - rubygems_\n target:\n - code\n - doc\n\n- name: Tencent WeChat API App ID\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?Pwx[0-9a-f]{16})(?![0-9A-Za-z_-])\n min_line_len: 18\n filter_type: TokenPattern\n required_substrings:\n - wx\n target:\n - code\n - doc\n\n- name: Salesforce Credentials\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (?:^|/|[^\\\\0-9A-Za-z+_-]|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P(3MVG[0-9A-Za-z_.]{24,200}|00D[0-9A-Za-z]{9,15}(![0-9A-Za-z_.]{24,200})?))(?![0-9A-Za-z_.])\n min_line_len: 12\n filter_type:\n - ValuePatternCheck(9)\n - ValueNumberCheck\n - ValueBase64PartCheck\n required_substrings:\n - 00D\n - 3MVG\n target:\n - code\n - doc\n\n- name: Postman Credentials\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P(PMAK-[0-9a-f]{24}-[0-9a-f]{34}|PMAT-[0-9A-Z]{26}))\n min_line_len: 29\n filter_type:\n - ValuePatternCheck\n required_substrings:\n - PMAK-\n - PMAT-\n target:\n - code\n - doc\n\n- name: NTLM Token\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?PTlRMTVNTUAADAAAA[=0-9A-Za-z_/+-]{8,8000})(?![0-9A-Za-z_/+-])\n filter_type:\n - ValueMorphemesCheck(2)\n - ValuePatternCheck\n min_line_len: 160\n required_substrings:\n - TlRMTVNTUAADAAAA\n target:\n - doc\n - code\n\n- name: Basic Authorization\n severity: medium\n confidence: strong\n type: pattern\n values:\n - (?P(?i:basic))(?P\\s+)(?P[=0-9A-Za-z_/+-]{8,8000})(?![0-9A-Za-z_/+-])\n min_line_len: 18\n filter_type:\n - ValueBasicAuthCheck\n required_substrings:\n - basic\n target:\n - code\n - doc\n\n- name: Bearer Authorization\n severity: medium\n confidence: moderate\n type: pattern\n values:\n - (?P(?i:bearer|ntlm))(?P\\s+)(?P[.0-9A-Za-z_/+-]{32,8000}=*)(?![0-9A-Za-z_/+-])\n min_line_len: 37\n filter_type: GeneralKeyword\n required_substrings:\n - bearer\n - ntlm\n target:\n - code\n - doc\n\n- name: SQL Password\n severity: medium\n confidence: weak\n type: pattern\n values:\n - (\\\\[nrt]|\\b)(?i:(?P(CREATE|ALTER|SET\\s{1,8}PASSWORD|INSERT(\\s{1,8}IGNORE)?|UPDATE\\s{1,8}[^\\s;]{1,80})\\s{1,8}(LOGIN|USER|ROLE|FOR|INTO|SET)\\s{1,8}((?!IDENTIFIED|PASSWORD)[^\\s;]{1,80}\\s{1,8}|VALUES\\s{0,8}\\(){1,8}(IDENTIFIED((\\s{1,8}WITH\\s{1,8}\\S{1,80})?\\s{1,8}(BY|AS))|(=|WITH)?\\s{0,8}PASSWORD\\b(\\s{0,8}=)?)))\\s{0,8}(?P[(]\\s{0,8})?(?P((?P\\\\{1,8})?([\\\"'`]|&(quot|apos|#3[49]);)){1,4})?(?P(?(value_leftquote)((?!(?P=value_leftquote))(?(esq)((?!(?P=esq)([\\\"'`]|&(quot|apos|#3[49]);)).)|((?!(?P=value_leftquote)).)))|(?!&(quot|apos|#3[49]);)(\\\\{1,8}([ tnr]|[^\\s\\\"'`])|[^\\s\\\"'`,;\\\\])){3,80})(?(value_leftquote)(?P(?curl)\\s.*(-[uU]|--(proxy-)?user)\\s\\s*(?P(\\\\*[\\\"']){1,3})?(?(value_leftquote)[^\\\"'\\\\:]|[^\\s\\\"'\\\\:]){0,64}:(?P(?(value_leftquote)[^\\\"'\\\\]|[^\\s\\\"'\\\\]){4,64})(?(value_leftquote)(?P(\\\\?[\\\"']){1,3}))\n filter_type: GeneralKeyword\n use_ml: true\n required_substrings:\n - curl\n min_line_len: 16\n target:\n - doc\n - code\n\n- name: CMD ConvertTo-SecureString\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?PConvertTo-SecureString(\\s\\s*-(String|AsPlainText|Force))*)\\s\\s*(?P(\\\\?[\\\"']){1,3})?(?P(?(value_leftquote)[^\\\"'\\\\]|[^\\s\\\"'\\\\]){4,800})(?(value_leftquote)(?P(\\\\?[\\\"']){1,3}))\n filter_type: GeneralKeyword\n use_ml: true\n required_substrings:\n - convertto-securestring\n min_line_len: 27\n target:\n - doc\n - code\n\n- name: CMD Password\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (^|\\W|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P-[A-Za-z_-]*(?i:pass(in|out|word|phrase)))(\\s|\\\\?[\\\"'],)\\s*(?!-)(?P(\\\\?[\\\"']){1,3})?(pass:)?(?!file:|env:|fd:)(?P(?(value_leftquote)[^\\\"'\\\\]|[^\\s\\\"'\\\\]){4,80})(?(value_leftquote)(?P(\\\\?[\\\"']){1,3}))\n filter_type: GeneralKeyword\n use_ml: true\n required_substrings:\n - pass\n min_line_len: 12\n target:\n - doc\n - code\n\n- name: CMD Token\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (^|\\W|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P-[A-Za-z_-]*(?i:token|oauth2-bearer))(\\s|\\\\?[\\\"'],)\\s*(?!-)(?P(\\\\?[\\\"']){1,3})?(?P(?(value_leftquote)[^\\\"'\\\\]|[^\\s\\\"'\\\\]){4,4000})(?(value_leftquote)(?P(\\\\?[\\\"']){1,3}))\n filter_type: GeneralKeyword\n use_ml: true\n required_substrings:\n - token\n - oauth2-bearer\n min_line_len: 12\n target:\n - doc\n - code\n\n- name: CMD Secret\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (^|\\W|\\\\[0abfnrtv]|(?:%|\\\\x)[0-9A-Fa-f]{2}|\\\\[0-7]{3}|\\\\[Uu][0-9A-Fa-f]{4}|\\x1B\\[[0-9;]{0,80}m)(?P-[A-Za-z_-]*(?i:secret)[A-Za-z_-]*)(\\s|\\\\?[\\\"'],)\\s*(?!-)(?P(\\\\?[\\\"']){1,3})?(pass:)?(?!file:|env:|fd:)(?P(?(value_leftquote)[^\\\"'\\\\]|[^\\s\\\"'\\\\]){4,4000})(?(value_leftquote)(?P(\\\\?[\\\"']){1,3}))\n filter_type: GeneralKeyword\n use_ml: true\n required_substrings:\n - secret\n min_line_len: 12\n target:\n - doc\n - code\n\n- name: URL Credentials\n severity: high\n confidence: moderate\n type: pattern\n values:\n - (?P[\\\"'])?(?P[+0-9A-Za-z-]{2,80}://)([^\\s\\'\"<>\\[\\]^~`{|}:/]{0,80}:){1,3}(?P[^\\s\\'\"<>\\[\\]^~`{|}@:/]{3,80})@[^\\s\\'\"<>\\[\\]^~`{|}@:/]{1,800}\\\\{0,8}(?P[\\\"'])?\n filter_type: UrlCredentialsGroup\n use_ml: true\n required_substrings:\n - ://\n min_line_len: 10\n target:\n - doc\n - code\n\n- name: API\n severity: low\n confidence: moderate\n type: keyword\n values:\n - api(?!tal)\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 11\n required_substrings:\n - api\n target:\n - code\n\n- name: Auth\n severity: medium\n confidence: moderate\n type: keyword\n values:\n - auth(?!ors?(?!i[tz]))\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 12\n required_substrings:\n - auth\n target:\n - code\n\n- name: Credential\n severity: medium\n confidence: moderate\n type: keyword\n values:\n - credential\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 18\n required_substrings:\n - credential\n target:\n - code\n\n- name: Key\n severity: high\n confidence: moderate\n type: keyword\n values:\n - key(?!word|board|pad|name)\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 11\n required_substrings:\n - key\n target:\n - code\n\n- name: Nonce\n severity: low\n confidence: moderate\n type: keyword\n values:\n - (? None:\n self.config = config\n self._verify_rule_config(rule_dict)\n # mandatory fields\n self.__rule_name = str(rule_dict[Rule.NAME])\n if severity := Severity.get(rule_dict[Rule.SEVERITY]):\n self.__severity = severity\n else:\n self._malformed_rule_error(rule_dict, Rule.SEVERITY)\n if confidence := Confidence.get(rule_dict[Rule.CONFIDENCE]):\n self.__confidence = confidence\n else:\n self._malformed_rule_error(rule_dict, Rule.CONFIDENCE)\n if rule_type := getattr(RuleType, str(rule_dict[Rule.TYPE]).upper(), None):\n self.__rule_type: RuleType = rule_type\n else:\n self._malformed_rule_error(rule_dict, Rule.TYPE)\n self.__patterns = self._init_patterns(rule_dict[Rule.VALUES])\n self.__target: List[str] = rule_dict.get(Rule.TARGET, [])\n if not self.__target or set(self.__target).difference({\"code\", \"doc\"}):\n self._malformed_rule_error(rule_dict, Rule.TARGET)\n # auxiliary fields\n self.__filters = self._init_filters(rule_dict.get(Rule.FILTER_TYPE, []))\n self.__use_ml = bool(rule_dict.get(Rule.USE_ML))\n self.__required_substrings = set(i.strip().lower() for i in rule_dict.get(Rule.REQUIRED_SUBSTRINGS, []))\n self.__has_required_substrings = bool(self.__required_substrings)\n required_regex = rule_dict.get(Rule.REQUIRED_REGEX)\n if required_regex and not isinstance(required_regex, str):\n self._malformed_rule_error(rule_dict, Rule.REQUIRED_REGEX)\n self.__required_regex = re.compile(required_regex) if required_regex else None\n self.__min_line_len = int(rule_dict.get(Rule.MIN_LINE_LEN, MAX_LINE_LENGTH))\n\n def _malformed_rule_error(self, rule_dict: Dict, field: str):\n raise ValueError(f\"Malformed rule '{self.__rule_name}'.\"\n f\" field '{field}' has invalid value\"\n f\" '{rule_dict.get(field)}'\")\n\n @cached_property\n def rule_name(self) -> str:\n \"\"\"rule_name getter\"\"\"\n return self.__rule_name\n\n @cached_property\n def rule_type(self) -> RuleType:\n \"\"\"rule_type getter\"\"\"\n return self.__rule_type\n\n @cached_property\n def severity(self) -> Severity:\n \"\"\"severity getter\"\"\"\n return self.__severity\n\n @cached_property\n def confidence(self) -> Confidence:\n \"\"\"confidence getter\"\"\"\n return self.__confidence\n\n @cached_property\n def filters(self) -> List[Filter]:\n \"\"\"filters getter\"\"\"\n return self.__filters\n\n @staticmethod\n def _get_arg(arg: str) -> Union[int, float, str]:\n \"\"\"Transform given string value to int, then float. In worst case - returns str\"\"\"\n with contextlib.suppress(Exception):\n return int(arg)\n with contextlib.suppress(Exception):\n return float(arg)\n return str(arg)\n\n def _init_filters(self, filter_type: Union[None, str, List[str]]) -> List[Filter]:\n \"\"\"\n filter_type: str - applies Group of filter\n list - creates specific set of Filters\n \"\"\"\n _filters: List[Filter] = []\n if isinstance(filter_type, str):\n # when string passed - (Group) of filters is applied\n filter_group = getattr(group, filter_type, None)\n if isinstance(filter_group, type) and issubclass(filter_group, Group):\n return filter_group(self.config).filters # type: ignore\n elif isinstance(filter_type, list):\n # list type means - list of (Filter)s is applied\n for i in filter_type:\n if '(' in i and ')' in i:\n left_pos = i.find('(')\n filter_parameters = [self._get_arg(x.strip()) for x in i[left_pos + 1:i.find(')')].split(',')]\n filter_name = i[:left_pos].strip()\n else:\n filter_parameters = None\n filter_name = i\n _filter = getattr(filters, filter_name, None)\n if isinstance(_filter, type) and issubclass(_filter, Filter):\n if filter_parameters:\n _filters.append(_filter(self.config, *filter_parameters))\n else:\n _filters.append(_filter(self.config))\n else:\n break\n else:\n return _filters\n raise ValueError(f\"Malformed rule '{self.__rule_name}'.\"\n f\" field '{Rule.FILTER_TYPE}' has invalid value\"\n f\" '{filter_type}'\")\n\n def _init_patterns(self, _values: List[str]) -> List[re.Pattern]:\n \"\"\"Get pattern values for rule object.\n\n Set the pattern value attribute of the rule object based on the passed values.\n So, if the received rule type corresponds to the RuleType.KEYWORD type,\n the \"patterns\" attribute is assigned the value of template keyword regex\n with the corresponding value. Otherwise, if the received rule type corresponds\n to the RuleType.PATTERN, RuleType.MULTI or RuleType.PEM_KEY types, the \"patterns\" attribute is\n assigned the compile regex ov received value\n\n Args:\n _values: regular expressions\n\n \"\"\"\n _patterns: List[re.Pattern] = []\n if RuleType.KEYWORD == self.rule_type and 0 < len(_values):\n for value in _values:\n _pattern = KeywordPattern.get_keyword_pattern(value)\n _patterns.append(_pattern)\n elif RuleType.MULTI == self.rule_type and 2 == len(_values) \\\n or self.rule_type in (RuleType.PATTERN, RuleType.PEM_KEY) and 0 < len(_values):\n for value in _values:\n _patterns.append(re.compile(value))\n if RuleType.PEM_KEY == self.rule_type and 1 < len(_values):\n logger.warning(\"Rule %s has extra patterns. Only single pattern supported.\", self.rule_name)\n elif RuleType.MULTI == self.rule_type and 2 < len(_values):\n logger.warning(\"Rule %s has extra patterns. Only two patterns supported.\", self.rule_name)\n else:\n raise ValueError(f\"Malformed rule config file. Rule '{self.rule_name}' type '{self.rule_type}' is invalid.\")\n return _patterns\n\n @cached_property\n def patterns(self) -> List[re.Pattern]:\n \"\"\"patterns getter\"\"\"\n return self.__patterns\n\n @cached_property\n def use_ml(self) -> bool:\n \"\"\"use_ml getter\"\"\"\n return self.__use_ml\n\n @staticmethod\n def _verify_rule_config(rule_config: Dict) -> None:\n \"\"\"Checks all mandatory fields and wrong names\n\n Args:\n rule_config: dictionary loaded from the config file\n\n Raises:\n ValueError if missing fields is present\n\n \"\"\"\n if missing_fields := Rule.mandatory_fields.difference(rule_config.keys()):\n raise ValueError(f\"Malformed rule config file. Contain rule with missing fields: {missing_fields}.\")\n if extra_fields := set(rule_config.keys()).difference(Rule.all_fields):\n raise ValueError(f\"Malformed rule config file. Extra fields: {extra_fields}.\")\n\n @cached_property\n def required_substrings(self) -> Set[str]:\n \"\"\"required_substrings getter\"\"\"\n return self.__required_substrings\n\n @cached_property\n def has_required_substrings(self) -> bool:\n \"\"\"has_required_substrings getter for speedup\"\"\"\n return self.__has_required_substrings\n\n @cached_property\n def required_regex(self) -> Optional[re.Pattern]:\n \"\"\"required_regex getter\"\"\"\n return self.__required_regex\n\n @cached_property\n def min_line_len(self) -> int:\n \"\"\"min_line_len getter\"\"\"\n return self.__min_line_len\n\n @cached_property\n def target(self) -> List[str]:\n \"\"\"target getter\"\"\"\n return self.__target\n" }, { "path": "credsweeper/scanner/__init__.py", "content": "" }, { "path": "credsweeper/scanner/scan_type/__init__.py", "content": "" }, { "path": "credsweeper/scanner/scan_type/multi_pattern.py", "content": "import copy\nimport re\nfrom typing import List\n\nfrom credsweeper.common.constants import RuleType, MAX_LINE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters import ValueSearchCheck\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scan_type.scan_type import ScanType\n\n\nclass MultiPattern(ScanType):\n \"\"\"Check if line is a part of a multi-line credential and second part is present within MAX_SEARCH_MARGIN lines.\n\n Parameters:\n MAX_SEARCH_MARGIN: Int constant. Number of lines around current to perform search for the second part\n\n \"\"\"\n\n MAX_SEARCH_MARGIN = 10\n\n @classmethod\n def run(cls, config: Config, rule: Rule, target: AnalysisTarget) -> List[Candidate]:\n \"\"\"Check if multiline credential present if the file within MAX_SEARCH_MARGIN range from current line_num.\n\n Args:\n config: user configs\n rule: Rule object to check current line. Should be a multi-pattern rule\n target: Analysis target\n\n Return:\n List of Candidates if pattern defined in a rule is present in a line\n and second part of multi-pattern rule is present within MAX_SEARCH_MARGIN from the line.\n Empty list (False) - otherwise.\n\n \"\"\"\n if RuleType.MULTI != rule.rule_type:\n raise ValueError(f\"Rule `{rule}` provided to `{cls.__name__}`.run \"\n f\"should have pattern_type equal to `{RuleType.MULTI.value}`\")\n\n candidates = cls._get_candidates(config, rule, target)\n\n for candidate in candidates:\n # use additional filter to skip the value in first line_data and continues scan\n filters = copy.deepcopy(rule.filters)\n filters.append(ValueSearchCheck(config, candidate.line_data_list[0].value))\n for line_pos in cls.get_line_positions(candidate.line_data_list[0].line_pos, target):\n if cls._scan(config, candidate, line_pos, target, rule.patterns[1], filters):\n break\n\n # return candidates with multi line_data_list only\n return [x for x in candidates if 1 < len(x.line_data_list)]\n\n @classmethod\n def get_line_positions(cls, line_pos: int, target: AnalysisTarget) -> List[int]:\n \"\"\"Returns list of line positions to be scanned for second part of multi-pattern rule in a priority order.\"\"\"\n if 0 <= line_pos < target.lines_len:\n # the same line is first\n priority_positions = [(0, line_pos)]\n else:\n return []\n # margin order is constant at start\n priority_forward = priority_backward = cls.MAX_SEARCH_MARGIN\n # backward lines are second priority\n priority_backward += cls.MAX_SEARCH_MARGIN\n line_pos_margin = 1\n while line_pos_margin <= cls.MAX_SEARCH_MARGIN:\n # forward\n line_pos_forward = line_pos + line_pos_margin\n if 0 <= line_pos_forward < target.lines_len:\n if forward_curled_diff := target.lines[line_pos_forward].count('}', 0, MAX_LINE_LENGTH):\n forward_curled_diff -= target.lines[line_pos_forward].count('{', 0, MAX_LINE_LENGTH)\n if 0 < forward_curled_diff:\n priority_forward += cls.MAX_SEARCH_MARGIN * (1 + forward_curled_diff)\n else:\n priority_forward += cls.MAX_SEARCH_MARGIN\n priority_positions.append((priority_forward, line_pos_forward))\n # backward\n line_pos_backward = line_pos - line_pos_margin\n if 0 <= line_pos_backward < target.lines_len:\n if backward_curled_diff := target.lines[line_pos_backward].count('{', 0, MAX_LINE_LENGTH):\n backward_curled_diff -= target.lines[line_pos_backward].count('}', 0, MAX_LINE_LENGTH)\n if 0 < backward_curled_diff:\n priority_backward += cls.MAX_SEARCH_MARGIN * (1 + backward_curled_diff)\n else:\n priority_backward += cls.MAX_SEARCH_MARGIN\n priority_positions.append((priority_backward, line_pos_backward))\n # increment the margin for next index\n line_pos_margin += 1\n # first item is priority, second - line_pos\n priority_positions.sort()\n return [x for _, x in priority_positions]\n\n @classmethod\n def _scan(cls, config: Config, candidate: Candidate, candi_line_pos: int, target: AnalysisTarget,\n pattern: re.Pattern, filters: List[Filter]) -> bool:\n \"\"\"Search for second pattern in multi-pattern rule.\n\n Automatically update candidate with detected line if any.\n\n Args:\n config: dict, scanner configuration\n candidate: Current credential candidate detected in the line\n candi_line_pos: line position of lines around candidate to perform search\n target: Analysis target\n pattern: second pattern in a rule\n filters: filters to be applied on candidate\n\n Return:\n Boolean. True if second part detected. False otherwise\n\n \"\"\"\n new_target = AnalysisTarget(candi_line_pos, target.lines, target.line_nums, target.descriptor)\n\n line_data_list = cls.get_line_data_list(config=config, target=new_target, pattern=pattern, filters=filters)\n\n if not line_data_list:\n return False\n candidate.line_data_list.extend(line_data_list)\n return True\n" }, { "path": "credsweeper/scanner/scan_type/pem_key_pattern.py", "content": "import logging\nfrom typing import List\n\nfrom credsweeper.common.constants import RuleType\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scan_type.scan_type import ScanType\nfrom credsweeper.utils.pem_key_detector import PemKeyDetector\n\nlogger = logging.getLogger(__name__)\n\n\nclass PemKeyPattern(ScanType):\n \"\"\"Scanner detects single PEM private key in target from current line\"\"\"\n\n @classmethod\n def run(cls, config: Config, rule: Rule, target: AnalysisTarget) -> List[Candidate]:\n \"\"\"Check if target is a PEM key\n\n Args:\n config: user configs\n rule: Rule object to check current line. Should be a pem-pattern rule\n target: Analysis target\n\n Return:\n List of Candidate objects if pattern defined in a rule is present in a line\n and filters defined in rule do not remove current line. Empty list - otherwise\n\n \"\"\"\n if RuleType.PEM_KEY != rule.rule_type:\n raise ValueError(f\"Rule `{rule}` provided to `{cls.__name__}`.run \"\n f\"should have pattern_type equal to `{RuleType.PEM_KEY.value}`\")\n for candidate in cls._get_candidates(config, rule, target):\n if pem_lines := PemKeyDetector(config).detect_pem_key(candidate.line_data_list[0], target):\n candidate.line_data_list = pem_lines\n return [candidate]\n\n return []\n" }, { "path": "credsweeper/scanner/scan_type/scan_type.py", "content": "import logging\nimport re\nfrom abc import ABC, abstractmethod\nfrom typing import List\n\nfrom credsweeper.common.constants import RuleType, MIN_DATA_LEN\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate, LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.filter import Filter\nfrom credsweeper.rules.rule import Rule\n\nlogger = logging.getLogger(__name__)\n\n\nclass ScanType(ABC):\n \"\"\"Base class for all Scanners.\n\n Scanner allow to check if regex pattern defined in a rule is present in a line.\n\n \"\"\"\n\n @classmethod\n @abstractmethod\n def run(cls, config: Config, rule: Rule, target: AnalysisTarget) -> List[Candidate]:\n \"\"\"Check if regex pattern defined in a rule is present in a line.\n\n Args:\n config: user configs\n rule: Rule object to check current line\n target: Analysis target\n\n Return:\n List of Candidate objects if pattern defined in a rule is present in a line\n and filters defined in rule do not remove current line. Empty list - otherwise\n\n \"\"\"\n raise NotImplementedError()\n\n @classmethod\n def filtering(cls, target: AnalysisTarget, line_data: LineData, filters: List[Filter]) -> bool:\n \"\"\"Check if line data should be removed based on filters.\n\n If `use_filters` option is false, always return False\n\n Args:\n target: AnalysisTarget from which `line_data` was obtained\n line_data: Line data to check with `filters`\n filters: Filters to use\n\n Return:\n boolean: True if line_data should be removed. False otherwise.\n If `use_filters` option is false, always return False\n\n \"\"\"\n if not line_data.value:\n logger.debug(\"Filtered line with empty value in file: %s:%d in line: %s value: '%s'\", line_data.path,\n line_data.line_num, line_data.line, line_data.value)\n return True\n for filter_ in filters:\n if filter_.run(line_data, target):\n logger.debug(\"Filtered line with filter: %s in file: %s:%d in line: %s value: %s\",\n filter_.__class__.__name__, line_data.path, line_data.line_num, line_data.line,\n line_data.value)\n return True\n return False\n\n @classmethod\n def get_line_data_list(\n cls, #\n config: Config, #\n target: AnalysisTarget, #\n pattern: re.Pattern, #\n filters: List[Filter]) -> List[LineData]:\n \"\"\"Check if regex pattern is present in line, and line should not be removed by filters.\n\n Args:\n config: dict of credsweeper configuration\n target: AnalysisTarget with all necessary data\n pattern: Compiled regex object to be searched in line\n filters: Filters to use\n\n Return:\n List of LineData objects if pattern a line and filters do not remove current line. Empty otherwise\n\n \"\"\"\n line_data_list: List[LineData] = []\n # start - end positions for continuously searching for overlapping pattern\n offsets = [(0, target.line_len)]\n\n while offsets:\n offset_start, offset_end = offsets.pop()\n bypass_start = bypass_end = None\n for _match in pattern.finditer(target.line, pos=offset_start, endpos=offset_end):\n\n logger.debug(\"Valid line for pattern: %s in file: %s:%d in line: %s\", pattern.pattern, target.file_path,\n target.line_num, target.line)\n line_data = LineData(config, target.line, target.line_pos, target.line_num, target.file_path,\n target.file_type, target.info, pattern, _match)\n if bypass_start and bypass_end:\n if 0 < line_data.variable_start:\n bypass_end = line_data.variable_start\n elif 0 < line_data.value_start:\n bypass_end = line_data.value_start\n if bypass_start < bypass_end and bypass_end - bypass_start > MIN_DATA_LEN:\n offsets.append((bypass_start, bypass_end))\n bypass_start = bypass_end = None\n elif MIN_DATA_LEN < line_data.value_end < _match.end() \\\n and MIN_DATA_LEN < _match.end() - line_data.value_end:\n # add bypass for valuable sanitized value\n bypass_start = line_data.value_end\n bypass_end = offset_end\n\n if config.use_filters and cls.filtering(target, line_data, filters):\n if line_data.variable and 0 <= line_data.variable_start < line_data.variable_end:\n # may be next matched item will be not filtered - let search it after variable\n bypass_start = line_data.variable_end\n bypass_end = offset_end\n elif line_data.value and 0 <= line_data.value_start < line_data.value_end:\n # may be next matched item will be not filtered - let search it after variable\n bypass_start = line_data.value_end\n bypass_end = offset_end\n continue\n\n if target.offset is not None:\n # the target line is a chunk of long line - offsets have to be corrected\n if 0 <= line_data.variable_start:\n line_data.variable_start += target.offset\n if 0 <= line_data.variable_end:\n line_data.variable_end += target.offset\n if 0 <= line_data.separator_start:\n line_data.separator_start += target.offset\n if 0 <= line_data.separator_end:\n line_data.separator_end += target.offset\n # value positions are mandatory\n line_data.value_start += target.offset\n line_data.value_end += target.offset\n # get the original line\n line_data.line = target.lines[target.line_pos]\n\n line_data_list.append(line_data)\n if bypass_start and bypass_end:\n offsets.append((bypass_start, bypass_end))\n\n return line_data_list\n\n @classmethod\n def _get_candidates(cls, config: Config, rule: Rule, target: AnalysisTarget) -> List[Candidate]:\n \"\"\"Returns Candidate objects list.\n\n Args:\n config: user configs\n rule: Rule object to check current line\n target: Target for analysis\n\n Return:\n List of Candidate objects if pattern defined in a rule is present in a line\n and filters defined in rule do not remove current line. Empty list - otherwise\n\n \"\"\"\n candidates: List[Candidate] = []\n if config.exclude_lines and target.line_strip in config.exclude_lines:\n return candidates\n\n if line_data_list := cls.get_line_data_list(config=config,\n target=target,\n pattern=rule.patterns[0],\n filters=rule.filters):\n for line_data in line_data_list:\n if config.exclude_values and line_data.value.strip() in config.exclude_values:\n continue\n candidate = Candidate(line_data_list=[line_data],\n patterns=rule.patterns,\n rule_name=rule.rule_name,\n severity=rule.severity,\n config=config,\n use_ml=rule.use_ml,\n confidence=rule.confidence)\n # single pattern with multiple values means all the patterns must matched in target\n if 1 < len(rule.patterns) and rule.rule_type in (RuleType.PATTERN, RuleType.KEYWORD):\n # additional check whether all patterns match\n if not cls._aux_scan(config, rule, target, candidate):\n # cannot find secondary values for the candidate\n continue\n candidates.append(candidate)\n return candidates\n\n @classmethod\n def _aux_scan(cls, config: Config, rule: Rule, target: AnalysisTarget, candidate: Candidate) -> bool:\n \"\"\"check for all secondary patterns\"\"\"\n for pattern in rule.patterns[1:]:\n line_data_list = cls.get_line_data_list(config=config, target=target, pattern=pattern, filters=rule.filters)\n pattern_matched = False\n\n for line_data in line_data_list:\n # standard filtering of values from config\n if config.exclude_values and line_data.value.strip() in config.exclude_values:\n continue\n candidate.line_data_list.append(line_data)\n pattern_matched = True\n if not pattern_matched:\n return False\n\n # all secondary patterns were matched and candidate is filled with the values\n return True\n" }, { "path": "credsweeper/scanner/scan_type/single_pattern.py", "content": "from typing import List\n\nfrom credsweeper.common.constants import RuleType\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scan_type.scan_type import ScanType\n\n\nclass SinglePattern(ScanType):\n \"\"\"Check if single line rule present in the line.\"\"\"\n\n @classmethod\n def run(cls, config: Config, rule: Rule, target: AnalysisTarget) -> List[Candidate]:\n \"\"\"Check if regex pattern defined in a rule is present in a line.\n\n Args:\n config: config object of user configs\n rule: Rule object to check current line\n target: Analysis target\n\n Return:\n List of Candidate objects if pattern defined in a rule is present in a line\n and filters defined in rule do not remove current line. Empty list - otherwise\n\n \"\"\"\n\n if RuleType.PATTERN != rule.rule_type and RuleType.KEYWORD != rule.rule_type:\n raise ValueError(f\"Rule `{rule}` provided to `{cls.__name__}`.run \"\n f\"should have pattern_type equal to `{RuleType.PATTERN.value}`\")\n\n return cls._get_candidates(config, rule, target)\n" }, { "path": "credsweeper/scanner/scanner.py", "content": "import logging\nimport re\nfrom pathlib import Path\nfrom typing import List, Type, Tuple, Union, Dict, Generator, Set\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.common.constants import RuleType, MIN_VARIABLE_LENGTH, MIN_SEPARATOR_LENGTH, MIN_VALUE_LENGTH, \\\n MAX_LINE_LENGTH, PEM_BEGIN_PATTERN\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.content_provider import ContentProvider\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scan_type.multi_pattern import MultiPattern\nfrom credsweeper.scanner.scan_type.pem_key_pattern import PemKeyPattern\nfrom credsweeper.scanner.scan_type.scan_type import ScanType\nfrom credsweeper.scanner.scan_type.single_pattern import SinglePattern\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\nRULES_PATH = APP_PATH / \"rules\" / \"config.yaml\"\n\n\nclass Scanner:\n \"\"\"Advanced Credential Scanner base class.\n\n Parameters:\n rules: list of rule objects to check\n min_pattern_len: minimal length specified in all pattern rules\n min_keyword_len: minimal possible length for a string to be matched by any keyword rule\n min_len: Smallest between min_pattern_len and min_keyword_len\n TargetGroup: Type for List[Tuple[AnalysisTarget, str, int]]\n\n \"\"\"\n\n TargetGroup = List[Tuple[AnalysisTarget, str, int]]\n\n def __init__(self, config: Config, rule_path: Union[None, str, Path]) -> None:\n self.config = config\n # init with MAX_LINE_LENGTH before _set_rules\n self.min_keyword_len = MAX_LINE_LENGTH\n self.min_pattern_len = MAX_LINE_LENGTH\n self.min_pem_key_len = MAX_LINE_LENGTH\n self.min_multi_len = MAX_LINE_LENGTH\n self.rules_scanners: List[Tuple[Rule, Type[ScanType]]] = []\n self._set_rules_scanners(rule_path)\n self.min_len = min(self.min_pattern_len, self.min_keyword_len, self.min_pem_key_len, self.min_multi_len,\n MIN_VARIABLE_LENGTH + MIN_SEPARATOR_LENGTH + MIN_VALUE_LENGTH)\n self.__keyword_rules_required_substrings = self._get_required_substrings(RuleType.KEYWORD)\n\n def keywords_required_substrings_check(self, text: str) -> bool:\n \"\"\"check whether `text` has any required substring for all keyword type rules\"\"\"\n return self._substring_check(self.__keyword_rules_required_substrings, text)\n\n def _get_required_substrings(self, rule_type: RuleType) -> Set[str]:\n \"\"\"init set of required substrings for custom rule type\"\"\"\n required_substrings: Set[str] = set()\n for rule in (x[0] for x in self.rules_scanners if rule_type == x[0].rule_type):\n required_substrings.update(set(rule.required_substrings))\n return required_substrings\n\n @staticmethod\n def _substring_check(substrings: Set[str], text: str) -> bool:\n \"\"\"checks whether `text` has any required substring. Set is used to reduce extra transformations\"\"\"\n for substring in substrings:\n if substring in text:\n return True\n return False\n\n def _set_rules_scanners(self, rules_path: Union[None, str, Path]) -> None:\n \"\"\"Auxiliary method to fill rules, determine min_pattern_len and set scanners\"\"\"\n if rules_path is None:\n rules_path = RULES_PATH\n rule_templates = Util.yaml_load(rules_path)\n if rule_templates and isinstance(rule_templates, list):\n rule_names = set()\n for rule_template in rule_templates:\n try:\n rule = Rule(self.config, rule_template)\n except Exception as exc:\n logger.error(\"Rule creation error%s\", str(rule_template))\n raise exc\n if not self._is_available(rule):\n continue\n if rule.rule_name in rule_names:\n raise RuntimeError(f\"Duplicated rule name {rule.rule_name}\")\n rule_names.add(rule.rule_name)\n if 0 < rule.min_line_len:\n if rule.rule_type == RuleType.KEYWORD:\n self.min_keyword_len = min(self.min_keyword_len, rule.min_line_len)\n elif rule.rule_type == RuleType.PATTERN:\n self.min_pattern_len = min(self.min_pattern_len, rule.min_line_len)\n elif rule.rule_type == RuleType.PEM_KEY:\n self.min_pem_key_len = min(self.min_pem_key_len, rule.min_line_len)\n elif rule.rule_type == RuleType.MULTI:\n self.min_multi_len = min(self.min_multi_len, rule.min_line_len)\n else:\n logger.warning(\"Unknown rule type:%s\", rule.rule_type)\n self.rules_scanners.append((rule, self.get_scanner(rule)))\n else:\n raise RuntimeError(f\"Wrong rules '{rule_templates}' were read from '{rules_path}'\")\n\n def _is_available(self, rule: Rule) -> bool:\n \"\"\"separate the method to reduce complexity\"\"\"\n if rule.severity < self.config.severity:\n return False\n if self.config.doc:\n if \"doc\" in rule.target:\n return True\n else:\n if \"code\" in rule.target:\n return True\n return False\n\n def yield_rule_scanner(\n self, #\n line_len: int, #\n matched_pattern: bool, #\n matched_keyword: bool, #\n matched_pem_key: bool, #\n matched_multi: bool) -> Generator[Tuple[Rule, Type[ScanType]], None, None]:\n \"\"\"returns generator for rules and according scanner\"\"\"\n for rule, scanner in self.rules_scanners:\n if line_len >= rule.min_line_len \\\n and (RuleType.PATTERN == rule.rule_type and matched_pattern\n or RuleType.KEYWORD == rule.rule_type and matched_keyword\n or RuleType.PEM_KEY == rule.rule_type and matched_pem_key\n or RuleType.MULTI == rule.rule_type and matched_multi):\n yield rule, scanner\n\n def scan(self, provider: ContentProvider) -> List[Candidate]:\n \"\"\"Run scanning of list of target lines from 'targets' with set of rule from 'self.rules'.\n\n Args:\n provider: objects with data to analyze: line, line number,\n filepath and all lines in file\n\n Return:\n list of all detected credential candidates in analyzed targets\n\n \"\"\"\n credentials: List[Candidate] = []\n\n for target in provider.yield_analysis_target(self.min_len):\n # Trim string from outer spaces to make future `x in str` checks faster\n target_line_stripped = target.line_strip\n target_line_stripped_len = target.line_strip_len\n # use lower case for required substring\n target_line_stripped_lower = target.line_lower_strip\n\n # \"cache\" - YAPF and pycharm formatters ...\n matched_keyword = \\\n target_line_stripped_len >= self.min_keyword_len and ( #\n '=' in target_line_stripped\n or ':' in target_line_stripped\n or (\"define\" in target_line_stripped\n and ('(' in target_line_stripped and ',' in target_line_stripped\n or \"#define\" in target_line_stripped\n or \"%define\" in target_line_stripped)\n )\n or \"%global\" in target_line_stripped\n or \"set\" in target_line_stripped_lower\n or \"%3d\" in target_line_stripped_lower\n ) #\n matched_pem_key = \\\n target_line_stripped_len >= self.min_pem_key_len \\\n and PEM_BEGIN_PATTERN in target_line_stripped and \"PRIVATE\" in target_line_stripped\n matched_pattern = target_line_stripped_len >= self.min_pattern_len\n matched_multi = target_line_stripped_len >= self.min_multi_len\n\n if not (matched_keyword or matched_pem_key or matched_pattern or matched_multi):\n # target may be skipped only with length because not all rules have required_substrings\n logger.debug(\"Skip too short (%d) line %s:%d\", target_line_stripped_len, target.file_path,\n target.line_num)\n continue\n\n # cached value to skip the same regex verifying\n matched_regex: Dict[re.Pattern, bool] = {}\n\n for rule, scanner in self.yield_rule_scanner(target_line_stripped_len, matched_pattern, matched_keyword,\n matched_pem_key, matched_multi):\n if rule.has_required_substrings \\\n and not self._substring_check(rule.required_substrings, target_line_stripped_lower):\n continue\n\n # common regex might be triggered for the same target\n if rule.required_regex:\n if rule.required_regex in matched_regex:\n regex_result = matched_regex[rule.required_regex]\n else:\n regex_result = bool(rule.required_regex.search(target_line_stripped))\n matched_regex[rule.required_regex] = regex_result\n if not regex_result:\n continue\n\n if new_credentials := scanner.run(self.config, rule, target):\n credentials.extend(new_credentials)\n logger.debug(\"Credential for rule: %s in file: %s:%d in line: %s\", rule.rule_name, target.file_path,\n target.line_num, target.line)\n return credentials\n\n @staticmethod\n def get_scanner(rule: Rule) -> Type[ScanType]:\n \"\"\"Choose type of scanner base on rule affiliation.\n\n Args:\n rule: rule object used to scanning\n\n Return:\n depending on the rule type, returns the corresponding scanner class\n\n \"\"\"\n if rule.rule_type in (RuleType.PATTERN, RuleType.KEYWORD):\n return SinglePattern\n if RuleType.MULTI == rule.rule_type:\n return MultiPattern\n if RuleType.PEM_KEY == rule.rule_type:\n return PemKeyPattern\n raise ValueError(f\"Unknown pattern_type in rule: {rule.rule_type}\")\n" }, { "path": "credsweeper/secret/config.json", "content": "{\n \"exclude\": {\n \"pattern\": [],\n \"containers\": [\n \".aar\",\n \".apk\",\n \".bz2\",\n \".class\",\n \".gz\",\n \".jar\",\n \".lzma\",\n \".rpm\",\n \".tar\",\n \".war\",\n \".whl\",\n \".xz\",\n \".zip\"\n ],\n \"documents\": [\n \".doc\",\n \".docx\",\n \".odp\",\n \".ods\",\n \".odt\",\n \".pdf\",\n \".ppt\",\n \".pptx\",\n \".xls\",\n \".xlsx\"\n ],\n \"extension\": [\n \".3gp\",\n \".7z\",\n \".a\",\n \".aac\",\n \".avi\",\n \".bin\",\n \".bmp\",\n \".css\",\n \".dmg\",\n \".ear\",\n \".eot\",\n \".elf\",\n \".exe\",\n \".gif\",\n \".gmo\",\n \".ico\",\n \".img\",\n \".info\",\n \".jpeg\",\n \".jpg\",\n \".lib\",\n \".map\",\n \".m4a\",\n \".m4b\",\n \".m4p\",\n \".m4r\",\n \".mat\",\n \".mo\",\n \".mov\",\n \".mp3\",\n \".mp4\",\n \".mpg\",\n \".mkv\",\n \".npy\",\n \".npz\",\n \".obj\",\n \".oga\",\n \".ogg\",\n \".ogv\",\n \".ops\",\n \".pak\",\n \".png\",\n \".psd\",\n \".pyc\",\n \".pyd\",\n \".pyo\",\n \".rar\",\n \".rc\",\n \".rc2\",\n \".realm\",\n \".res\",\n \".s7z\",\n \".scss\",\n \".so\",\n \".sum\",\n \".svg\",\n \".swf\",\n \".tif\",\n \".tiff\",\n \".tlb\",\n \".ttf\",\n \".vcxproj\",\n \".vdproj\",\n \".wav\",\n \".webm\",\n \".webp\",\n \".wma\",\n \".woff\",\n \".woff2\",\n \".yuv\"\n ],\n \"path\": [\n \"/.git/\",\n \"/.idea/\",\n \"/.svn/\",\n \"/__pycache__/\",\n \"/node_modules/\",\n \"/target/\",\n \"/.venv/\",\n \"/venv/\"\n ],\n \"lines\": [],\n \"values\": []\n },\n \"source_ext\": [\n \".aspx\",\n \".cs\",\n \".cshtml\",\n \".ejs\",\n \".erb\",\n \".go\",\n \".html\",\n \".ipynb\",\n \".jsp\",\n \".jsx\",\n \".php\",\n \".phtml\",\n \".rb\",\n \".sh\",\n \".swift\",\n \".ts\",\n \".twig\",\n \".vue\",\n \".xhtml\",\n \".java\",\n \".js\",\n \".py\",\n \".cpp\",\n \".c\",\n \".h\",\n \".hpp\",\n \".mm\",\n \".cu\",\n \".y\",\n \".vb\",\n \".m\",\n \".cu\"\n ],\n \"source_quote_ext\": [\n \".cs\",\n \".cc\",\n \".php\",\n \".tf\",\n \".kt\",\n \".go\",\n \".ipynb\",\n \".ts\",\n \".java\",\n \".js\",\n \".py\",\n \".cpp\",\n \".c\",\n \".h\",\n \".hpp\"\n ],\n \"find_by_ext_list\": [\n \".pem\",\n \".cer\",\n \".csr\",\n \".der\",\n \".pfx\",\n \".p12\",\n \".key\",\n \".jks\"\n ],\n \"bruteforce_list\": [\n \"\",\n \"changeit\",\n \"changeme\",\n \"tizen\"\n ],\n \"check_for_literals\": true,\n \"max_password_value_length\": 64,\n \"max_url_cred_value_length\": 80,\n \"line_data_output\": [\n \"line\",\n \"line_num\",\n \"path\",\n \"info\",\n \"variable\",\n \"variable_start\",\n \"variable_end\",\n \"value\",\n \"value_start\",\n \"value_end\",\n \"entropy\"\n ],\n \"candidate_output\": [\n \"rule\",\n \"severity\",\n \"confidence\",\n \"ml_probability\",\n \"line_data_list\"\n ]\n}\n" }, { "path": "credsweeper/secret/log.yaml", "content": "---\n\nversion: 1\n\ndisable_existing_loggers: False\n\nignore: [git, pdfminer]\n\nformatters:\n simple:\n format: \"%(asctime)s | %(levelname)s | %(module)s:%(lineno)d | %(message)s\"\n verbose:\n format: \"%(asctime)s | %(levelname)s | %(module)s | %(processName)s:%(threadName)s | %(filename)s:%(lineno)s | %(message)s\"\n\nhandlers:\n console:\n class: logging.StreamHandler\n level: INFO\n formatter: simple\n stream: ext://sys.stdout\n\n logfile:\n class: logging.handlers.RotatingFileHandler\n level: DEBUG\n formatter: simple\n filename: ./log/credsweeper.log\n maxBytes: 50485760\n backupCount: 100\n delay: True\n\n error_log:\n class: logging.handlers.RotatingFileHandler\n level: ERROR\n formatter: verbose\n filename: ./log/error.log\n maxBytes: 10485760\n backupCount: 5\n\nroot:\n level: DEBUG\n handlers: [console, error_log]\n" }, { "path": "credsweeper/utils/__init__.py", "content": "" }, { "path": "credsweeper/utils/hop_stat.py", "content": "import statistics\nfrom typing import Tuple, Dict\n\n\nclass HopStat:\n \"\"\"Statistical check distances between symbols sequence in a value on keyboard layout\"\"\"\n\n KEYBOARD = ( #\n \"`1234567890-=\", #\n \"\\0qwertyuiop[]\\\\\", #\n \"\\0\\0asdfghjkl;'\", #\n \"\\0\\0zxcvbnm,./\", #\n )\n TRANSLATION = str.maketrans({\n '~': '`',\n '!': '1',\n '@': '2',\n '#': '3',\n '$': '4',\n '%': '5',\n '^': '6',\n '&': '7',\n '*': '8',\n '(': '9',\n ')': '0',\n '_': '-',\n '+': '=',\n 'Q': 'q',\n 'W': 'w',\n 'E': 'e',\n 'R': 'r',\n 'T': 't',\n 'Y': 'y',\n 'U': 'u',\n 'I': 'i',\n 'O': 'o',\n 'P': 'p',\n '{': '[',\n '}': ']',\n '|': '\\\\',\n 'A': 'a',\n 'S': 's',\n 'D': 'd',\n 'F': 'f',\n 'G': 'g',\n 'H': 'h',\n 'J': 'j',\n 'K': 'k',\n 'L': 'l',\n ':': ';',\n '\"': \"'\",\n 'Z': 'z',\n 'X': 'x',\n 'C': 'c',\n 'V': 'v',\n 'B': 'b',\n 'N': 'n',\n 'M': 'm',\n '<': ',',\n '>': '.',\n '?': '/',\n })\n\n def __init__(self):\n self.__hop_dict: Dict[Tuple[str, str], int] = {}\n base = ''.join(x for x in HopStat.KEYBOARD)\n for a in (x for x in base if '\\0' != x):\n for b in (x for x in base if '\\0' != x):\n if (b, a) in self.__hop_dict:\n self.__hop_dict[(a, b)] = self.__hop_dict[(b, a)]\n continue\n if a == b:\n self.__hop_dict[(a, b)] = 0\n else:\n x_a, y_a, z_a = self.__get_xyz(a)\n x_b, y_b, z_b = self.__get_xyz(b)\n d = (abs(x_a - x_b) + abs(y_a - y_b) + abs(z_a - z_b)) // 2\n self.__hop_dict[(a, b)] = d\n\n @staticmethod\n def __get_xyz(c: str) -> Tuple[int, int, int]:\n \"\"\"Returns axial coordinates of a char on keyboad qwerty\"\"\"\n x = y = z = 0\n for i, _ in enumerate(HopStat.KEYBOARD):\n x = HopStat.KEYBOARD[i].find(c)\n if 0 <= x:\n z = i\n x = x - (i // 2)\n y = -(z + x)\n break\n return x, y, z\n\n def stat(self, value: str) -> Tuple[float, float]:\n \"\"\"Calculates statistical distances between given symbols\n\n Args:\n value: string based on initial alphabet\n\n Return:\n Average distance, deviation or exception if a value is not in initial alphabet\n\n \"\"\"\n hops = []\n value = value.translate(HopStat.TRANSLATION)\n for a, b in zip(value[:-1], value[1:]):\n hop = self.__hop_dict.get((a, b))\n if hop is None:\n raise ValueError(f\"Unknown char '{a}' or '{b}'\")\n hops.append(hop)\n avg = statistics.mean(hops)\n dev = statistics.stdev(hops, avg)\n return avg, dev\n" }, { "path": "credsweeper/utils/pem_key_detector.py", "content": "import contextlib\nimport logging\nimport re\nimport string\nfrom typing import List\n\nfrom credsweeper.common.constants import PEM_BEGIN_PATTERN, PEM_END_PATTERN, Chars, MAX_LINE_LENGTH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.utils.util import Util\n\nlogger = logging.getLogger(__name__)\n\n\nclass PemKeyDetector:\n \"\"\"Class to detect PEM PRIVATE keys only\"\"\"\n BASE64_CHARS_SET = set(Chars.BASE64STDPAD_CHARS.value)\n RE_BASE64_CHARS = re.compile(fr\"[{re.escape(Chars.BASE64STDPAD_CHARS.value)}]+\")\n\n ENTROPY_LIMIT_BASE64 = 4.5\n\n # the limit is huge with possible prefixes and escaping\n MAX_PEM_LENGTH = 4 * MAX_LINE_LENGTH\n\n IGNORE_STARTS = [PEM_BEGIN_PATTERN, \"Proc-Type\", \"Version\", \"DEK-Info\"]\n WRAP_CHARACTERS = \"\\\\'\\\"`;,[]#*!\"\n REMOVE_CHARACTERS = string.whitespace + WRAP_CHARACTERS\n # last line contains 4 symbols, at least\n RE_PEM_BEGIN = re.compile(r\"(?P\" + PEM_BEGIN_PATTERN +\n r\"(?![^-]{1,80}ENCRYPTED)[^-]{0,80}PRIVATE[^-]{1,80}KEY[^-]{0,80}-----\"\n r\"(.{1,8000}\" + PEM_END_PATTERN + r\"[^-]{1,80}KEY[^-]{0,80}-----)?)\")\n RE_PEM_VALUE = re.compile(fr\"(?P.{{0,{MAX_PEM_LENGTH}}})\")\n\n def __init__(self, config: Config):\n self.__config = config\n self._barrier_pos: int = -2\n self._barrier_cut: int = -2\n self._barrier: str = ''\n\n def cut_barrier(self, line: str) -> str:\n \"\"\"Cut off barrier if detected\"\"\"\n if self._barrier and 0 <= self._barrier_pos < self._barrier_cut < len(line):\n if line[self._barrier_pos] == self._barrier:\n return line[self._barrier_cut:]\n self._barrier = ''\n self._barrier_pos = self._barrier_cut = -1\n return line\n\n def set_barrier(self, line: str, start=0, end=MAX_LINE_LENGTH):\n \"\"\"Detects barrier with offset of RE_PEM_BEGIN\"\"\"\n self._barrier = ''\n self._barrier_cut = line.find(PEM_END_PATTERN, start, end)\n self._barrier_pos = self._barrier_cut - 1\n if 0 <= self._barrier_pos < self._barrier_cut < len(line):\n barrier = line[self._barrier_pos]\n if barrier not in PemKeyDetector.BASE64_CHARS_SET:\n self._barrier = barrier\n\n def detect_pem_key(self, first_line: LineData, target: AnalysisTarget) -> List[LineData]:\n \"\"\"Detects PEM key in single line and with iterative for next lines according\n https://www.rfc-editor.org/rfc/rfc7468\n\n Args:\n first_line: detected -----BEGIN from rule pattern\n target: Analysis target\n\n Return:\n List of LineData with found PEM\n\n \"\"\"\n line_data_list: List[LineData] = []\n key_data_list: List[str] = []\n # escaped key in one line with prefixes\n pem_end_limit = min(target.line_len, first_line.value_start + PemKeyDetector.MAX_PEM_LENGTH)\n first_line_end_pattern_start = target.line.find(PEM_END_PATTERN, first_line.value_start, pem_end_limit)\n first_line_end_pattern_end = ( #\n target.line.find(\"-----\", first_line_end_pattern_start + 5, first_line_end_pattern_start + 80) #\n if 0 <= first_line_end_pattern_start else -2)\n if first_line.value_start < first_line_end_pattern_start < first_line_end_pattern_end:\n # the whole PEM in single line\n pem_text = target.line[first_line.value_start:first_line_end_pattern_end + 5]\n first_line.value = pem_text\n first_line.value_end = first_line.value_start + len(pem_text)\n line_data_list.append(first_line)\n else:\n line_data_list.append(first_line)\n pem_text = first_line.line[first_line.value_start:first_line.value_start + PemKeyDetector.MAX_PEM_LENGTH]\n # perhaps, in next lines\n start_pos = max(0, target.line_pos) + 1\n end_pos = min(start_pos + 200, target.lines_len)\n for line_pos in range(start_pos, end_pos):\n target_line = target.lines[line_pos]\n end_pattern_start = target_line.find(PEM_END_PATTERN, 0, PemKeyDetector.MAX_PEM_LENGTH)\n end_pattern_end = (5 + target_line.find(\"-----\", end_pattern_start + 5, end_pattern_start + 80)\n if 0 <= end_pattern_start else -2)\n if 0 <= end_pattern_start < end_pattern_end:\n pem_line = target_line[:end_pattern_end]\n else:\n pem_line = target_line[:PemKeyDetector.MAX_PEM_LENGTH]\n next_line = LineData(self.__config, target_line, line_pos, target.line_nums[line_pos], target.file_path,\n target.file_type, target.info, PemKeyDetector.RE_PEM_VALUE)\n line_data_list.append(next_line)\n pem_text += f\"\\n{pem_line}\"\n if PEM_END_PATTERN in pem_line:\n break\n if PemKeyDetector.MAX_PEM_LENGTH < len(pem_text):\n logger.warning(\"PEM text oversize\")\n return []\n else:\n logger.warning(\"PEM end not found %s\", target.descriptor)\n return []\n\n while \"\\\\\\\\\" in pem_text:\n # reduce JSON escaping sequences of backslash\n pem_text = pem_text.replace(\"\\\\\\\\\", '\\\\')\n\n # replace escaped line ends with real and process them - PEM does not contain '\\' sign\n pem_text = pem_text.replace(\"\\\\r\\\\n\", '\\n').replace(\"\\\\r\", '\\n').replace(\"\\\\n\", '\\n').replace(\"\\\\t\", '\\t')\n pem_lines = pem_text.splitlines()\n self.set_barrier(pem_lines[-1])\n for subline in pem_lines:\n if PemKeyDetector.is_leading_config_line(subline):\n continue\n _subline = self.cut_barrier(subline)\n if sanitized_line := PemKeyDetector.sanitize_line(_subline):\n if PEM_END_PATTERN in sanitized_line:\n return PemKeyDetector.finalize(line_data_list, key_data_list, sanitized_line)\n # the end is not reached - sanitize the data\n # PEM key line should not contain spaces or . (and especially not ...)\n if not PemKeyDetector.RE_BASE64_CHARS.fullmatch(sanitized_line):\n return []\n key_data_list.append(sanitized_line)\n return []\n\n @staticmethod\n def finalize(line_data_list: List[LineData], key_data_list: List[str], last_line: str) -> List[LineData]:\n \"\"\"Checks collected key_data according the key type\"\"\"\n if len(key_data_list) < len(line_data_list):\n PemKeyDetector.sanitize_line_data_list(line_data_list, key_data_list, last_line)\n key_data = ''.join(key_data_list)\n if \"PGP\" in line_data_list[0].value:\n # Check if entropy is high enough for base64 set with padding sign\n entropy = Util.get_shannon_entropy(key_data)\n if PemKeyDetector.ENTROPY_LIMIT_BASE64 <= entropy:\n return line_data_list\n logger.debug(\"Filtered with entropy %f '%s'\", entropy, key_data)\n if \"OPENSSH\" in line_data_list[0].value:\n # Check whether the key is encrypted\n with contextlib.suppress(Exception):\n decoded = Util.decode_base64(key_data, urlsafe_detect=True)\n if 32 < len(decoded) and b\"bcrypt\" not in decoded:\n # 256 bits is the minimal size of Ed25519 keys\n # all OK - the key is not encrypted in this top level\n return line_data_list\n logger.debug(\"Filtered with size or bcrypt '%s'\", key_data)\n else:\n with contextlib.suppress(Exception):\n if decoded := Util.decode_base64(key_data, padding_safe=True, urlsafe_detect=True):\n if len(decoded) == Util.get_asn1_size(decoded):\n # all OK - the key is not encrypted in this top level\n return line_data_list\n logger.debug(\"Filtered with non asn1 '%s'\", key_data)\n return []\n\n @staticmethod\n def sanitize_line_data_list(line_data_list: List[LineData], key_data_list: List[str], last_line: str):\n \"\"\"Sanitize line_data_list to keep only valuable values\"\"\"\n for value in key_data_list:\n if 64 <= len(value):\n # normal value length should not have a collision\n for line_data in line_data_list:\n if value == line_data.value:\n # plain case - no sanitize necessary\n break\n value_start = line_data.value.find(value)\n if 0 <= value_start:\n line_data.value = value\n line_data.value_start = value_start\n line_data.value_end = value_start + len(value)\n break\n else:\n # end of pem may be short and have collisions in long lines\n value_pattern = re.compile(fr\".*[^0-9A-Za-z+/=]?({re.escape(value)})[^0-9A-Za-z+/=]?.*\")\n for line_data in line_data_list:\n if value == line_data.value:\n # plain case - no sanitize necessary\n break\n if value_match := value_pattern.fullmatch(line_data.value):\n line_data.value = value_match.group(1)\n line_data.value_start, line_data.value_end = value_match.span(1)\n break\n if last_line.startswith(PEM_END_PATTERN) and last_line.endswith(\"-----\"):\n last_line_data = line_data_list[-1]\n last_value_start = last_line_data.value.find(last_line, 0, PemKeyDetector.MAX_PEM_LENGTH)\n if 0 <= last_line_data.value_start <= last_value_start:\n # left barrier was sanitized\n last_line_data.value = last_line\n last_line_data.value_start = last_value_start\n last_line_data.value_end = last_value_start + len(last_line)\n\n @staticmethod\n def sanitize_line(line: str, recurse_level: int = 5) -> str:\n \"\"\"Remove common symbols that can surround PEM keys inside code.\n\n Examples::\n\n `# ZZAWarrA1`\n `* ZZAWarrA1`\n ` \"ZZAWarrA1\\\\n\" + `\n\n Args:\n line: Line to be cleaned\n recurse_level: to avoid infinite loop in case when removed symbol inside base64 encoded\n\n Return:\n line with special characters removed from both ends\n\n \"\"\"\n recurse_level -= 1\n\n if 0 > recurse_level:\n return line\n\n # Note that this strip would remove `\\n` but not `\\\\n`\n line = line.strip(string.whitespace)\n while line.startswith((\"// \", \"//\\t\")):\n line = line[3:]\n while line.startswith((\"/// \", \"///\\t\")):\n line = line[4:]\n while line.startswith(\"/*\"):\n line = line[2:]\n while line.endswith(\"*/\"):\n line = line[:-2]\n while line.endswith(\"\\\\\"):\n # line carry in many languages\n line = line[:-1]\n\n # remove concatenation carefully only when it is not part of base64\n if line.startswith('+') and 1 < len(line) and line[1] not in PemKeyDetector.BASE64_CHARS_SET:\n line = line[1:]\n if line.endswith('+') and 2 < len(line) and line[-2] not in PemKeyDetector.BASE64_CHARS_SET:\n line = line[:-1]\n\n line = line.strip(PemKeyDetector.REMOVE_CHARACTERS)\n # check whether new iteration requires\n for x in PemKeyDetector.WRAP_CHARACTERS:\n if x in line:\n return PemKeyDetector.sanitize_line(line, recurse_level=recurse_level)\n\n return line\n\n @staticmethod\n def is_leading_config_line(line: str) -> bool:\n \"\"\"Remove non-key lines from the beginning of a list.\n\n Example lines with non-key leading lines:\n\n .. code-block:: text\n\n Proc-Type: 4,ENCRYPTED\n DEK-Info: DEK-Info: AES-256-CBC,2AA219GG746F88F6DDA0D852A0FD3211\n\n ZZAWarrA1...\n\n Args:\n line: Line to be checked\n\n Return:\n True if the line is not a part of encoded data but leading config\n\n \"\"\"\n if not line:\n return True\n for ignore_string in PemKeyDetector.IGNORE_STARTS:\n if ignore_string in line:\n return True\n return False\n" }, { "path": "credsweeper/utils/util.py", "content": "import ast\nimport base64\nimport contextlib\nimport json\nimport logging\nimport math\nimport os\nimport random\nimport re\nimport string\nimport warnings\nfrom pathlib import Path\nfrom typing import Any, Dict, List, Tuple, Optional, Union\n\nimport numpy as np\nimport yaml\nfrom cryptography.hazmat.primitives import hashes\nfrom cryptography.hazmat.primitives.asymmetric import padding\nfrom cryptography.hazmat.primitives.asymmetric.dh import DHPrivateKey, DHPublicKey\nfrom cryptography.hazmat.primitives.asymmetric.dsa import DSAPrivateKey, DSAPublicKey\nfrom cryptography.hazmat.primitives.asymmetric.ec import EllipticCurvePrivateKey, EllipticCurvePublicKey\nfrom cryptography.hazmat.primitives.asymmetric.ed25519 import Ed25519PrivateKey, Ed25519PublicKey\nfrom cryptography.hazmat.primitives.asymmetric.ed448 import Ed448PrivateKey, Ed448PublicKey\nfrom cryptography.hazmat.primitives.asymmetric.rsa import RSAPrivateKey\nfrom cryptography.hazmat.primitives.asymmetric.types import PrivateKeyTypes\nfrom cryptography.hazmat.primitives.asymmetric.x25519 import X25519PublicKey, X25519PrivateKey\nfrom cryptography.hazmat.primitives.asymmetric.x448 import X448PublicKey, X448PrivateKey\nfrom cryptography.hazmat.primitives.serialization import load_der_private_key\nfrom cryptography.hazmat.primitives.serialization.pkcs12 import load_key_and_certificates\nfrom lxml import etree\n\nfrom credsweeper.common.constants import AVAILABLE_ENCODINGS, \\\n DEFAULT_ENCODING, LATIN_1, CHUNK_SIZE, MAX_LINE_LENGTH, CHUNK_STEP_SIZE, ASCII, UTF_16_LE, UTF_16_BE\n\nlogger = logging.getLogger(__name__)\n\n\nclass Util:\n \"\"\"Class that contains different useful methods.\"\"\"\n\n @staticmethod\n def get_extension(file_path: str, lower=True) -> str:\n \"\"\"Return extension of file in lower case by default e.g.: '.txt', '.JPG'\"\"\"\n _, extension = os.path.splitext(str(file_path))\n return extension.lower() if lower else extension\n\n @staticmethod\n def get_regex_combine_or(re_strs: List[str]) -> str:\n \"\"\"Routine combination for regex 'or'\"\"\"\n result = \"(?:\"\n\n for elem in re_strs:\n result += elem + \"|\"\n\n if result[-1] == \"|\":\n result = result[:-1]\n result += \")\"\n\n return result\n\n @staticmethod\n def get_shannon_entropy(data: Union[str, bytes]) -> float:\n \"\"\"Borrowed from http://blog.dkbza.org/2007/05/scanning-data-for-entropy-anomalies.html.\"\"\"\n if not data:\n return 0.0\n size = len(data)\n _uniq, counts = np.unique(list(data), return_counts=True)\n probabilities = counts / size\n entropy = -float(np.sum(probabilities * np.log2(probabilities)))\n return entropy\n\n # Precalculated data for speedup\n MIN_DATA_ENTROPY: Dict[int, float] = {\n 16: 1.66973671780348,\n 20: 2.07723544540831,\n 32: 3.25392803184602,\n 40: 3.64853567064867,\n 64: 4.57756933688035,\n 384: 7.39,\n 512: 7.55,\n }\n\n @staticmethod\n def get_min_data_entropy(x: int) -> float:\n \"\"\"Returns minimal entropy for size of random data. Precalculated data is applied for speedup\"\"\"\n if x in Util.MIN_DATA_ENTROPY:\n y = Util.MIN_DATA_ENTROPY[x]\n elif 8 < x < 64:\n # approximated for range 12 - 64\n _x = x - 8\n y = ((0.000016617804 * _x - 0.002695077) * _x + 0.170393) * _x + 0.4\n elif 64 < x < 384:\n # logarithm base 2 - slow, but precise\n _x = x - 8\n y = 1.095884 * math.log2(_x) - 1.90156\n elif 384 < x < 512:\n # solved for 384 - 512\n y = -0.11215851 * math.log2(x)**2 + 2.34303484 * math.log2(x) - 4.4466237\n else:\n # less or equal to 8 bytes might have 0 entropy\n y = 0\n return y\n\n @staticmethod\n def is_ascii_entropy_validate(data: bytes) -> bool:\n \"\"\"\n Tests small data sequence (<256) for data randomness by testing for ascii and shannon entropy\n Returns True when data is an ASCII symbols or have small entropy\n \"\"\"\n if not data:\n return True\n data_len = len(data)\n if 9 > data_len:\n # even random data may have 0 entropy for length of 8 bytes and less\n return True\n entropy = 0.\n cells = [int(0)] * 256\n ascii_test = True\n # \"basket\" sorting approach\n for x in data:\n cells[x] += 1\n if ascii_test and 0b10000000 & x:\n ascii_test = False\n if ascii_test:\n # only ascii symbols found\n return True\n left = 0.\n step = 256.0 / data_len\n right = left + step\n while left < 256:\n cell_sum = 0\n i = int(left)\n r = int(right)\n while i < r and i < 256:\n cell_sum += cells[i]\n i += 1\n p_x = float(cell_sum) / data_len\n if p_x > 0:\n entropy += -p_x * math.log2(p_x)\n left = right\n right += step\n min_entropy = Util.get_min_data_entropy(data_len)\n return entropy < min_entropy\n\n @staticmethod\n def is_binary(data: Union[bytes, bytearray]) -> bool:\n \"\"\"\n Returns True when two zeroes sequence is found in begin of data.\n The sequence never exists in text format (UTF-8, UTF-16). UTF-32 is not supported.\n \"\"\"\n if 0 <= data.find(b\"\\0\\0\", 0, MAX_LINE_LENGTH):\n return True\n return False\n\n NOT_LATIN1_PRINTABLE_SET = set(range(0, 256)) \\\n .difference(set(x for x in string.printable.encode(ASCII))) \\\n .difference({0x1B}) \\\n .difference(set(x for x in range(0xA0, 0x100)))\n\n @staticmethod\n def is_latin1(data: Union[bytes, bytearray]) -> bool:\n \"\"\"Returns True when data looks like LATIN-1 for first MAX_LINE_LENGTH bytes.\"\"\"\n result = False\n if data:\n non_latin1_cnt = sum(1 for x in data[:MAX_LINE_LENGTH] if x in Util.NOT_LATIN1_PRINTABLE_SET)\n # experiment for 255217 binary files shown avg = 0.268264 ± 0.168767, so let choose minimal\n chunk_len = min(MAX_LINE_LENGTH, len(data))\n result = bool(0.1 > non_latin1_cnt / chunk_len)\n return result\n\n @staticmethod\n def read_file(path: Union[str, Path], encodings: Optional[List[str]] = None) -> List[str]:\n \"\"\"Read the file content using different encodings.\n\n Try to read the contents of the file according to the list of encodings \"encodings\" as soon as reading\n occurs without any exceptions, the data is returned in the current encoding\n\n Args:\n path: path to file\n encodings: supported encodings\n\n Return:\n list of file rows in a suitable encoding from \"encodings\",\n if none of the encodings match, an empty list will be returned\n\n \"\"\"\n if data := Util.read_data(path):\n return Util.decode_bytes(data, encodings)\n return []\n\n @staticmethod\n def decode_text(content: Optional[bytes], encodings: Optional[List[str]] = None) -> Optional[str]:\n \"\"\"Decode content using different encodings.\n\n Try to decode bytes according to the list of encodings \"encodings\"\n occurs without any exceptions. UTF-16 requires BOM\n\n Args:\n content: raw data that might be text\n encodings: supported encodings\n\n Return:\n Decoded text in str for any suitable encoding\n or None when binary data detected\n\n \"\"\"\n if content is None:\n return None\n binary_suggest = False\n if encodings:\n # use exactly defined encodings\n _encodings = encodings\n elif content.startswith(b\"\\xFF\\xFE\") or 1 < len(content) and 0 == content[1]:\n _encodings = [UTF_16_LE]\n elif content.startswith(b\"\\xFE\\xFF\") or content.startswith(b'\\x00'):\n _encodings = [UTF_16_BE]\n else:\n _encodings = AVAILABLE_ENCODINGS\n for encoding in _encodings:\n try:\n if binary_suggest and LATIN_1 == encoding and (Util.is_binary(content) or not Util.is_latin1(content)):\n # LATIN_1 may convert data (bytes in range 0x80:0xFF are transformed)\n break\n text = content.decode(encoding=encoding, errors=\"strict\")\n if content != text.encode(encoding=encoding, errors=\"strict\"):\n # the refurbish test helps to detect a real encoding\n binary_suggest = True\n continue\n # the case decoding is good\n if UTF_16_LE == encoding or UTF_16_BE == encoding:\n return text.lstrip('\\uFEFF')\n return text\n except UnicodeError:\n binary_suggest = True\n logger.debug(\"UnicodeError: Can't decode content as %s.\", encoding)\n except Exception as exc:\n logger.error(\"Unexpected Error: Can't read content as %s. Error message: %s\", encoding, exc)\n return None\n\n @staticmethod\n def split_text(text: str) -> List[str]:\n \"\"\"Splits a text into lines, handling all common line endings (e.g., LF, CRLF, CR).\"\"\"\n return text.replace(\"\\r\\n\", '\\n').replace('\\r', '\\n').split('\\n')\n\n @staticmethod\n def decode_bytes(content: Optional[bytes], encodings: Optional[List[str]] = None) -> List[str]:\n \"\"\"Decode content using different encodings.\n\n Try to decode bytes according to the list of encodings \"encodings\"\n occurs without any exceptions. UTF-16 requires BOM\n\n Args:\n content: raw data that might be text\n encodings: supported encodings\n\n Return:\n list of file rows in a suitable encoding from \"encodings\",\n if none of the encodings match, an empty list will be returned\n Also empty list will be returned after last encoding and 0 symbol is present in lines not at end\n\n \"\"\"\n if text := Util.decode_text(content, encodings):\n return Util.split_text(text)\n return []\n\n @staticmethod\n def get_asn1_size(data: Union[bytes, bytearray]) -> int:\n \"\"\"Only sequence type 0x30 and size correctness are checked\n Returns size of ASN1 data over 128 bytes or 0 if no interested data\n \"\"\"\n if isinstance(data, (bytes, bytearray)) and 2 <= len(data) and 0x30 == data[0]:\n # https://www.oss.com/asn1/resources/asn1-made-simple/asn1-quick-reference/basic-encoding-rules.html#Lengths\n length = data[1]\n if 0x80 == length:\n if data.endswith(b\"\\x00\\x00\"):\n # assume, all data are ASN1 of various size\n return len(data)\n # else - skip the case where the ASN1 size is smaller than the actual data\n elif 0x80 < length:\n byte_len = 0x7F & length\n len_limit = 2 + byte_len\n if 4 >= byte_len and len(data) >= len_limit:\n length = 0\n for i in range(2, len_limit):\n length <<= 8\n length |= data[i]\n if len(data) >= length + len_limit:\n return length + len_limit\n # else - unsupported huge size\n else:\n # length is less than 0x80\n if len(data) >= length + 2:\n return length + 2\n # fallback - unsupported\n return 0\n\n @staticmethod\n def read_data(path: Union[str, Path]) -> Optional[bytes]:\n \"\"\"Read the file bytes as is.\n\n Try to read the data of the file.\n\n Args:\n path: path to file\n\n Return:\n list of file rows in a suitable encoding from \"encodings\",\n if none of the encodings match, an empty list will be returned\n\n \"\"\"\n\n try:\n with open(path, \"rb\") as file:\n return file.read()\n except Exception as exc:\n logger.error(\"Unexpected Error: Can not read '%s'. Error message: '%s'\", path, exc)\n return None\n\n @staticmethod\n def get_xml_from_lines(xml_lines: List[str]) -> Tuple[Optional[List[str]], Optional[List[int]]]:\n \"\"\"Parse xml data from list of string and return List of str.\n\n Args:\n xml_lines: list of lines of xml data\n\n Return:\n List of formatted string(f\"{root.tag} : {root.text}\")\n\n Raises:\n xml exception\n\n \"\"\"\n lines = []\n line_nums = []\n tree = etree.fromstringlist(xml_lines)\n for element in tree.iter():\n tag = Util.extract_element_data(element, \"tag\")\n text = Util.extract_element_data(element, \"text\")\n lines.append(f\"{tag} : {text}\")\n line_nums.append(element.sourceline)\n return lines, line_nums\n\n @staticmethod\n def extract_element_data(element: Any, attr: str) -> str:\n \"\"\"Extract xml element data to string.\n\n Try to extract the xml data and strip() the string.\n\n Args:\n element: xml element\n attr: attribute name\n\n Return:\n String xml data with strip()\n\n \"\"\"\n element_attr: Any = getattr(element, attr)\n if element_attr is None or not isinstance(element_attr, str):\n return ''\n return str(element_attr).strip()\n\n @staticmethod\n def json_load(file_path: Union[str, Path], encoding=DEFAULT_ENCODING) -> Any:\n \"\"\"Load dictionary from JSON file\"\"\"\n try:\n with open(file_path, \"r\", encoding=encoding) as f:\n return json.load(f)\n except Exception as exc:\n logging.error(\"Failed to read: %s %s\", file_path, exc)\n return None\n\n @staticmethod\n def json_dump(obj: Any, file_path: Union[str, Path], encoding=DEFAULT_ENCODING, indent=4) -> None:\n \"\"\"Write dictionary to JSON file\"\"\"\n try:\n with open(file_path, \"w\", encoding=encoding) as f:\n json.dump(obj, f, indent=indent)\n except Exception as exc:\n logging.error(\"Failed to write: %s %s\", file_path, exc)\n\n @staticmethod\n def yaml_load(file_path: Union[str, Path], encoding=DEFAULT_ENCODING) -> Any:\n \"\"\"Load dictionary from YAML file\"\"\"\n try:\n with open(file_path, \"r\", encoding=encoding) as f:\n return yaml.safe_load(f)\n except Exception as exc:\n logger.error(\"Failed to read %s %s\", file_path, exc)\n return None\n\n @staticmethod\n def yaml_dump(obj: Any, file_path: Union[str, Path], encoding=DEFAULT_ENCODING) -> None:\n \"\"\"Write dictionary to YAML file\"\"\"\n try:\n with open(file_path, \"w\", encoding=encoding) as f:\n yaml.dump(obj, f)\n except Exception as exc:\n logging.error(\"Failed to write: %s %s\", file_path, exc)\n\n @staticmethod\n def parse_python(source: str) -> List[Any]:\n \"\"\"Parse Python source and back to remove strings merge and line wrap\"\"\"\n with warnings.catch_warnings(record=True):\n warnings.simplefilter(\"error\", SyntaxWarning)\n src = ast.parse(source)\n result = ast.unparse(src).splitlines()\n return result\n\n PEM_CLEANING_PATTERN = re.compile(r\"\\\\[tnrvf]\")\n WHITESPACE_TRANS_TABLE = str.maketrans('', '', string.whitespace)\n\n @staticmethod\n def decode_base64(text: str, padding_safe: bool = False, urlsafe_detect=False) -> bytes:\n \"\"\"decode text to bytes with / without padding detect and urlsafe symbols\"\"\"\n value = text.translate(Util.WHITESPACE_TRANS_TABLE)\n if padding_safe:\n # workaround for binascii.Error: Excess padding not allowed\n value = value.rstrip('=')\n pad_num = 0x3 & len(value)\n if pad_num:\n value += '=' * (4 - pad_num)\n if urlsafe_detect and ('-' in value or '_' in value):\n decoded = base64.b64decode(value, altchars=b\"-_\", validate=True)\n else:\n decoded = base64.b64decode(value, validate=True)\n return decoded\n\n @staticmethod\n def load_pk(data: bytes, password: Optional[bytes] = None) -> Optional[PrivateKeyTypes]:\n \"\"\"Try to load private key from PKCS1, PKCS8 and PKCS12 formats\"\"\"\n with contextlib.suppress(Exception):\n # PKCS1, PKCS8 probes\n private_key = load_der_private_key(data, password)\n return private_key\n with contextlib.suppress(Exception):\n # PKCS12 probe\n private_key, _certificate, _additional_certificates = load_key_and_certificates(data, password)\n return private_key\n return None\n\n RANDOM_DATA = random.randbytes(20)\n\n @staticmethod\n def check_pk(pkey: PrivateKeyTypes) -> bool:\n \"\"\"Check private key with encrypt-decrypt random data\"\"\"\n if not pkey or isinstance(pkey, (EllipticCurvePublicKey, DSAPublicKey, Ed448PublicKey, Ed25519PublicKey,\n DHPublicKey, X448PublicKey, X25519PublicKey)):\n # These aren't the keys we're looking for\n return False\n if isinstance(pkey, (EllipticCurvePrivateKey, DSAPrivateKey, Ed448PrivateKey, Ed25519PrivateKey, DHPrivateKey,\n X448PrivateKey, X25519PrivateKey)):\n # One does not simply perform check the keys\n return True\n if isinstance(pkey, RSAPrivateKey):\n pd = padding.OAEP(mgf=padding.MGF1(algorithm=hashes.SHA1()), algorithm=hashes.SHA1(), label=None)\n ciphertext = pkey.public_key().encrypt(Util.RANDOM_DATA, padding=pd)\n refurb = pkey.decrypt(ciphertext, padding=pd)\n return bool(refurb == Util.RANDOM_DATA)\n logger.warning(\"Unknown private key type: %s\", type(pkey))\n return False\n\n @staticmethod\n def get_chunks(line_len: int) -> List[Tuple[int, int]]:\n \"\"\"Returns chunks positions for given line length\"\"\"\n # line length is over MAX_LINE_LENGTH already\n chunks = [(0, CHUNK_SIZE)]\n # case for oversize line\n next_offset = CHUNK_STEP_SIZE\n while line_len > next_offset:\n # the target is too long for single \"finditer\" - it will be scanned by chunks\n if line_len > next_offset + MAX_LINE_LENGTH:\n # the chunk is not the before last\n chunks.append((next_offset, next_offset + CHUNK_SIZE))\n next_offset += CHUNK_STEP_SIZE\n else:\n # the tail of line is between CHUNK_SIZE and MAX_LINE_LENGTH\n chunks.append((next_offset, line_len))\n break\n return chunks\n\n @staticmethod\n def subtext(text: str, pos: int, hunk_size: int) -> str:\n \"\"\"cut text symmetrically for given position or use remained quota to be fitted in 2x hunk_size\"\"\"\n # cut trailed whitespaces to obtain more informative data\n text = text.rstrip()\n if hunk_size <= pos:\n left_quota = 0\n left_pos = pos - hunk_size\n else:\n left_quota = hunk_size - pos\n left_pos = 0\n # skip leading whitespaces in result string\n for i in range(left_pos, pos):\n if text[i] in string.whitespace:\n left_quota += 1\n left_pos += 1\n else:\n break\n right_remain = len(text) - pos\n if hunk_size <= right_remain:\n right_quota = 0\n right_pos = pos + hunk_size + left_quota\n else:\n right_quota = hunk_size - right_remain\n right_pos = pos + hunk_size + left_quota\n if len(text) < right_pos:\n right_pos = len(text)\n if 0 < left_pos:\n left_pos -= right_quota\n if 0 > left_pos:\n left_pos = 0\n return text[left_pos:right_pos].rstrip()\n\n @staticmethod\n def get_excel_column_name(column_index: int) -> str:\n \"\"\"Converts index based column position into Excel style column name\"\"\"\n name = ''\n if isinstance(column_index, int):\n while 0 <= column_index:\n column_index, remain = divmod(column_index, 26)\n name = f\"{chr(ord('A') + remain)}{name}\"\n column_index -= 1\n return name\n" }, { "path": "docs/Makefile", "content": "# Minimal makefile for Sphinx documentation\n#\n\n# You can set these variables from the command line, and also\n# from the environment for the first two.\nSPHINXOPTS ?= -v -W\nSPHINXBUILD ?= sphinx-build\nSOURCEDIR = source\nBUILDDIR = build\n\n# Put it first so that \"make\" without argument is like \"make help\".\nhelp:\n\t@$(SPHINXBUILD) -M help \"$(SOURCEDIR)\" \"$(BUILDDIR)\" $(SPHINXOPTS) $(O)\n\n.PHONY: help Makefile\n\n# Catch-all target: route all unknown targets to Sphinx using the new\n# \"make mode\" option. $(O) is meant as a shortcut for $(SPHINXOPTS).\n%: Makefile\n\t@$(SPHINXBUILD) -M $@ \"$(SOURCEDIR)\" \"$(BUILDDIR)\" $(SPHINXOPTS) $(O)\n" }, { "path": "docs/README.md", "content": "# Documentation of CredSweeper\n\nThe directory is used for documentation of CredSweeper with using [sphinx](https://www.sphinx-doc.org/en/master/),\n\n## Workflow\n\nThere is applied custom documentation, so auto-generation might fail. Please, use auto-generation as reference.\nWith the command new sources might be updated (in /docs directory):\n\n```bash\nsphinx-apidoc --force --full --ext-autodoc ../credsweeper -o source/\n```\n\nEdit, then check with command:\n\n```bash\nmake html\n```\n" }, { "path": "docs/howto/how-to-contribute.md", "content": "# Contributing\n\nThank you for your interest in contributing to the CredSweeper tool!\n\nThe document covers the process for contributing to the CredSweeper code and documentation. Contributions may be as simple as typo corrections or as complex as new features.\n\n1. [Process for contributing](#process-for-contributing)\n\n 1. [Repository structure](#repository-structure)\n 2. [File Name](#file-name)\n 3. [Self Test & Verification](#self-test-and-verification)\n \n2. [How to PR](#how-to-pr)\n\n3. [DOs and DON'Ts](#dos-and-donts)\n\n## Process for contributing\n\nYou need a basic understanding of [Git and GitHub.com](https://guides.github.com/activities/hello-world/).\n\n**Step 1:** You can skip this step for small changes such as typo corrections. Open an [new issue](https://github.com/Samsung/CredSweeper/issues/new) describing what you want to do, such as change an existing code, functionality or create a new one.\n\nYou can also look at our [issues](https://github.com/Samsung/CredSweeper/issues) list and volunteer to work on the ones you're interested in.\n\n**Step 2:** Fork the [Samsung/CredSweeper](https://github.com/Samsung/CredSweeper/fork) repo and create a branch for your changes.\n\nFor small changes, you can use GitHub's web interface. Simply click the **Edit the file in your fork of this project** on the file you'd like to change.\nGitHub creates the new branch for you when you submit the changes.\nVCS(git) requirement: the branch MUST be forked after latest release.\n\n**Step 3:** Make the changes on this new branch.\n\nBe sure to follow the proper Python syntax. For more information, see the [style guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md).\nUse pre-commit hook with [yapf config file](https://github.com/Samsung/CredSweeper/blob/main/.style.yapf).\n\n\n### Repository structure\n\nAll new filters or another feature should be located in the appropriate directories. Also, for all new functionality, you need to create new positive and negative tests in the appropriate file and directory in ./tests/\n\n### File name\n\nFile names use the following rules:\n- Contain only lowercase letters, numbers, and underlines.\n- No spaces or punctuation characters. Use the underlines to separate words and numbers in the file name.\n- Use action verbs that are specific, such as develop, buy, build, troubleshoot. No -ing words.\n- No small words - don't include a, and, the, in, or, etc.\n- Keep file names reasonably short.\n\n### Self Test and Verification\n\nAfter updating CredSweeper code, please verify your change doesn't break the library. We suggest unit-tests using the pytest. You can easily run it with:\n ```bash\n python -m pytest\n ```\n\nPlease make it sure running all tests and no any fail case.\nRun all Actions in your fork before submitting the PR to the upstream and ensure all CI checks pass.\n\n**Step 4:** Submit a Pull Request (PR) from your branch to `Samsung/CredSweeper/main`.\n\nEach PR should usually address one issue at a time. The PR can modify one or multiple files. If you're addressing multiple fixes on different files, separate PRs are preferred.\n\nIf your PR is addressing an existing issue, add the `Fixes #Issue_Number` keyword to the commit message or PR description. That way, the issue is automatically closed when the PR is merged. For more information, see [Closing issues via commit messages](https://help.github.com/articles/closing-issues-via-commit-messages/).\n\nThe CredSweeper team will review your PR and let you know if there are any other updates/changes necessary in order to approve it.\n\n**Step 5:** Make any necessary updates to your branch as discussed with the team.\n\nThe maintainers will merge your PR into the main branch once feedback has been applied and your change is approved.\n\n\n### How to PR\n\n1. Fork form the original repository, https://github.com/Samsung/CredSweeper.\n (Ref. https://help.github.com/articles/fork-a-repo/)\n\n2. Type `git clone`, and then paste the URL you copied in 1. It will look like this, with your GitHub username instead of `YOUR-USERNAME`:\n\n ```bash\n git clone https://github.com/YOUR-USERNAME/CredSweeper.git\n ```\n \n3. Set to synchronize the original repository and the forked repository.\n\n ```bash\n git remote -v\n git remote add upstream https://github.com/Samsung/CredSweeper.git\n git remote -v\n ```\n \n4. Create a new branch on the forked repository or the local repository,\n and switch to the new branch.\n\n ```bash\n git checkout -b \n ```\n \n5. Install Yapf as a pre-commit hook with\n\n ``` bash\n pip install pre-commit\n pre-commit install\n ```\n \n6. Create a local commit.\n\n ```bash\n git status\n git add\n git commit -a\n ```\n\n7. Push the branch\n\n ```bash\n git push origin \n ```\n\n8. Open a pull request on https://github.com/Samsung/CredSweeper.\n\n All tests and checks MUST be passed\n - Codestyle check\n - Static analysis\n - Unit tests\n > - Development tests - use only linux and compatible version of packages. Code coverage is checked without test_app.py.\n > - Release tests - use Linux, Mac, Windows platform without version limitation.\n - Dynamic analysis (fuzzing)\n > Used Atheris framework to fuzzing various input. Code coverage is checked. In case of unsatisfied coverage - need to do new fuzzing or refactor fuzzer. \n - Benchmark\n > If your PR changes benchmark scores - the scores MUST be updated (cicd/benchmark.txt)\n \n9. Verify ActionTest after merge.\n > The test verifies integration CredSweeper to github action and points to main branch of main repo.\n\n## DOs and DON'Ts\n\nThe following list shows some guiding rules that you should keep in mind when you're contributing to the CredSweeper:\n\n- **DON'T** surprise us with large pull requests. Instead, file an issue and start a discussion so we can agree on a direction before you invest a large amount of time.\n- **DO** read the [style guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md) guideline.\n- **DO** create a separate branch on your fork before working on the changes.\n- **DO** follow the [GitHub Flow workflow](https://guides.github.com/introduction/flow/).\n- **DO** blog and tweet (or whatever) about your contributions, frequently!\n\n> **Note**\n>\n> you might notice that some of the topics are not currently following all the guidelines specified here and on the [style guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md) as well. We're working towards achieving consistency throughout the tool. Check the list of [open issues](https://github.com/Samsung/CredSweeper/issues?q=is%3Aissue+is%3Aopen) we're currently tracking for that specific goal.\n" }, { "path": "docs/make.bat", "content": "@ECHO OFF\r\n\r\npushd %~dp0\r\n\r\nREM Command file for Sphinx documentation\r\n\r\nif \"%SPHINXBUILD%\" == \"\" (\r\n\tset SPHINXBUILD=sphinx-build\r\n)\r\nset SOURCEDIR=source\r\nset BUILDDIR=build\r\n\r\nif \"%1\" == \"\" goto help\r\n\r\n%SPHINXBUILD% >NUL 2>NUL\r\nif errorlevel 9009 (\r\n\techo.\r\n\techo.The 'sphinx-build' command was not found. Make sure you have Sphinx\r\n\techo.installed, then set the SPHINXBUILD environment variable to point\r\n\techo.to the full path of the 'sphinx-build' executable. Alternatively you\r\n\techo.may add the Sphinx directory to PATH.\r\n\techo.\r\n\techo.If you don't have Sphinx installed, grab it from\r\n\techo.https://www.sphinx-doc.org/\r\n\texit /b 1\r\n)\r\n\r\n%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%\r\ngoto end\r\n\r\n:help\r\n%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%\r\n\r\n:end\r\npopd\r\n" }, { "path": "docs/requirements.txt", "content": "myst_parser[linkify]==4.0.1\nsphinx==8.1.3\nsphinx_rtd_theme==3.0.2\n" }, { "path": "docs/source/api.rst", "content": "API\n===\n\nThis part of the documentation covers all the interfaces of CredSweeper.\n\n.. toctree::\n :maxdepth: 2\n\n credsweeper\n credsweeper.common.rst\n credsweeper.config.rst\n credsweeper.credentials.rst\n credsweeper.deep_scanner.rst\n credsweeper.file_handler.rst\n credsweeper.filters.group.rst\n credsweeper.filters.rst\n credsweeper.logger.rst\n credsweeper.ml_model.rst\n credsweeper.rules.rst\n credsweeper.scanner.rst\n credsweeper.scanner.scan_type.rst\n credsweeper.utils.rst\n\n" }, { "path": "docs/source/apps_config.rst", "content": "CredSweeper Credential Analyzer Configuration\n=============================================\n\n.. literalinclude:: ../../credsweeper/secret/config.json\n :language: json\n :linenos:\n" }, { "path": "docs/source/conf.py", "content": "# Configuration file for the Sphinx documentation builder.\n#\n# For the full list of built-in configuration values, see the documentation:\n# https://www.sphinx-doc.org/en/master/usage/configuration.html\n\nimport os\nimport sys\n\nsys.path.insert(0, os.path.abspath('../..'))\ndi = os.path.abspath(os.pardir)\nremove_docs = di.strip('docs')\n\nfor r, d, f in os.walk(r\"{}credsweeper\".format(remove_docs)):\n sys.path.append(r)\n\n# -- Project information -----------------------------------------------------\n# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information\n\nproject = 'CredSweeper'\ncopyright = '2026, Samsung CredTeam'\nauthor = 'CredTeam'\n\nfrom credsweeper import __version__ as credsweeper_version\n\n# The short X.Y version\nversion = '.'.join(credsweeper_version.split('.')[0:2])\n\n# The full version, including alpha/beta/rc tags\nrelease = credsweeper_version\n\n# The master toctree document.\nmaster_doc = 'index'\n\n# -- General configuration ---------------------------------------------------\n# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration\n\n# Add any Sphinx extension module names here, as strings. They can be\n# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones.\nextensions = [\n 'sphinx.ext.autodoc',\n 'sphinx.ext.intersphinx',\n 'sphinx.ext.viewcode',\n 'sphinx.ext.todo',\n 'sphinx.ext.napoleon',\n 'myst_parser',\n]\n\nintersphinx_mapping = {\n 'python': ('https://docs.python.org/3/', None),\n 'numpy': ('https://numpy.org/doc/stable/', None),\n}\n\nmyst_enable_extensions = [\n \"amsmath\",\n \"attrs_inline\",\n \"colon_fence\",\n \"deflist\",\n \"dollarmath\",\n \"fieldlist\",\n \"html_admonition\",\n \"html_image\",\n \"linkify\",\n \"replacements\",\n \"smartquotes\",\n \"strikethrough\",\n \"substitution\",\n \"tasklist\",\n]\n\nsource_suffix = {\n '.rst': 'restructuredtext',\n '.txt': 'markdown',\n '.md': 'markdown',\n}\n\nmyst_heading_anchors = 3\n\n# Add any paths that contain templates here, relative to this directory.\ntemplates_path = ['_templates']\n\n# List of patterns, relative to source directory, that match files and\n# directories to ignore when looking for source files.\n# This patterns also effect to html_static_path and html_extra_path\nexclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']\n\n# The language for content autogenerated by Sphinx. Refer to documentation\n# for a list of supported languages.\n#\n# This is also used if you do content translation via gettext catalogs.\n# Usually you set \"language\" from the command line for these cases.\nlanguage = 'en'\n\n# The name of the Pygments (syntax highlighting) style to use.\npygments_style = 'sphinx'\n\n# If true, `todo` and `todoList` produce output, else they produce nothing.\n# https://www.sphinx-doc.org/en/master/usage/extensions/todo.html#configuration\ntodo_include_todos = True\n\n# -- Options for HTML output -------------------------------------------------\n# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output\n\nhtml_theme = 'sphinx_rtd_theme'\n\n# Add any paths that contain custom static files (such as style sheets) here,\n# relative to this directory. They are copied after the builtin static files,\n# so a file named \"default.css\" will overwrite the builtin \"default.css\".\nhtml_static_path = ['_static']\n\nhtml_theme_options = {\n 'logo_only': True, #\n 'navigation_depth': 3 #\n}\n\n# The name of an image file (relative to this directory) to place at the top of the sidebar.\nhtml_logo = 'https://raw.githubusercontent.com/Samsung/CredSweeper/main/docs/images/Logo.png'\n\nhtml_scaled_image_link = False\n\n# -- Options for HTMLHelp output ------------------------------------------\n\n# Output file base name for HTML help builder.\nhtmlhelp_basename = 'ci_doc'\n\n# -- Suppress unusual parts ... in json e.g.\nsuppress_warnings = ['misc.highlighting_failure']\n\n# -- Options for manual page output ---------------------------------------\n\n# One entry per manual page. List of tuples\n# (source start file, name, description, authors, manual section).\nman_pages = [(master_doc, 'ci', u'CI Documentation', [author], 1)]\n\nsys.path.append(os.path.dirname(__file__) + '/..')\n" }, { "path": "docs/source/credsweeper.common.rst", "content": "credsweeper.common package\n==========================\n\nSubmodules\n----------\n\ncredsweeper.common.constants module\n-----------------------------------\n\n.. automodule:: credsweeper.common.constants\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.common.keyword\\_checklist module\n--------------------------------------------\n\n.. automodule:: credsweeper.common.keyword_checklist\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.common.keyword\\_pattern module\n------------------------------------------\n\n.. automodule:: credsweeper.common.keyword_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.common\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.config.rst", "content": "credsweeper.config package\n==========================\n\nSubmodules\n----------\n\ncredsweeper.config.config module\n--------------------------------\n\n.. automodule:: credsweeper.config.config\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.config\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.credentials.rst", "content": "credsweeper.credentials package\n===============================\n\nSubmodules\n----------\n\ncredsweeper.credentials.augment\\_candidates module\n--------------------------------------------------\n\n.. automodule:: credsweeper.credentials.augment_candidates\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.credentials.candidate module\n----------------------------------------\n\n.. automodule:: credsweeper.credentials.candidate\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.credentials.candidate\\_group\\_generator module\n----------------------------------------------------------\n\n.. automodule:: credsweeper.credentials.candidate_group_generator\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.credentials.candidate\\_key module\n---------------------------------------------\n\n.. automodule:: credsweeper.credentials.candidate_key\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.credentials.credential\\_manager module\n--------------------------------------------------\n\n.. automodule:: credsweeper.credentials.credential_manager\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.credentials.line\\_data module\n-----------------------------------------\n\n.. automodule:: credsweeper.credentials.line_data\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.credentials\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.deep_scanner.rst", "content": "credsweeper.deep\\_scanner package\n=================================\n\nSubmodules\n----------\n\ncredsweeper.deep\\_scanner.abstract\\_scanner module\n--------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.abstract_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.byte\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.byte_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.bzip2\\_scanner module\n-----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.bzip2_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.crx\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.crx_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.csv\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.csv_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.deb\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.deb_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.deep\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.deep_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.docx\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.docx_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.eml\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.eml_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.encoder\\_scanner module\n-------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.encoder_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.gzip\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.gzip_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.html\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.html_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.jclass\\_scanner module\n------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.jclass_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.jks\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.jks_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.lang\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.lang_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.lzma\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.lzma_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.mxfile\\_scanner module\n------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.mxfile_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.patch\\_scanner module\n-----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.patch_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.pdf\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.pdf_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.pkcs\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.pkcs_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.png\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.png_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.pptx\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.pptx_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.rpm\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.rpm_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.rtf\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.rtf_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.sqlite3\\_scanner module\n-------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.sqlite3_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.strings\\_scanner module\n-------------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.strings_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.tar\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.tar_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.tmx\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.tmx_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.xlsx\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.xlsx_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.xml\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.xml_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.zip\\_scanner module\n---------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.zip_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.deep\\_scanner.zlib\\_scanner module\n----------------------------------------------\n\n.. automodule:: credsweeper.deep_scanner.zlib_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.deep_scanner\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.file_handler.rst", "content": "credsweeper.file\\_handler package\n=================================\n\nSubmodules\n----------\n\ncredsweeper.file\\_handler.abstract\\_provider module\n---------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.abstract_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.analysis\\_target module\n-------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.analysis_target\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.byte\\_content\\_provider module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.byte_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.content\\_provider module\n--------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.data\\_content\\_provider module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.data_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.descriptor module\n-------------------------------------------\n\n.. automodule:: credsweeper.file_handler.descriptor\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.diff\\_content\\_provider module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.diff_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.file\\_path\\_extractor module\n------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.file_path_extractor\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.files\\_provider module\n------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.files_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.patches\\_provider module\n--------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.patches_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.string\\_content\\_provider module\n----------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.string_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.struct\\_content\\_provider module\n----------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.struct_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.file\\_handler.text\\_content\\_provider module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.file_handler.text_content_provider\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.file_handler\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.filters.group.rst", "content": "credsweeper.filters.group package\n=================================\n\nSubmodules\n----------\n\ncredsweeper.filters.group.general\\_keyword module\n-------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.general_keyword\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.general\\_pattern module\n-------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.general_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.group module\n--------------------------------------\n\n.. automodule:: credsweeper.filters.group.group\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.password\\_keyword module\n--------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.password_keyword\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.token\\_pattern module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.group.token_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.url\\_credentials\\_group module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.url_credentials_group\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.weird\\_base36\\_token module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.weird_base36_token\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.group.weird\\_base64\\_token module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.group.weird_base64_token\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.filters.group\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.filters.rst", "content": "credsweeper.filters package\n===========================\n\nSubpackages\n-----------\n\n.. toctree::\n :maxdepth: 4\n\n credsweeper.filters.group\n\nSubmodules\n----------\n\ncredsweeper.filters.filter module\n---------------------------------\n\n.. automodule:: credsweeper.filters.filter\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.line\\_git\\_binary\\_check module\n---------------------------------------------------\n\n.. automodule:: credsweeper.filters.line_git_binary_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.line\\_specific\\_key\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.line_specific_key_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.line\\_uue\\_part\\_check module\n-------------------------------------------------\n\n.. automodule:: credsweeper.filters.line_uue_part_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_allowlist\\_check module\n--------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_allowlist_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_array\\_dictionary\\_check module\n----------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_array_dictionary_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_atlassian\\_token\\_check module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_atlassian_token_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_azure\\_token\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_azure_token_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_base32\\_data\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_base32_data_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_base64\\_data\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_base64_data_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_base64\\_encoded\\_pem\\_check module\n-------------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_base64_encoded_pem_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_base64\\_key\\_check module\n----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_base64_key_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_base64\\_part\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_base64_part_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_basic\\_auth\\_check module\n----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_basic_auth_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_blocklist\\_check module\n--------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_blocklist_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_camel\\_case\\_check module\n----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_camel_case_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_dictionary\\_keyword\\_check module\n------------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_dictionary_keyword_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_discord\\_bot\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_discord_bot_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_entropy\\_base32\\_check module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_entropy_base32_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_entropy\\_base36\\_check module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_entropy_base36_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_entropy\\_base64\\_check module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_entropy_base64_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_entropy\\_base\\_check module\n------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_entropy_base_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_file\\_path\\_check module\n---------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_file_path_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_github\\_check module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_github_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_grafana\\_check module\n------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_grafana_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_grafana\\_service\\_check module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_grafana_service_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_hex\\_number\\_check module\n----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_hex_number_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_jfrog\\_token\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_jfrog_token_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_json\\_web\\_key\\_check module\n-------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_json_web_key_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_json\\_web\\_token\\_check module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_json_web_token_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_last\\_word\\_check module\n---------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_last_word_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_length\\_check module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_length_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_method\\_check module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_method_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_morphemes\\_check module\n--------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_morphemes_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_not\\_allowed\\_pattern\\_check module\n--------------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_not_allowed_pattern_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_not\\_part\\_encoded\\_check module\n-----------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_not_part_encoded_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_number\\_check module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_number_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_pattern\\_check module\n------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_pattern_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_sealed\\_secret\\_check module\n-------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_sealed_secret_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_search\\_check module\n-----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_search_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_similarity\\_check module\n---------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_similarity_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_split\\_keyword\\_check module\n-------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_split_keyword_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_string\\_type\\_check module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_string_type_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_token\\_base32\\_check module\n------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_token_base32_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_token\\_base36\\_check module\n------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_token_base36_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_token\\_base64\\_check module\n------------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_token_base64_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_token\\_base\\_check module\n----------------------------------------------------\n\n.. automodule:: credsweeper.filters.value_token_base_check\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.filters.value\\_token\\_check module\n----------------------------------------------\n\n.. automodule:: credsweeper.filters.value_token_check\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.filters\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.logger.rst", "content": "credsweeper.logger package\n==========================\n\nSubmodules\n----------\n\ncredsweeper.logger.logger module\n--------------------------------\n\n.. automodule:: credsweeper.logger.logger\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.logger\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.ml_model.features.rst", "content": "credsweeper.ml\\_model.features package\n======================================\n\nSubmodules\n----------\n\ncredsweeper.ml\\_model.features.entropy\\_evaluation module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.entropy_evaluation\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.feature module\n---------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.feature\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.file\\_extension module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.file_extension\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.has\\_html\\_tag module\n----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.has_html_tag\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.is\\_secret\\_numeric module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.is_secret_numeric\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.length\\_of\\_attribute module\n-----------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.length_of_attribute\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.morpheme\\_dense module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.morpheme_dense\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.rule\\_name module\n------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.rule_name\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.rule\\_severity module\n----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.rule_severity\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.search\\_in\\_attribute module\n-----------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.search_in_attribute\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in module\n----------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_path module\n----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_path\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_postamble module\n---------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_postamble\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_preamble module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_preamble\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_transition module\n----------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_transition\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_value module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_value\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.ml\\_model.features.word\\_in\\_variable module\n--------------------------------------------------------\n\n.. automodule:: credsweeper.ml_model.features.word_in_variable\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.ml_model.features\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.ml_model.rst", "content": "credsweeper.ml\\_model package\n=============================\n\nSubpackages\n-----------\n\n.. toctree::\n :maxdepth: 4\n\n credsweeper.ml_model.features\n\nSubmodules\n----------\n\ncredsweeper.ml\\_model.ml\\_validator module\n------------------------------------------\n\n.. automodule:: credsweeper.ml_model.ml_validator\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.ml_model\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.rst", "content": "Credsweeper package\n===================\n\nCredSweeper\n-----------\n\n.. toctree::\n :maxdepth: 4\n\n.. automodule:: credsweeper.app\n :members:\n :undoc-members:\n :show-inheritance:\n\n" }, { "path": "docs/source/credsweeper.rules.rst", "content": "credsweeper.rules package\n=========================\n\nSubmodules\n----------\n\ncredsweeper.rules.rule module\n-----------------------------\n\n.. automodule:: credsweeper.rules.rule\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.rules\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.scanner.rst", "content": "credsweeper.scanner package\n===========================\n\nSubpackages\n-----------\n\n.. toctree::\n :maxdepth: 4\n\n credsweeper.scanner.scan_type\n\nSubmodules\n----------\n\ncredsweeper.scanner.scanner module\n----------------------------------\n\n.. automodule:: credsweeper.scanner.scanner\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.scanner\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.scanner.scan_type.rst", "content": "credsweeper.scanner.scan\\_type package\n======================================\n\nSubmodules\n----------\n\ncredsweeper.scanner.scan\\_type.multi\\_pattern module\n----------------------------------------------------\n\n.. automodule:: credsweeper.scanner.scan_type.multi_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.scanner.scan\\_type.pem\\_key\\_pattern module\n-------------------------------------------------------\n\n.. automodule:: credsweeper.scanner.scan_type.pem_key_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.scanner.scan\\_type.scan\\_type module\n------------------------------------------------\n\n.. automodule:: credsweeper.scanner.scan_type.scan_type\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.scanner.scan\\_type.single\\_pattern module\n-----------------------------------------------------\n\n.. automodule:: credsweeper.scanner.scan_type.single_pattern\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.scanner.scan_type\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/credsweeper.utils.rst", "content": "credsweeper.utils package\n=========================\n\nSubmodules\n----------\n\ncredsweeper.utils.hop\\_stat module\n----------------------------------\n\n.. automodule:: credsweeper.utils.hop_stat\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.utils.pem\\_key\\_detector module\n-------------------------------------------\n\n.. automodule:: credsweeper.utils.pem_key_detector\n :members:\n :undoc-members:\n :show-inheritance:\n\ncredsweeper.utils.util module\n-----------------------------\n\n.. automodule:: credsweeper.utils.util\n :members:\n :undoc-members:\n :show-inheritance:\n\nModule contents\n---------------\n\n.. automodule:: credsweeper.utils\n :members:\n :undoc-members:\n :show-inheritance:\n" }, { "path": "docs/source/develop.rst", "content": "Develop\n=======\n\nTests\n-----\n\nTo run all tests:\n\n.. code-block:: bash\n\n python -m pytest -s tests/\n\nBenchmark\n---------\n\nWe have a dataset for testing credential scanners that called `CredData `_. If you want to test CredSweeper with this dataset please check `here `_.\n" }, { "path": "docs/source/guide.rst", "content": "How To Use\n==========\n\nRun\n---\n\nGet all argument list:\n\n.. code-block:: bash\n\n python -m credsweeper --help\n\n\n.. code-block:: text\n\n usage: python -m credsweeper [-h]\n (--path PATH [PATH ...] | --diff_path PATH [PATH ...] | --export_config [PATH] | --export_log_config [PATH] | --git PATH)\n [--ref REF] [--rules PATH] [--severity SEVERITY]\n [--config PATH] [--log_config PATH]\n [--denylist PATH] [--find-by-ext]\n [--pedantic | --no-pedantic]\n [--depth POSITIVE_INT] [--no-filters] [--doc]\n [--ml_threshold THRESHOLD_OR_FLOAT_OR_ZERO]\n [--ml_batch_size POSITIVE_INT] [--ml_config PATH]\n [--ml_model PATH] [--ml_providers STR]\n [--jobs POSITIVE_INT] [--thrifty | --no-thrifty]\n [--skip_ignored] [--error | --no-error]\n [--save-json [PATH]] [--save-xlsx [PATH]]\n [--stdout | --no-stdout] [--color | --no-color]\n [--hashed | --no-hashed]\n [--subtext | --no-subtext] [--sort | --no-sort]\n [--log LOG_LEVEL] [--size_limit SIZE_LIMIT]\n [--banner] [--version]\n\n options:\n -h, --help show this help message and exit\n --path PATH [PATH ...]\n file or directory to scan\n --diff_path PATH [PATH ...]\n git diff file to scan\n --export_config [PATH]\n exporting default config to file (default:\n config.json)\n --export_log_config [PATH]\n exporting default logger config to file (default:\n log.yaml)\n --git PATH git repo to scan\n --ref REF scan git repo from the ref, otherwise - all branches\n were scanned (slow)\n --rules PATH path of rule config file (default:\n credsweeper/rules/config.yaml). severity:['critical',\n 'high', 'medium', 'low', 'info'] type:['keyword',\n 'pattern', 'pem_key', 'multi']\n --severity SEVERITY set minimum level for rules to apply ['critical',\n 'high', 'medium', 'low', 'info'](default:\n 'Severity.INFO', case insensitive)\n --config PATH use custom config (default: built-in)\n --log_config PATH use custom log config (default: built-in)\n --denylist PATH path to a plain text file with lines or secrets to\n ignore\n --find-by-ext find files by predefined extension\n --pedantic, --no-pedantic\n process files without extension (default: False)\n --depth POSITIVE_INT additional recursive search in data (experimental)\n --no-filters disable filters\n --doc document-specific scanning\n --ml_threshold THRESHOLD_OR_FLOAT_OR_ZERO\n setup threshold for the ml model. The lower the\n threshold - the more credentials will be reported.\n Allowed values: float between 0 and 1, or any of\n ['lowest', 'low', 'medium', 'high', 'highest']\n (default: medium)\n --ml_batch_size POSITIVE_INT, -b POSITIVE_INT\n batch size for model inference (default: 16)\n --ml_config PATH use external config for ml model\n --ml_model PATH use external ml model\n --ml_providers STR comma separated list of providers for onnx\n (CPUExecutionProvider is used by default)\n --jobs POSITIVE_INT, -j POSITIVE_INT\n number of parallel processes to use (default: 1)\n --thrifty, --no-thrifty\n clear objects after scan to reduce memory consumption\n (default: True)\n --skip_ignored parse .gitignore files and skip credentials from\n ignored objects\n --error, --no-error produce error code if credentials are found (default:\n False)\n --save-json [PATH] save result to json file (default: output.json)\n --save-xlsx [PATH] save result to xlsx file (default: output.xlsx)\n --stdout, --no-stdout\n print results to stdout (default: True)\n --color, --no-color print results with colorization (default: False)\n --hashed, --no-hashed\n line, variable, value will be hashed in output\n (default: False)\n --subtext, --no-subtext\n line text will be stripped in 128 symbols but value\n and variable are kept (default: False)\n --sort, --no-sort enable output sorting (default: False)\n --log LOG_LEVEL, -l LOG_LEVEL\n provide logging level of ['DEBUG', 'INFO', 'WARN',\n 'WARNING', 'ERROR', 'FATAL', 'CRITICAL', 'SILENCE']\n (default: 'warning', case insensitive)\n --size_limit SIZE_LIMIT\n set size limit of files that for scanning (eg. 1GB /\n 10MiB / 1000)\n --banner show version and crc32 sum of CredSweeper files at\n start\n --version, -V show program's version number and exit\n\n.. note::\n Validation by `ML model classifier `_ is used to reduce False Positives (by far), but might increase False negatives and execution time.\n You may change system sensitivity by modifying --ml_threshold argument. Increasing threshold will decrease the number of alerts.\n Setting `--ml_threshold 0` will turn ML off and will maximize the number of alerts.\n\n Typical False Positives: `password = \"template_password\"`\n\n.. note::\n CredSweeper includes an experimental `--depth` option that enables scanning with awareness of specific data formats, such as:\n\n - Compressed files (zip, gzip, bzip2, lzma)\n - Data containers (deb, tar, Docker images, pkcs12, jks)\n - Document rendering (pdf, xls, ods, xlsx, docx, pptx, tm7, mxfile)\n - Base64-encoded content\n - Structured text formats (HTML, XML, JSON, NDJSON, YAML, etc.) - keys and values are combined before analysis\n - Python sources - reformatting source code to plain code style to avoid cases which may hide values from patterns (\"AKIA\" \"EXAMPLE...\" -> \"AKIAEXAMPLE...\")\n\n **Remark:** The reported line number for a found credential with the option may not correspond to the original file. The `info` field provides context to help you understand how the credential was detected.\n\nGet output as JSON file with deep scan for docker image:\n\nPrepare dockerfile\n\n.. code-block:: docker\n\n FROM scratch\n ADD tests/samples /\n\nBuild, save and scan\n\n.. code-block:: bash\n\n docker build . --tag test_samples\n docker save test_samples --output test_samples.docker\n python -m credsweeper --path test_samples.docker --save-json output.json --depth 3\n\nReview the report file (output.json):\n\n.. code-block:: json\n\n [\n ...\n {\n \"rule\": \"Password\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.7925280332565308,\n \"line_data_list\": [\n {\n \"line\": \"password = 'cackle!'\",\n \"line_num\": 1,\n \"path\": \"test_samples.docker\",\n \"info\": \"FILE:test_samples.docker|TAR:blobs/sha256/82a4962c3cfebb62a42c2fd5c120ea0706a9ae66f52f71f957c052c873c60775|TAR:password.gradle|STRUCT|STRING:0|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n },\n ...\n ]\n\nGet CLI output only:\n\n.. code-block:: bash\n\n python -m credsweeper --path tests/samples/password.gradle\n\n\n.. code-block:: text\n\n rule: Password | severity: medium | confidence: moderate | ml_probability: 0.9149653911590576 | line_data_list: [path: tests/samples/password.gradle | line_num: 1 | value: 'cackle!' | line: 'password = \"cackle!\"']\n\n\nExclude outputs using CLI:\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nIf you want to remove some values from report (e.g. known public secrets):\ncreate text files with lines or values you want to remove and add it using `--denylist` argument.\nSpace-like characters at left and right will be ignored.\n\n.. code-block:: bash\n\n $ python -m credsweeper --path tests/samples/password.gradle --denylist list.txt\n Detected Credentials: 0\n Time Elapsed: 0.07523202896118164s\n $ cat list.txt\n cackle!\n password = \"cackle!\"\n\nExclude outputs using config:\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nEdit ``exclude`` part of the config file.\nDefault config can be generated using ``python -m credsweeper --export_config place_to_save.json``\nor can be found in ``credsweeper/secret/config.json``.\nSpace-like characters at left and right will be ignored.\n\n.. code-block:: json\n\n \"exclude\": {\n \"lines\": [\" password = \\\"cackle!\\\" \"],\n \"values\": [\"cackle!\"]\n }\n\nThen specify your config in CLI:\n\n.. code-block:: bash\n\n $ python -m credsweeper --path tests/samples/password.gradle --config my_cfg.json\n Detected Credentials: 0\n Time Elapsed: 0.07152628898620605s\n\nUse as a python library\n-----------------------\n\nMinimal example for scanning line list:\n\n.. code-block:: python\n\n from credsweeper import CredSweeper, StringContentProvider\n\n\n to_scan = [\"line one\", \"password='in_line_2'\"]\n cred_sweeper = CredSweeper()\n provider = StringContentProvider(to_scan)\n results = cred_sweeper.file_scan(provider)\n for r in results:\n print(r)\n\n.. code-block:: text\n\n rule: Password | severity: medium | confidence: moderate | ml_probability: 0.9857242107391357 | line_data_list: [line: 'password = \"cackle!\"' | line_num: 1 | path: | value: 'cackle!' | entropy_validation: BASE64STDPAD_CHARS 2.120590 False]\n\nMinimal example for scanning bytes:\n\n.. code-block:: python\n\n from credsweeper import CredSweeper, ByteContentProvider\n\n\n to_scan = b\"line one\\npassword='cackle!'\"\n cred_sweeper = CredSweeper()\n provider = ByteContentProvider(to_scan)\n results = cred_sweeper.file_scan(provider)\n for r in results:\n print(r)\n\n.. code-block:: text\n\n rule: Password | severity: medium | confidence: moderate | ml_probability: 0.9857242107391357 | line_data_list: [line: 'password = \"cackle!\"' | line_num: 2 | path: | value: 'cackle!' | entropy_validation: BASE64STDPAD_CHARS 2.120590 False]\n\n\nMinimal example for the ML validation:\n\n.. code-block:: python\n\n from credsweeper import CredSweeper, StringContentProvider, MlValidator, ThresholdPreset\n\n\n to_scan = [\"line one\", \"password='cackle!'\", \"secret='template'\"]\n cred_sweeper = CredSweeper()\n provider = StringContentProvider(to_scan)\n\n # You can select lower or higher threshold to get more or less reports respectively\n threshold = ThresholdPreset.medium\n validator = MlValidator(threshold=threshold)\n\n results = cred_sweeper.file_scan(provider)\n for candidate in results:\n # For each results detected by a CredSweeper, you can validate them using MlValidator\n is_credential, with_probability = validator.validate(candidate)\n if is_credential:\n print(candidate)\n\nNote that `\"secret='template'\"` is not reported due to failing check by the `MlValidator`.\n\n.. code-block:: text\n\n rule: Password | severity: medium | confidence: moderate | ml_probability: 0.9857242107391357 | line_data_list: [line: 'password = \"cackle!\"' | line_num: 2 | path: | value: 'cackle!' | entropy_validation: BASE64STDPAD_CHARS 2.120590 False]\n\nConfigurations\n--------------\n\n.. toctree::\n :maxdepth: 1\n\n apps_config\n\n.. toctree::\n :maxdepth: 1\n\n rules_config\n" }, { "path": "docs/source/how_to_contribute.rst", "content": "How To Contribute\n=================\n\n.. include:: ../howto/how-to-contribute.md\n :parser: myst_parser.sphinx_\n" }, { "path": "docs/source/index.rst", "content": ".. |CredSweeper_logo| image:: ../images/Logo.png\n :width: 100\n :alt: Alternative text\n\n|CredSweeper_logo|\n\nWelcome to CredSweeper's documentation!\n=======================================\n\nCredSweeper is a tool to detect credentials in any directories or files. CredSweeper could help users to detect\nunwanted exposure of credentials (such as personal information, token, passwords, api keys and etc) in advance.\nBy scanning lines, filtering, and using AI model as option, CredSweeper reports lines with possible credentials,\nwhere the line is, and expected type of the credential as a result.\n\nHow To Use\n==========\n\n.. toctree::\n :maxdepth: 2\n\n guide\n\nInstallation\n============\n\n.. toctree::\n :maxdepth: 2\n\n install\n\nDevelop\n=======\n\n.. toctree::\n :maxdepth: 2\n\n develop\n\n\nHow to Contribute\n=================\n\n.. toctree::\n :maxdepth: 2\n\n how_to_contribute\n\n\nOverall architecture\n====================\n\n.. toctree::\n :maxdepth: 2\n\n overall_architecture\n\n\nAPI Reference\n=============\n\nIf you are looking for information on a specific function, class or method, this part of the documentation is for you.\n\n.. toctree::\n :maxdepth: 2\n\n api\n\n\nIndices and tables\n==================\n\n* :ref:`genindex`\n* :ref:`modindex`\n* :ref:`search`\n" }, { "path": "docs/source/install.rst", "content": "Installation\n============\n\nCurrently `CredSweeper` requires the following prerequisites:\n\n* Python version 3.10, 3.11, 3.12\n\n.. note::\n We recommend to use credsweeper in a separate virtual enviroment. Some heave dependencies as Tensorflow\n might create a conflict with other dependencies othervise\n\nVia pip\n-------\n\n.. code-block:: bash\n\n pip install credsweeper\n\n.. note::\n If you didn't installed git, you may encounter the following error:\n \n .. code-block:: bash\n\n ...\n\n All git commands will error until this is rectified.\n\n This initial warning can be silenced or aggravated in the future by setting the\n $GIT_PYTHON_REFRESH environment variable. Use one of the following values:\n - quiet|q|silence|s|none|n|0: for no warning or exception\n - warn|w|warning|1: for a printed warning\n - error|e|raise|r|2: for a raised exception\n\n Example:\n export GIT_PYTHON_REFRESH=quiet\n\n If so, please install git.\n\n .. code-block:: bash\n\n sudo apt install git\n\n.. note::\n Allows to use `ML model classifier `_\n to validate credential candidates, but requires setup of additional packages: numpy, scikit-learn and tensorflow.\n\nVia git clone (dev install)\n---------------------------\n\n.. code-block:: bash\n\n git clone https://github.com/Samsung/CredSweeper.git\n cd CredSweeper\n # Annotate \"onnxruntime\" if you don't want to use the ML validation feature.\n pip install -qr requirements.txt\n\nPre-commit git hook\n---------------------------\n Install CredSweeper into system and copy ``pre-commit`` file in your ``.git/hooks`` repo.\n\n.. note::\n CredSweeper must be available in current python environment.\n\n.. note::\n pre-commit file context:\n.. code-block:: python\n\n #!/usr/bin/env python\n import io\n import subprocess\n import sys\n \n from credsweeper import CredSweeper\n from credsweeper.common.constants import DiffRowType\n from credsweeper.file_handler.patch_provider import PatchProvider\n \n \n def main() -> int:\n command = [\"git\", \"diff\", \"--cached\"]\n with subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE) as pipe:\n _stdout, _stderr = pipe.communicate()\n if pipe.returncode:\n print(str(_stdout), flush=True)\n print(str(_stderr), flush=True)\n print(f\"{command} EXIT CODE:{pipe.returncode}\", flush=True)\n return 1\n \n patch = io.BytesIO(_stdout)\n added = PatchProvider([patch], change_type=DiffRowType.ADDED)\n deleted = PatchProvider([patch], change_type=DiffRowType.DELETED)\n \n credsweeper = CredSweeper()\n \n if credsweeper.run(content_provider=deleted):\n print(f\"CREDENTIALS FOUND IN DELETED CONTENT\", flush=True)\n # return 1 # <<< UNCOMMENT THE LINE IF YOU WANT TO MANAGE DELETED CREDENTIALS\n \n if credsweeper.run(content_provider=added):\n print(f\"CREDENTIALS FOUND IN ADDED CONTENT\", flush=True)\n return 1\n \n return 0\n \n \n if __name__ == \"__main__\":\n sys.exit(main())\n\nOr use pre-commit with ``.pre-commit-config.yaml`` in your repo:\n\n.. code-block:: none\n\n repos:\n - repo: https://github.com/Samsung/CredSweeper\n rev: v1.10.6\n hooks:\n - id: CredSweeper\n\nInstall with: ``pre-commit install --install-hooks``\n" }, { "path": "docs/source/overall_architecture.rst", "content": "Overall Architecture\n====================\n\nCredSweeper is largely composed of 3 parts as follows. (Pre-processing_, Scan_, `ML validation`_)\n\n.. image:: https://raw.githubusercontent.com/Samsung/CredSweeper/main/docs/images/Architecture.png\n\nPre-processing\n--------------\n\nWhen paths to scan are entered, get the files in that paths and the files are excluded based on the list created by `config.json `_.\n\n**config.json**\n\n- exclude\n - pattern: Regex patterns to exclude scan.\n - containers: Extensions in lower case of container files which might be scan with --depth option\n - documents: Extensions in lower case of container files which might be scan with --doc and/or --depth option\n - extension: Extensions in lower case to exclude scan.\n - path: Paths to exclude scan.\n- source_ext: List of extensions for scanning categorized as source files.\n- source_quote_ext: List of extensions for scanning categorized as source files that using quote.\n- find_by_ext_list: List of extensions to detect only extensions.\n- check_for_literals: Bool value for whether to check line has string literal declaration or not.\n- line_data_output: List of attributes of `line_data `_ for output.\n- candidate_output: List of attributes of `candidate `_ for output.\n\n.. code-block:: text\n\n ...\n \"exclude\": {\n \"pattern\": [\n ...\n ],\n \"containers\": [\n \".gz\",\n \".zip\",\n ...\n ],\n \"documents\": [\n \".docx\",\n \".pdf\",\n ...\n ],\n \"extension\": [\n \".7z\",\n \".jpg\",\n ...\n ],\n \"path\": [\n \"/.git/\",\n \"/.idea/\",\n ...\n ]\n }\n ...\n\nScan\n----\n\n\nBasically, scanning is performed for each file path, and it is performed based on the Rule_. Scanning method differs from scan type of the Rule_, which is assigned when the Rule_ is generated. There are 3 scan types: `SinglePattern `_, `MultiPattern `_, and `PEMKeyPattern `_. Below is the description of the each scan type and its scanning method.\n\n- `SinglePattern `_\n - When : The Rule_ has only 1 pattern.\n - How : Check if a single line Rule pattern present in the line.\n- `MultiPattern `_\n - When : The Rule_ has 2 patterns.\n - How : Check if a line is a part of a multi-line credential and the remaining part exists within 10 lines below.\n- `PEMKeyPattern `_\n - When : The Rule_ type is `pem_key`.\n - How : Check if a line’s entropy is high enough and the line have no substring with 5 same consecutive characters. (like 'AAAAA')\n\nRule\n----\n\nEach Rule_ is dedicated to detect a specific type of credential, imported from `config.yaml `_ at the runtime.\n\n**config.yaml**\n\n.. code-block:: yaml\n\n ...\n - name: API\n severity: medium\n confidence: moderate\n type: keyword\n values:\n - api\n filter_type: GeneralKeyword\n use_ml: true\n min_line_len: 11\n required_substrings:\n - api\n target:\n - code\n ...\n\n**Rule Attributes** \n\n- severity\n - `Severity `_\n\n .. code-block:: python\n\n ...\n class Severity(Enum):\n CRITICAL = \"critical\"\n HIGH = \"high\"\n MEDIUM = \"medium\"\n LOW = \"low\"\n ...\n\n- confidence\n - `Confidence `_ - The manually configured value indicates the confidence that the found candidate could be the credential type.\n\n .. code-block:: python\n\n ...\n class Confidence(Enum):\n STRONG = \"strong\"\n MODERATE = \"moderate\"\n WEAK = \"weak\"\n ...\n\n- type\n - `RuleType `_\n \n .. code-block:: python\n\n ...\n class RuleType(Enum):\n KEYWORD = \"keyword\"\n PATTERN = \"pattern\"\n PEM_KEY = \"pem_key\"\n MULTI = \"multi\"\n ...\n\n- values\n - keyword : The keywords you want to detect. If you want to detect multiple keywords, you can write them as follows : `password|passwd|pwd`.\n - pattern : The patterns you want to detect. For more accurate detection, it is recommended to specify `?P` in the patterns : `(?PAIza[0-9A-Za-z\\-_]{35})`.\n - pem_key : Specific rule to find multiline PEM private keys.\n - multi : Two patterns you want to detect. Candidate will be found only if second pattern matched nearby.\n- filter_type\n - The type of the Filter_ group you want to apply. Filter_ groups implemented are as follows: `GeneralKeyword `_, `GeneralPattern `_, `PasswordKeyword `_, and `UrlCredentials `_.\n- use_ml\n - The attribute to set whether to perform ML validation. If true, ML validation will be performed. If false - ml_probability will be set to None in report.\n- min_line_len\n - drop too short stripped lines before text search to increase performance\n- required_substrings\n - any strings has to be found in a line before regex search to increase performance\n- target\n - code : The rule will be applied without --doc option\n - doc : The rule will be applied with --doc option\n\nFilter\n------\n\nCheck the detected candidates from the formal step. If a candidate is caught by the Filter_, it is removed from the candidates set.\nThere are 21 filters and 4 filter groups. Filter_ group is a set of Filter_s, which is designed to use many Filter_s effectively at the same time.\n\nML validation\n-------------\n\nCredSweeper provides pre-trained ML models to filter false credential lines.\n`ML validation` is on by the default and its sensitivity can be adjusted using ``--ml_threshold``:\n\n.. code-block:: text\n\n --ml_threshold THRESHOLD_OR_FLOAT_OR_ZERO\n setup threshold for the ml model.\n The lower the threshold - the more credentials will be reported.\n Allowed values: float between 0 and 1, or any of ['lowest', 'low', 'medium', 'high', 'highest']\n (default: medium)\n\nAnd ML can be fully disable by setting ``--ml_threshold 0``\n\n.. code-block:: bash\n\n python -m credsweeper --ml_threshold 0 ...\n\nOur ML model architecture is a combination of Bidirectional LSTM with additional handcrafted features.\nIt uses first 80 characters from the potential credential value and variable (if available), 160 characters from line around the value and configurable handcrafted features to decide if it's a real credential or not.\n\nExample (file leaked_cred.py):\n\n.. code-block:: python\n\n my_db_password = \"NUU423cds\"\n\nSteps:\n\n1. Regular expression extracts ```NUU423cds``` as a secret value, ```my_db_password``` as a variable, and ```my_db_password = \"NUU423cds\"``` as whole line\n2. Handcrafted feature classes instantiated from classes in `features.py `_ using `model_config.json `_. Instantiation process can be checked at `ml_validator.py#L46 `_. Features include: ``` ``` character in line: yes/no, ```(``` character in line: yes/no, file extension is ```.c```: yes/no, etc.\n3. Handcrafted features from step 2 used on line, value, variable, and filename to get feature vector of length 91\n4. ```NUU423cds``` Configurable character set is applied + 1 padding character + 1 special character for all other symbols. Padded line than `one-hot encoded `_. Link to corresponding code: `MlValidator.encode `_\n5. Padded line from step 4 inputted to Bidirectional LSTM of value. The same encodings are performed for variable and line. LSTM produce 3 single vectors of lengths 80, 80, 160 as outputs\n6. LSTM outputs and handcrafted features concatenated into a single vector\n7. The vector from step 6 is fed into a stack of two sequential Dense layers, each with the number of output units equal to the number of input units.\n8. Last layer outputs float value in range 0-1 with estimated probability of line being a real credential\n9. Predicted probability compared to the threshold (see `--ml_threshold` CLI option) and credential reported if predicted probability is greater\n\n.. image:: https://raw.githubusercontent.com/Samsung/CredSweeper/main/docs/images/Model_with_features.png\n\nAdditional:\n\n- Handcrafted features are based on the rules described in `\"Secrets in Source Code\" publication `_.\n\n.. code-block:: text\n\n @INPROCEEDINGS{9027350,\n author={Saha, Aakanksha and Denning, Tamara and Srikumar, Vivek and Kasera, Sneha Kumar}, \n booktitle={2020 International Conference on COMmunication Systems NETworkS (COMSNETS)}, \n title={Secrets in Source Code: Reducing False Positives using Machine Learning}, \n year={2020}, \n pages={168-175}, \n doi={10.1109/COMSNETS48256.2020.9027350}\n }\n\n- Mapping between text threshold values and float can be found at `model_config.json#L2 `_. Values are based on F-0.25, F-0.5, F-1, F-2 and F-4 scores on `CredData test `_\n" }, { "path": "docs/source/rules_config.rst", "content": "Rules Configuration\n===================\n\n.. literalinclude:: ../../credsweeper/rules/config.yaml\n :language: yaml\n :linenos:\n" }, { "path": "experiment/README.md", "content": "# Train credential detection model\n\nThis code will allow you to retrain model on the CredData dataset\n\n## Preparation\n\n- Make sure that you are using Python 3.10 or higher\n\n- Download CredData dataset\n\n```bash\ngit clone https://github.com/Samsung/CredData\ncd CredData\npython download_data.py --data_dir data\n```\n\n- Go back to `CredSweeper/experiment` directory\n- Install the additional requirements\n\n```bash\npip install -r requirements.txt\n``` \n\n- Make sure that `credsweeper` in the `PYTHONPATH`. You can add it with \n\n```bash\nexport PYTHONPATH=:$PYTHONPATH\n``` \n\nExample:\n\n```bash\nexport PYTHONPATH=/home/user/code/CredSweeper:$PYTHONPATH\n``` \n\n## Run\n\n- Launch the experiment with\n\n```bash\npython main.py --data -j \n```\n\nExample:\n\n```bash\npython main.py --data /home/user/datasets/CredData -j 16\n``` \n\n- Resulting model will be saved to `results/ml_model_at-`.\nYou now can convert the model to onnx:\n\n```bash\npython -m tf2onnx.convert --saved-model results/ml_model_at-20240225_111951 --output ../credsweeper/ml_model/ml_model.onnx --verbose\n```\n\n" }, { "path": "experiment/__init__.py", "content": "" }, { "path": "experiment/data_loader.py", "content": "import contextlib\nimport json\nimport os\nimport pathlib\nfrom copy import deepcopy\nfrom functools import cache\nfrom typing import Tuple, Dict, Set, Any\n\nimport numpy as np\nimport pandas as pd\nfrom colorama import Fore, Style, Back\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.utils.util import Util\n\n# path, line, val_start, val_end\nidentifier = Tuple[str, int, int, int]\n\n\ndef transform_to_meta_path(file_path: pathlib.Path):\n \"\"\"Transform any path to '......./data/xxxxxxxx/[type]...../yyyyyyyy.ext' to find in meta markup\"\"\"\n file_path = pathlib.Path(file_path).as_posix()\n path_list = file_path.split('/')\n assert path_list.count(\"data\") == 1, file_path # only one \"data\" directory allowed\n meta_path = \"\"\n for n, x in enumerate(path_list):\n if x == \"data\":\n meta_path = '/'.join(path_list[n:])\n break\n assert meta_path, f\"data dir was not found in {file_path}\" # just extra check\n return meta_path\n\n\ndef read_detected_data(file_path: pathlib.Path) -> Dict[identifier, Dict]:\n print(f\"Reading detections from {file_path}\", flush=True)\n with open(file_path) as f:\n detections = json.load(f)\n\n detected_lines = {}\n\n for cred in detections:\n rule_name = cred[\"rule\"]\n # skip not ML values like private keys and so on. Unsupported for ml train. \"use_ml\" rules ONLY\n assert 0 < len(cred[\"line_data_list\"]), cred # at least, one line_data_list must present\n line_data = deepcopy(cred[\"line_data_list\"][0])\n line_data.pop(\"entropy\")\n line_data.pop(\"info\")\n line_data[\"line\"] = None # will be read during join_label with data for ML input only\n meta_path = transform_to_meta_path(line_data[\"path\"])\n line_data[\"path\"] = meta_path\n line_data[\"RuleName\"] = [rule_name]\n\n index = meta_path, line_data[\"line_num\"], line_data[\"value_start\"], line_data[\"value_end\"]\n if index not in detected_lines:\n detected_lines[index] = line_data\n else:\n detected_lines[index][\"RuleName\"].append(rule_name)\n\n print(f\"Detected {len(detected_lines)} unique lines!\", flush=True)\n print(f\"{len(detections)} detections in total\", flush=True)\n\n return detected_lines\n\n\ndef read_metadata(meta_dir: str) -> Dict[identifier, Dict]:\n print(f\"Reading meta from {meta_dir}\", flush=True)\n meta_lines = {}\n j = 0\n\n for file_path in os.listdir(meta_dir):\n csv_file = os.path.join(meta_dir, file_path)\n if not file_path.endswith(\".csv\"):\n print(f\"skip garbage: {csv_file}\", flush=True)\n continue\n try:\n df = pd.read_csv(csv_file,\n dtype={\n \"RepoName\": str,\n \"GroundTruth\": str,\n \"Category\": str,\n \"LineStart\": \"Int64\",\n \"LineEnd\": \"Int64\",\n \"ValueStart\": \"Int64\",\n \"ValueEnd\": \"Int64\",\n })\n except Exception as exc:\n print(csv_file, exc, flush=True)\n raise\n # Int64 is important to change with NaN\n df[\"LineStart\"] = df[\"LineStart\"].fillna(-1).astype(int)\n df[\"LineEnd\"] = df[\"LineEnd\"].fillna(-1).astype(int)\n df[\"ValueStart\"] = df[\"ValueStart\"].fillna(-1).astype(int)\n df[\"ValueEnd\"] = df[\"ValueEnd\"].fillna(-1).astype(int)\n # all templates are false\n df.loc[df[\"GroundTruth\"] != 'T', \"GroundTruth\"] = 'F'\n for _, row in df.iterrows():\n j += 1\n if row[\"LineStart\"] != row[\"LineEnd\"] \\\n or all(x in [\"AWS Multi\", \"Google Multi\"] for x in row[\"Category\"].split(':')):\n # print(f\"WARNING: skip not ml category {row['FilePath']},{line_start},{line_end}\"\n # f\",{row['GroundTruth']},{row['Category']}\", flush=True)\n continue\n assert 'F' == row[\"GroundTruth\"] or 'T' == row[\"GroundTruth\"] and 0 <= row[\"ValueStart\"], row\n\n meta_path = transform_to_meta_path(row[\"FilePath\"])\n index = meta_path, row['LineStart'], row['ValueStart'], row['ValueEnd']\n if index not in meta_lines:\n row_data = row.to_dict()\n row_data[\"Used\"] = False\n row_data[\"FilePath\"] = meta_path\n meta_lines[index] = row_data\n else:\n print(\n f\"WARNING: {index} already in meta_lines {row['GroundTruth']} {row['Category']}\"\n f\"\\n{meta_lines[index]}\",\n flush=True)\n\n print(f\"Loaded {len(meta_lines)} lines from meta of {j} total\", flush=True)\n\n return meta_lines\n\n\ndef get_colored_line(line_data: Dict[str, Any]) -> str:\n val_start = int(line_data['value_start'])\n val_end = int(line_data['value_end'])\n colored_line = line_data['line'][:val_start] \\\n + Fore.LIGHTYELLOW_EX \\\n + line_data['line'][val_start:val_end] \\\n + Style.RESET_ALL \\\n + line_data['line'][val_end:]\n\n with contextlib.suppress(Exception):\n var_start = int(line_data['variable_start'])\n var_end = int(line_data['variable_end'])\n if 0 <= var_start < var_end:\n colored_line = colored_line[:var_start] \\\n + Fore.LIGHTBLUE_EX \\\n + colored_line[var_start:var_end] \\\n + Style.RESET_ALL \\\n + colored_line[var_end:]\n\n colored_sub_line = Util.subtext(colored_line, line_data['value_start'], ML_HUNK)\n return f\"{colored_sub_line}{Style.RESET_ALL}\"\n\n\ndef join_label(detected_data: Dict[identifier, Dict], meta_data: Dict[identifier, Dict],\n cred_data_location: str) -> pd.DataFrame:\n\n @cache\n def read_text(path) -> list[str]:\n with open(path, \"r\", encoding=\"utf8\") as f:\n return f.read().replace(\"\\r\\n\", '\\n').replace('\\r', '\\n').split('\\n')\n\n positive_lines = set((x[0], x[1]) for x, y in meta_data.items() if 'T' == y[\"GroundTruth\"])\n values = []\n detected_rules: Set[str] = set()\n for index, line_data in detected_data.items():\n for i in line_data[\"RuleName\"]:\n detected_rules.add(i)\n text = read_text(f'{cred_data_location}/{line_data[\"path\"]}')\n line = text[line_data[\"line_num\"] - 1]\n line_data[\"line\"] = line\n if not line_data[\"value\"]:\n print(f\"WARNING: empty value\\n{line_data}\", flush=True)\n continue\n label = False\n if markup := meta_data.get(index):\n # it means index in meta_data with exactly match\n if 'T' == markup[\"GroundTruth\"]:\n label = True\n markup[\"Used\"] = True\n markup_rules = markup[\"Category\"].split(':')\n if not set(markup_rules).intersection(set(line_data[\"RuleName\"])):\n print(f\"1.CHECK CATEGORIES\\n{markup_rules}, {line_data['RuleName']}\\n{str(markup)}\" +\n get_colored_line(line_data),\n flush=True)\n elif markup := meta_data.get((index[0], index[1], index[2], -1)):\n # perhaps, the line has only start markup - so value end position is -1\n if 'T' == markup[\"GroundTruth\"]:\n label = True\n markup[\"Used\"] = True\n markup_rules = markup[\"Category\"].split(':')\n if not set(markup[\"Category\"].split(':')).intersection(set(line_data[\"RuleName\"])):\n print(f\"2.CHECK CATEGORIES\\n{markup_rules}, {line_data['RuleName']}\\n{str(markup)}\" +\n get_colored_line(line_data),\n flush=True)\n elif markup := meta_data.get((index[0], index[1], -1, -1)):\n # perhaps, the line has false markup - so value start-end position is -1, -1\n if 'T' == markup[\"GroundTruth\"]:\n raise RuntimeError(f\"ERROR: markup {markup} cannot be TRUE\\n{line_data}\")\n markup[\"Used\"] = True\n markup_rules = markup[\"Category\"].split(':')\n if not set(markup[\"Category\"].split(':')).intersection(set(line_data[\"RuleName\"])):\n print(f\"3.CHECK CATEGORIES\\n{markup_rules}, {line_data['RuleName']}\\n{str(markup)}\" +\n get_colored_line(line_data),\n flush=True)\n elif (index[0], index[1]) in positive_lines:\n print(f\"WARNING: {index} is not in meta!!! {Fore.LIGHTRED_EX}CHECK THE NEGATIVE CASE{Style.RESET_ALL}\\n\" +\n get_colored_line(line_data),\n flush=True)\n else:\n print(f\"WARNING: {index} is not in meta!!! IT WILL BE USED AS NEGATIVE CASE\\n\" +\n get_colored_line(line_data),\n flush=True)\n # check the value in detected data\n assert line[line_data[\"value_start\"]:line_data[\"value_end\"]] == line_data[\"value\"], (\n line_data, line[line_data[\"value_start\"]:line_data[\"value_end\"]], line_data[\"value\"])\n # todo: variable input has to be markup in meta too, or/and new feature \"VariableExists\" created ???\n line_data[\"GroundTruth\"] = label\n # auxiliary field for model_config_preprocess\n # no extra memory usage due the dataframe is deleted before train\n line_data[\"ext\"] = Util.get_extension(line_data[\"path\"])\n values.append(line_data)\n\n all_meta_found = True\n for markup in meta_data.values():\n if 'T' == markup[\"GroundTruth\"] and not markup[\"Used\"]:\n for markup_rule in markup[\"Category\"].split(':'):\n if markup_rule in detected_rules:\n if all_meta_found:\n # print header of the markup once\n print(f\"{Back.MAGENTA}{Fore.BLACK}WARNING: Not all TRUE meta found!{Style.RESET_ALL}\",\n flush=True)\n print(','.join(markup.keys()), flush=True)\n all_meta_found = False\n print(','.join(str(x) for x in markup.values()), flush=True)\n text = read_text(f'{cred_data_location}/{markup[\"FilePath\"]}')\n line = text[markup[\"LineStart\"] - 1]\n if 0 <= markup[\"ValueStart\"] and 0 <= markup[\"ValueEnd\"]:\n line = line[:markup[\"ValueStart\"]] \\\n + Fore.LIGHTGREEN_EX \\\n + line[markup[\"ValueStart\"]:markup[\"ValueEnd\"]] \\\n + Style.RESET_ALL \\\n + line[markup[\"ValueEnd\"]:]\n elif 0 <= markup[\"ValueStart\"]:\n line = line[:markup[\"ValueStart\"]] \\\n + Fore.LIGHTGREEN_EX \\\n + line[markup[\"ValueStart\"]:] \\\n + Style.RESET_ALL\n print(line, flush=True)\n break\n read_text.cache_clear()\n df = pd.DataFrame(values)\n print(f\"Initial full dataset: {len(df)} items\\n{df.memory_usage(deep=True)}\", flush=True)\n df = df.drop_duplicates(subset=[\"line\", \"variable\", \"value\", \"path\"])\n print(f\"Full dataset: {len(df)} items after drop duplicates\\n{df.memory_usage(deep=True)}\", flush=True)\n return df\n\n\ndef get_y_labels(df: pd.DataFrame) -> np.ndarray:\n true_cases = np.array(df[\"GroundTruth\"], dtype=np.float32)\n return true_cases\n" }, { "path": "experiment/evaluate_model.py", "content": "from typing import List\n\nimport numpy as np\nfrom keras import Model # type: ignore\nfrom sklearn.metrics import f1_score, precision_score, recall_score, log_loss, accuracy_score\n\n\ndef evaluate_model(thresholds: dict, keras_model: Model, x_data: List[np.ndarray], y_label: np.ndarray):\n \"\"\"Evaluate Keras model with printing scores\n\n Args:\n thresholds: dict of credsweeper thresholds\n keras_model: fitted keras model\n x_data: List of np.arrays. Number and shape depends on model\n y_label: expected result\n\n \"\"\"\n predictions_proba = keras_model.predict(x_data, verbose=2).ravel()\n for name, threshold in thresholds.items():\n predictions = (predictions_proba > threshold)\n accuracy = accuracy_score(y_label, predictions)\n precision = precision_score(y_label, predictions)\n recall = recall_score(y_label, predictions)\n loss = log_loss(y_label, predictions)\n f1 = f1_score(y_label, predictions)\n print(\n f\"{name}: {threshold:0.6f}, \"\n f\"accuracy: {accuracy:0.6f}, \"\n f\"precision:{precision:0.6f}, \"\n f\"recall: {recall:0.6f}, \"\n f\"loss: {loss:0.6f}, \"\n f\"F1:{f1:0.6f}\",\n flush=True)\n" }, { "path": "experiment/features.py", "content": "from typing import Tuple, Union\n\nimport numpy as np\nimport pandas as pd\n\nfrom credsweeper.common.constants import Severity, ML_HUNK\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.ml_model.ml_validator import MlValidator\nfrom credsweeper.utils.util import Util\n\n\nclass CustomLineData(LineData):\n \"\"\"Object that allows to create LineData from scanner results\"\"\"\n\n def __init__(\n self, #\n line: str, #\n value: str, #\n line_num: int, #\n path: str, #\n variable: str, #\n value_start: int, #\n value_end: int, #\n variable_start: int, #\n variable_end: int, #\n ) -> None:\n self.line: str = line\n self.line_num: int = line_num\n self.path: str = path\n self.value = value\n self.file_type = Util.get_extension(path)\n self.variable = variable\n self.value_start = value_start\n self.value_end = value_end if value_start < value_end else value_start + len(value)\n self.variable_start = variable_start\n self.variable_end = variable_end\n\n\ndef get_candidates(line_data: dict):\n \"\"\"Get list of candidates. 1 candidate for each rule that detected this line\"\"\"\n ld = CustomLineData(line=line_data[\"line\"],\n value=line_data[\"value\"],\n line_num=line_data[\"line_num\"],\n path=line_data[\"path\"],\n variable=line_data[\"variable\"],\n value_start=line_data[\"value_start\"],\n value_end=line_data[\"value_end\"],\n variable_start=line_data[\"variable_start\"],\n variable_end=line_data[\"variable_end\"])\n candidates = []\n for rule in line_data[\"RuleName\"]:\n candidates.append(\n Candidate(\n line_data_list=[ld],\n patterns=[],\n rule_name=rule,\n severity=Severity.MEDIUM,\n use_ml=True,\n ))\n return candidates\n\n\ndef get_features(line_data: Union[dict, pd.Series],\n ml_validator: MlValidator) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n \"\"\"Get features from a single detection using CredSweeper.MlValidator module\"\"\"\n\n candidates = get_candidates(line_data)\n\n line_input = ml_validator.encode_line(line_data[\"line\"], line_data[\"value_start\"])\n if variable := line_data[\"variable\"]:\n if len(variable) > ML_HUNK:\n variable = variable[:ML_HUNK]\n variable_input = ml_validator.encode_value(variable)\n else:\n variable_input = ml_validator.encode_value('')\n\n if value := line_data[\"value\"]:\n if len(value) > ML_HUNK:\n value = value[:ML_HUNK]\n value_input = ml_validator.encode_value(value)\n else:\n raise RuntimeError(f\"Empty value is not allowed {line_data}\")\n\n line = line_data[\"line\"]\n assert line[line_data[\"value_start\"]:].startswith(line_data[\"value\"]), line_data\n\n extracted_features = ml_validator.extract_features(candidates)\n\n return line_input, variable_input, value_input, extracted_features\n\n\ndef prepare_data(df: pd.DataFrame) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:\n \"\"\"Get features from a DataFrame detection using CredSweeper.MlValidator module\"\"\"\n\n ml_validator = MlValidator(0.5) # MLValidator object loads config (MAY be updated!) with features\n\n x_size = len(df)\n x_line_input = np.zeros(shape=[x_size, MlValidator.MAX_LEN, ml_validator.num_classes], dtype=np.float32)\n x_variable_input = np.zeros(shape=[x_size, ML_HUNK, ml_validator.num_classes], dtype=np.float32)\n x_value_input = np.zeros(shape=[x_size, ML_HUNK, ml_validator.num_classes], dtype=np.float32)\n # features size preprocess to calculate the dimension automatically\n features = get_features( #\n line_data={ #\n \"path\": \"\", #\n \"line_num\": 1, #\n \"line\": \"const API=123;\", #\n \"value\": \"123\", #\n \"value_start\": 10, #\n \"value_end\": 13, #\n \"variable\": \"API\", #\n \"variable_start\": 6, #\n \"variable_end\": 9, #\n \"RuleName\": [\"API\"], #\n }, #\n ml_validator=ml_validator)\n features_size = features[3].shape[1]\n print(f\"Features size: {features_size}\", flush=True)\n x_features = np.zeros(shape=[x_size, features_size], dtype=np.float32)\n n = 0\n for i, row in df.iterrows():\n assert bool(row[\"line\"]) and bool(row[\"value\"]), row\n line_input, variable_input, value_input, extracted_features = get_features(row, ml_validator)\n x_line_input[n] = line_input\n x_variable_input[n] = variable_input\n x_value_input[n] = value_input\n x_features[n] = extracted_features\n n += 1\n return x_line_input, x_variable_input, x_value_input, x_features\n" }, { "path": "experiment/hyperparameters.py", "content": "HP_DICT = {\n \"line_lstm_dropout_rate\": ((0.4, 0.5, 0.01), 0.47),\n \"variable_lstm_dropout_rate\": ((0.4, 0.5, 0.01), 0.42),\n \"value_lstm_dropout_rate\": ((0.4, 0.5, 0.01), 0.47),\n \"dense_a_drop\": ((0.0, 0.3, 0.01), 0.21),\n \"dense_b_drop\": ((0.0, 0.3, 0.01), 0.23),\n}\n" }, { "path": "experiment/log_callback.py", "content": "import datetime\n\nimport psutil\nfrom keras.src.callbacks import Callback\n\n\nclass LogCallback(Callback):\n\n def __init__(self):\n super().__init__()\n\n @staticmethod\n def get_memory_info():\n process = psutil.Process()\n memory_info = process.memory_info()\n return str(memory_info)\n\n def on_epoch_end(self, epoch, logs=None):\n print(str(datetime.datetime.now()), flush=True)\n print(f\"{epoch + 1}:{self.get_memory_info()}\", flush=True)\n print(logs, flush=True)\n" }, { "path": "experiment/main.py", "content": "import os\nimport random\nimport sys\nfrom argparse import ArgumentParser, BooleanOptionalAction\n\nfrom train import train\n\n\ndef main(argv) -> int:\n parser = ArgumentParser()\n parser.add_argument(\"-d\",\n \"--data\",\n nargs=\"?\",\n help=\"CredData location\",\n dest=\"cred_data_location\",\n metavar=\"PATH\",\n required=True)\n parser.add_argument(\"-j\",\n \"--jobs\",\n help=\"number of parallel processes to use (default: 4)\",\n default=4,\n dest=\"jobs\",\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"-e\",\n \"--epochs\",\n help=\"maximal epochs to train (default: 100)\",\n default=100,\n dest=\"epochs\",\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"-b\",\n \"--batch_size\",\n help=\"batch size (default: 256)\",\n default=256,\n dest=\"batch_size\",\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"-p\",\n \"--patience\",\n help=\"early stopping patience (default: 5)\",\n default=5,\n dest=\"patience\",\n metavar=\"POSITIVE_INT\")\n parser.add_argument(\"--doc\", help=\"use doc target\", dest=\"doc_target\", action=BooleanOptionalAction, default=False)\n parser.add_argument(\"--tuner\",\n help=\"use keras tuner\",\n dest=\"use_tuner\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--eval-test\",\n help=\"evaluate model for test dataset\",\n dest=\"eval_test\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--eval-train\",\n help=\"evaluate model for train dataset\",\n dest=\"eval_train\",\n action=BooleanOptionalAction,\n default=False)\n parser.add_argument(\"--eval-full\",\n help=\"evaluate model for full dataset after train\",\n dest=\"eval_full\",\n action=BooleanOptionalAction,\n default=False)\n args = parser.parse_args(argv[1:])\n\n fixed_seed = 20251216\n print(f\"Fixed seed:{fixed_seed}\", flush=True)\n random.seed(fixed_seed)\n\n print(args, flush=True) # dbg\n _model_file_name = train(\n cred_data_location=args.cred_data_location,\n jobs=int(args.jobs),\n epochs=int(args.epochs),\n batch_size=int(args.batch_size),\n patience=int(args.patience),\n doc_target=bool(args.doc_target),\n use_tuner=bool(args.use_tuner),\n eval_test=bool(args.eval_test),\n eval_train=bool(args.eval_train),\n eval_full=bool(args.eval_full),\n )\n if os.path.exists(_model_file_name):\n # print in last line the name\n print(f\"\\nYou can find your model in:\\n{_model_file_name}\", flush=True)\n return 0\n print(f\"Error: {_model_file_name}\", flush=True)\n return 1\n\n\nif __name__ == \"__main__\":\n sys.exit(main(sys.argv))\n" }, { "path": "experiment/main.sh", "content": "#!/usr/bin/env bash\n\nset -ex\n\nSTART_TIME=$(date +%s)\nNOW=$(date +%Y%m%d_%H%M%S)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at ${NOW}\"\n\nfree --wide --human\n\n# use the path environments without / at end\n\necho \"CREDSWEEPER_DIR='${CREDSWEEPER_DIR}'\"\nif [ -z \"${CREDSWEEPER_DIR}\" ] || [ ! -d \"${CREDSWEEPER_DIR}\" ]; then\n echo \"CREDSWEEPER_DIR environment is empty or does not exist\"\n exit 1\nfi\n\nexport PYTHONPATH=\"${CREDSWEEPER_DIR}\":$PYTHONPATH\n# check current version of CredSweeper\n\"${CREDSWEEPER_DIR}\"/.venv/bin/python -m credsweeper --banner\ngit log -1\ngit status\n\n\necho \"CREDDATA_DIR='${CREDDATA_DIR}'\"\nif [ -z \"${CREDDATA_DIR}\" ] || [ ! -d \"${CREDDATA_DIR}\" ]; then\n echo \"CREDDATA_DIR environment is empty or does not exist\"\n exit 1\nfi\n\n# do some check in CredData repo\n(cd \"${CREDDATA_DIR}\" && git log -1 && git status)\n\necho \"JOBS=${JOBS} of $(nproc)\"\nif [ -z \"${JOBS}\" ]; then\n JOBS=$(nproc)\n echo \"Used JOBS=${JOBS} for multiple process\"\nelif [ ! 0 -lt ${JOBS} ]; then\n echo \"Unappropriated JOBS=${JOBS}\"\n exit 1\nfi\n\necho \"BATCH=${BATCH}\"\nif [ -z \"${BATCH}\" ]; then\n BATCH=256\n echo \"Used BATCH=${BATCH}\"\nelif [ ! 0 -lt ${JOBS} ]; then\n echo \"Unappropriated BATCH=${BATCH}\"\n exit 1\nfi\n\n\nWORK_DIR=\"${CREDSWEEPER_DIR}/experiment\"\ncd \"${WORK_DIR}\"\nRESULT_DIR=\"${WORK_DIR}/results\"\nmkdir -vp \"${RESULT_DIR}\"\n\n# set env TUNER to use keras-tuner\n#TUNER=--tuner\n# set env DOC to apply doc dataset\n#DOC=--doc\n\"${CREDSWEEPER_DIR}\"/.venv/bin/python main.py --data \"${CREDDATA_DIR}\" --jobs ${JOBS} ${TUNER} ${DOC} --batch_size ${BATCH} | tee \"${RESULT_DIR}/${NOW}.train.log\"\nerror_code=${PIPESTATUS}\nif [ 0 -ne ${error_code} ]; then exit ${error_code}; fi\n\ncd \"${CREDSWEEPER_DIR}\"\nreport_file=${RESULT_DIR}/${NOW}.json\nif [ -z \"${TESTDATA_DIR}\" ]; then\n echo \"Used CREDDATA_DIR=${CREDDATA_DIR} for BenchMark and train rules only\"\n ${CREDSWEEPER_DIR}/.venv/bin/python -m credsweeper ${DOC} --sort --rules ${CREDSWEEPER_DIR}/experiment/results/train_config.yaml --path \"${CREDDATA_DIR}/data\" --log info --jobs ${JOBS} --subtext --save-json ${report_file} --no-stdout\n cd \"${CREDDATA_DIR}\"\nelse\n echo \"TESTDATA_DIR=${TESTDATA_DIR}\"\n ${CREDSWEEPER_DIR}/.venv/bin/python -m credsweeper ${DOC} --sort --path \"${TESTDATA_DIR}/data\" --log info --jobs ${JOBS} --subtext --save-json ${report_file} --no-stdout\n cd \"${TESTDATA_DIR}\"\nfi\n\n.venv/bin/python -m benchmark --scanner credsweeper --load ${report_file} | tee ${CREDSWEEPER_DIR}/.ci/benchmark.txt\n\nSPENT_SECONDS=$(( $(date +%s) - ${START_TIME} ))\nif [ 86400 -lt ${SPENT_SECONDS} ];then\n SPENT_TIME=$(date -ud \"@${SPENT_SECONDS}\" +\"$(( ${SPENT_SECONDS} / 86400 ))-%H:%M:%S\")\nelse\n SPENT_TIME=$(date -ud \"@${SPENT_SECONDS}\" +\"%H:%M:%S\")\nfi\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "experiment/ml_model.py", "content": "from typing import Any, Optional\n\nimport keras_tuner as kt\nfrom tensorflow.keras.layers import Dense, LSTM, Bidirectional, Input, Concatenate, Dropout\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.optimizers import Adam\nfrom tensorflow.python.keras.layers import ReLU, Softmax, Multiply\nfrom tensorflow.python.keras.metrics import BinaryAccuracy, Precision, Recall\n\nfrom credsweeper.common.constants import ML_HUNK\nfrom credsweeper.ml_model.ml_validator import MlValidator\n\n\nclass MlModel(kt.HyperModel):\n d_type = \"float32\"\n\n def __init__(self, line_shape: tuple, variable_shape: tuple, value_shape: tuple, feature_shape: tuple, **kwargs):\n self.line_shape = line_shape\n self.variable_shape = variable_shape\n self.value_shape = value_shape\n self.feature_shape = feature_shape\n self.__kwargs = kwargs\n\n def get_hyperparam(self, param_name: str, hp=None) -> Any:\n if param_name in self.__kwargs:\n param = self.__kwargs.get(param_name)\n if isinstance(param, float):\n print(f\"'{param_name}' constant = {param}\", flush=True)\n return param\n elif hp and isinstance(param, tuple) and 3 == len(param):\n print(f\"'{param_name}' tuning = {param}\", flush=True)\n return hp.Float(param_name, min_value=param[0], max_value=param[1], step=param[2])\n else:\n raise ValueError(f\"'{param_name}' was not inited well {param} tuner is {hp}\")\n else:\n raise ValueError(f\"'{param_name}' was not defined during init and tuner is used\")\n\n def build(self, hp: Optional[Any]) -> Model:\n \"\"\"Get keras model with string and feature input and single binary out\"\"\"\n line_lstm_dropout_rate = self.get_hyperparam(\"line_lstm_dropout_rate\", hp)\n variable_lstm_dropout_rate = self.get_hyperparam(\"variable_lstm_dropout_rate\", hp)\n value_lstm_dropout_rate = self.get_hyperparam(\"value_lstm_dropout_rate\", hp)\n dense_a_drop = self.get_hyperparam(\"dense_a_drop\", hp)\n dense_b_drop = self.get_hyperparam(\"dense_b_drop\", hp)\n\n line_input = Input(shape=(None, self.line_shape[2]), name=\"line_input\", dtype=self.d_type)\n line_lstm = LSTM(units=self.line_shape[1],\n dtype=self.d_type,\n dropout=line_lstm_dropout_rate,\n recurrent_dropout=0)\n line_bidirectional = Bidirectional(layer=line_lstm, name=\"line_bidirectional\")\n line_lstm_branch = line_bidirectional(line_input)\n\n variable_input = Input(shape=(None, self.variable_shape[2]), name=\"variable_input\", dtype=self.d_type)\n variable_lstm = LSTM(units=self.variable_shape[1],\n dtype=self.d_type,\n dropout=variable_lstm_dropout_rate,\n recurrent_dropout=0)\n variable_bidirectional = Bidirectional(layer=variable_lstm, name=\"variable_bidirectional\")\n variable_lstm_branch = variable_bidirectional(variable_input)\n\n value_input = Input(shape=(None, self.value_shape[2]), name=\"value_input\", dtype=self.d_type)\n value_lstm = LSTM(units=self.value_shape[1],\n dtype=self.d_type,\n dropout=value_lstm_dropout_rate,\n recurrent_dropout=0)\n value_bidirectional = Bidirectional(layer=value_lstm, name=\"value_bidirectional\")\n value_lstm_branch = value_bidirectional(value_input)\n\n feature_input = Input(shape=(self.feature_shape[1], ), name=\"feature_input\", dtype=self.d_type)\n feature_attention = Dense(self.feature_shape[1], activation=Softmax(), use_bias=False,\n name=\"feature_attention\")(feature_input)\n x_scaled = Multiply(name=\"feature_multiply\")([feature_input, feature_attention])\n\n joined_features = Concatenate()([line_lstm_branch, variable_lstm_branch, value_lstm_branch, x_scaled])\n\n # 3 bidirectional + features\n dense_units = 2 * MlValidator.MAX_LEN + 2 * 2 * ML_HUNK + self.feature_shape[1]\n # check after model compilation. Should be matched the combined size.\n\n # first hidden layer\n dense_a = Dense(units=dense_units, activation=ReLU(), name=\"a_dense\", dtype=self.d_type)(joined_features)\n drop_a = Dropout(name=\"a_drop\", rate=dense_a_drop)(dense_a)\n\n # second hidden layer\n dense_b = Dense(units=dense_units, activation=ReLU(), name=\"b_dense\", dtype=self.d_type)(drop_a)\n drop_b = Dropout(name=\"b_drop\", rate=dense_b_drop)(dense_b)\n\n dense_final = Dense(units=1, activation='sigmoid', name=\"prediction\", dtype=self.d_type)(drop_b)\n\n metrics = [BinaryAccuracy(name=\"binary_accuracy\"), Precision(name=\"precision\"), Recall(name=\"recall\")]\n\n model: Model = Model(inputs=[line_input, variable_input, value_input, feature_input], outputs=dense_final)\n model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=metrics)\n model.summary(line_length=120, expand_nested=True, show_trainable=True)\n\n return model\n" }, { "path": "experiment/model_config_preprocess.py", "content": "import mimetypes\nfrom typing import Dict\n\nimport pandas as pd\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.utils.util import Util\n\nML_CONFIG_PATH = APP_PATH / \"ml_model\" / \"ml_config.json\"\n\n\ndef model_config_preprocess(df_all: pd.DataFrame, doc_target: bool) -> Dict[str, float]:\n model_config = Util.json_load(ML_CONFIG_PATH)\n ascii_char_set = ''.join(chr(x) for x in range(0x20, 0x7F))\n extra_char_set = \"\\x1B\\t\\n\\r\" # ESC code, tab and line end variations\n doc_char_set = \" ●가개공기께내는님당드등따로메면문밀방번보복본비사생서석성슈스시암에요용워으의이작정주지채체큰키토팅패필하할호화\" if doc_target else ''\n model_config[\"char_set\"] = extra_char_set + ascii_char_set + doc_char_set\n\n # check whether all extensions from meta are in ml_config.json\n\n for x in model_config[\"features\"]:\n if \"FileExtension\" == x[\"type\"]:\n config_extensions = x[\"kwargs\"][\"extensions\"]\n config_extensions_set = set(config_extensions)\n if len(config_extensions) != len(config_extensions_set):\n print(\"WARNING: duplicates in config extensions list\", flush=True)\n if any(x != x.lower() for x in config_extensions_set):\n print(\"WARNING: file extensions in config must be in lowercase\", flush=True)\n break\n else:\n raise RuntimeError(f\"FileExtension was not found in config ({ML_CONFIG_PATH}) features!\")\n\n data_extension_set = set(df_all[\"ext\"].unique())\n\n if config_extensions_set != data_extension_set:\n unknown_extensions = []\n for x in model_config[\"features\"]:\n if \"FileExtension\" == x[\"type\"]:\n known_extensions = set(x[\"kwargs\"][\"extensions\"])\n x[\"kwargs\"][\"extensions\"] = []\n for extension in sorted(list(data_extension_set)):\n if extension in known_extensions or mimetypes.guess_type(f\"a_file{extension}\")[0]:\n # use already present extensions and well-known additionally\n x[\"kwargs\"][\"extensions\"].append(extension)\n else:\n # collect all unknown extensions for error log\n print(f\"UNKNOWN EXTENSION: {extension}\", flush=True)\n unknown_extensions.append(extension)\n Util.json_dump(model_config, ML_CONFIG_PATH)\n if known_extensions != set(x[\"kwargs\"][\"extensions\"]):\n # the process must be restarted with updated config\n raise RuntimeError(\"RESTART: differences in extensions:\"\n f\"\\nconfig:{config_extensions_set.difference(data_extension_set)}\"\n f\"\\ndata:{data_extension_set.difference(config_extensions_set)}\"\n f\"\\nFile {ML_CONFIG_PATH} was updated.\"\n f\"\\nUnknown extensions:{unknown_extensions if unknown_extensions else None}\")\n break\n\n # append all rule names for the feature\n\n for x in model_config[\"features\"]:\n if \"RuleName\" == x[\"type\"]:\n config_rules = x[\"kwargs\"][\"rule_names\"]\n config_rules_set = set(config_rules)\n if len(config_rules) != len(config_rules_set):\n print(\"WARNING: duplicates in config rule_names list\", flush=True)\n break\n else:\n raise RuntimeError(f\"rule_names was not found in config ({ML_CONFIG_PATH}) features!\")\n\n data_rules_set = set(df_all[\"RuleName\"].explode().unique())\n\n if config_rules_set != data_rules_set:\n sorted_rules = sorted(list(data_rules_set))\n print(\"Update config rule names with \", sorted_rules, flush=True)\n for x in model_config[\"features\"]:\n if \"RuleName\" == x[\"type\"]:\n x[\"kwargs\"][\"rule_names\"] = sorted_rules\n Util.json_dump(model_config, ML_CONFIG_PATH)\n break\n # the process must be restarted with updated config\n raise RuntimeError(f\"RESTART: differences in rules:\"\n f\"\\nconfig:{config_rules_set.difference(data_rules_set)}\"\n f\"\\ndata:{data_rules_set.difference(config_rules_set)}\"\n f\"\\nFile {ML_CONFIG_PATH} was updated.\")\n else:\n print(config_rules_set, \" matches \", data_rules_set, flush=True)\n\n thresholds = model_config[\"thresholds\"]\n assert isinstance(thresholds, dict), thresholds\n print(f\"Load thresholds: {thresholds}\", flush=True)\n return thresholds\n" }, { "path": "experiment/plot.py", "content": "import itertools\nimport math\nimport pathlib\n\nimport matplotlib.pyplot as plt\nfrom keras.src.callbacks import History\nfrom matplotlib import image as mpimg\n\nMETRICS = [\"loss\", \"binary_accuracy\", \"precision\", \"recall\"]\nNCOLS = 2 # GRAPHS_PER_ROW\nNROWS = math.ceil(len(METRICS) / NCOLS)\n\n\ndef save_plot(stamp: str, title: str, history: History, dir_path: pathlib.Path, best_epoch: int, info: str):\n plt.clf()\n fig, axes = plt.subplots(nrows=NROWS, ncols=NCOLS, figsize=(16, 9), tight_layout=True)\n\n fig.suptitle(f\"{stamp} {title}\")\n\n # train displays \"Epoch 1/7\", so let the plot starts from 1\n x = [x + 1 for x in history.epoch]\n\n for idx, characteristic in itertools.zip_longest(range(NROWS * NROWS), METRICS):\n axes_x = idx % NCOLS\n axes_y = idx // NCOLS\n if characteristic:\n y_train = history.history[characteristic]\n y_test = history.history[f\"val_{characteristic}\"]\n axes[axes_x, axes_y].plot(x, y_train, label=\"train\")\n axes[axes_x, axes_y].plot(x, y_test, label=\"test\")\n axes[axes_x, axes_y].set_title(characteristic)\n axes[axes_x, axes_y].legend(loc=\"upper left\")\n axes[axes_x, axes_y].grid(visible=True, which=\"both\", color=\"grey\", linewidth=0.75, linestyle=\"dotted\")\n axes[axes_x, axes_y].set_xticks(range(min(x), max(x) + 1, 1), minor=True)\n axes[axes_x, axes_y].axvline(x=best_epoch, color='green', linestyle='--', linewidth=1)\n else:\n axes[axes_x, axes_y].axis('off')\n\n fig.text(0.001, 0.001, info, fontsize=10, color='green', backgroundcolor='white')\n plt.savefig(dir_path / f\"{stamp}.png\", dpi=96)\n plt.close('all')\n\n\ndef stamp_plot(stamp: str, dir_path: pathlib.Path, info: str):\n file_path = dir_path / f\"{stamp}.png\"\n image = mpimg.imread(file_path)\n plt.figure(figsize=(16, 9), tight_layout=True)\n plt.imshow(image)\n plt.text(222, 333, info, fontsize=10, color='red', backgroundcolor='white')\n plt.axis('off')\n plt.savefig(file_path, bbox_inches='tight', pad_inches=0, dpi=96)\n plt.close('all')\n" }, { "path": "experiment/prepare_data.py", "content": "import binascii\nimport hashlib\nimport os\nimport pathlib\nimport subprocess\nimport sys\nfrom pathlib import Path\n\nfrom credsweeper.scanner.scanner import RULES_PATH\nfrom credsweeper.utils.util import Util\n\nRESULTS_DIR = pathlib.Path(__file__).parent / \"results\"\n\n\ndef execute_scanner(dataset_location: str, report_file_str: str, train_rules_str: str, jobs: int, doc_target: bool):\n \"\"\"Execute CredSweeper as a separate process to make sure no global states is shared with training script\"\"\"\n dir_path = os.path.dirname(os.path.realpath(__file__))\n command = (f\"{sys.executable} -m credsweeper\"\n f\" --jobs {jobs}\"\n f\" --path {dataset_location}/data\"\n f\" {'--doc' if doc_target else ''}\"\n f\" --save-json {report_file_str}\"\n f\" --rules {train_rules_str}\"\n \" --pedantic\"\n \" --ml_threshold 0\"\n \" --sort\"\n \" --subtext\"\n \" --log info\"\n \" --no-stdout\")\n error_code = subprocess.check_call(command, shell=True, cwd=dir_path)\n if 0 != error_code:\n sys.exit(error_code)\n\n\ndef data_checksum(dir_path: Path) -> str:\n checksum = hashlib.md5(b'').digest()\n for root, dirs, files in os.walk(dir_path):\n for file in files:\n with open(os.path.join(root, file), \"rb\") as f:\n cvs_checksum = hashlib.md5(f.read()).digest()\n checksum = bytes(a ^ b for a, b in zip(checksum, cvs_checksum))\n return binascii.hexlify(checksum).decode()\n\n\ndef prepare_train_data(cred_data_location: str, jobs: int, doc_target: bool):\n print(\"Start train data preparation...\", flush=True)\n\n # use current rules\n rules = Util.yaml_load(RULES_PATH)\n target = \"doc\" if doc_target else \"code\"\n new_rules = [x for x in rules if x.get(\"use_ml\") and target in x[\"target\"]]\n train_rules_config_path = RESULTS_DIR / \"train_config.yaml\"\n Util.yaml_dump(new_rules, train_rules_config_path)\n\n meta_dir_checksum = data_checksum(Path(cred_data_location) / \"meta\")\n print(f\"meta checksum {meta_dir_checksum}\", flush=True)\n\n data_dir_checksum = data_checksum(Path(cred_data_location) / \"data\")\n print(f\"data checksum {data_dir_checksum}\", flush=True)\n detected_data_filename = RESULTS_DIR / f\"detected_data.{data_dir_checksum}.json\"\n\n if not os.path.exists(detected_data_filename):\n print(f\"Get CredSweeper results from {cred_data_location}. May take some time\", flush=True)\n execute_scanner(cred_data_location, str(detected_data_filename), str(train_rules_config_path), jobs, doc_target)\n else:\n print(f\"Get cached result {data_dir_checksum}\", flush=True)\n\n print(\"Train data prepared!\", flush=True)\n return meta_dir_checksum, data_dir_checksum\n" }, { "path": "experiment/requirements.txt", "content": "# Python 3.10.20\n# pip 26.1\n\n# version sensetive\nh5py==3.12.1\nkeras==2.15.0\nkeras-tuner==1.4.7\nnumpy==1.26.4\nonnx==1.17.0\nprotobuf==3.20.3\nscikit-learn==1.6.1\ntensorflow-cpu==2.15.1\ntf2onnx==1.16.1\nwrapt==1.14.1\n\n# version insensetive\ntypes-tensorflow\nmatplotlib\ncolorama\npsutil\n" }, { "path": "experiment/tf2onnx/tf2onnx.sh", "content": "#!/usr/bin/env bash\n\nset -e\n\n# tensorflow model may be obtained like this: git restore -s be06d6059f0def4f0fdb50444c08db4ce542173e -- ml_model.h5\n# use virtual environment and the requirements.txt - there are very specific luke combination of packages verions\n# python -m venv .venv\n# . .venv/bin/activate\n# python -m pip install --upgrade pip\n# python -m pip install --requirement requirements.txt\n\n# [optional] thransform model form h5 to saved directory\npython -c 'import tensorflow as tf;model=tf.keras.models.load_model(\"ml_model.h5\");model.save(\"ml_model\")'\n# transform the model\npython -m tf2onnx.convert --saved-model ml_model --output ml_model.onnx --verbose --rename-inputs feature_input,line_input\n# md5sum for integrity\nmd5sum --binary ml_model.onnx\n" }, { "path": "experiment/tools/base64_test.py", "content": "#!/usr/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nThe script is useful to test patterns of base64 encoded data with 0,1,2 offsets\n\"\"\"\nimport base64\nimport random\nimport sys\n\n\ndef gen_token(pad: int, txt: bytes) -> bytes:\n trash = random.randbytes(3) + random.randbytes(pad) + txt + random.randbytes(pad) + random.randbytes(3)\n return base64.b64encode(trash, altchars=b\"-_\")\n\n\ndef main(argv):\n loops = int(argv[1]) if 1 < len(argv) else 1\n inner_pattern = b\"XgroqX\"\n while 0 < loops:\n loops -= 1\n token0 = gen_token(0, inner_pattern)\n assert b\"WGdyb3FY\" in token0, token0\n token1 = gen_token(1, inner_pattern)\n assert b\"hncm9xW\" in token1, token1\n token2 = gen_token(2, inner_pattern)\n assert b\"YZ3JvcV\" in token2, token2\n\n\nif __name__ == \"\"\"__main__\"\"\":\n main(sys.argv)\n" }, { "path": "experiment/tools/entropy_test.py", "content": "import random\nimport signal\nimport statistics\nimport threading\nimport time\nfrom multiprocessing import Pool\nfrom typing import Tuple, Dict\n\nfrom credsweeper.common.constants import Chars\nfrom credsweeper.utils.util import Util\n\nrandom_data: str\nITERATIONS = 1000\n\n\ndef pool_initializer() -> None:\n signal.signal(signal.SIGINT, signal.SIG_IGN)\n\n\ndef evaluate_avg(_args: Tuple[int, float, float]) -> Tuple[float, float]:\n min_avg = _args[1]\n max_dvt = _args[2]\n size = _args[0]\n entropies = []\n for x in range(ITERATIONS):\n offset = x * size\n entropy = Util.get_shannon_entropy(random_data[offset:offset + size])\n entropies.append(entropy)\n avg = statistics.mean(entropies)\n dvt = statistics.stdev(entropies, avg)\n if avg < min_avg:\n min_avg = avg\n if dvt > max_dvt:\n max_dvt = dvt\n return min_avg, max_dvt\n\n\nif __name__ == \"__main__\":\n random.seed()\n stats: Dict[int, Tuple[float, float]] = {}\n sizes = [x for x in range(8, 36)]\n try:\n for n in range(1000):\n start_time = time.time()\n random_data = ''.join([random.choice(Chars.BASE32_CHARS.value) for _ in range(ITERATIONS * max(sizes))])\n _args = [(i, stats[i][0] if i in stats else 9.9, stats[i][1] if i in stats else 0.0) for i in sizes]\n with Pool(processes=min(15, len(_args)), initializer=pool_initializer) as pool:\n for _size, _res in zip(sizes, pool.map(evaluate_avg, _args)):\n with threading.Lock():\n stats[_size] = _res\n for k, v in stats.items():\n print(f\"{k}: {v}\", flush=True)\n print(f\"loop {n} in {time.time() - start_time}\", flush=True)\n except KeyboardInterrupt as exc:\n print(exc, flush=True)\n finally:\n print(\"===========================================================\", flush=True)\n for k, v in stats.items():\n # for parametrization of unit tests\n print(f\"({k}, {v[0]}, {v[1]}),\", flush=True)\n" }, { "path": "experiment/tools/morpheme_test.py", "content": "import random\nimport signal\nimport threading\nimport time\nfrom multiprocessing import Pool\nfrom typing import Tuple, Dict\n\nfrom credsweeper.common import KeywordChecklist\nfrom credsweeper.common.constants import BASE64COMMON\n\nrandom_data: str\nITERATIONS = 1000\n\n\nclass KeywordChecklistTest(KeywordChecklist):\n\n def calc(self, line_lower: str) -> int:\n matches = 0\n for keyword in self.morpheme_set:\n if keyword in line_lower:\n matches += 1\n return matches\n\n\ncounter = KeywordChecklistTest()\n\n\ndef pool_initializer() -> None:\n signal.signal(signal.SIGINT, signal.SIG_IGN)\n\n\ndef evaluate_avg(_args: Tuple[int, float, float]) -> Tuple[float, float]:\n min_avg = _args[1]\n max_dvt = _args[2]\n size = _args[0]\n for x in range(ITERATIONS):\n offset = x * size\n value = counter.calc(random_data[offset:offset + size])\n if 0 < value < min_avg:\n min_avg = value\n if value > max_dvt:\n max_dvt = value\n return min_avg, max_dvt\n\n\nif __name__ == \"__main__\":\n random.seed()\n stats: Dict[int, Tuple[float, float]] = {}\n sizes = [4, 8, 16, 32, 40, 64, 70, 80, 90, 100, 128, 256, 512, 1024]\n try:\n for n in range(100):\n start_time = time.time()\n random_data = ''.join([random.choice(BASE64COMMON) for _ in range(ITERATIONS * max(sizes))])\n _args = [(i, stats[i][0] if i in stats else 9.9, stats[i][1] if i in stats else 0.0) for i in sizes]\n with Pool(processes=min(15, len(_args)), initializer=pool_initializer) as pool:\n for _size, _res in zip(sizes, pool.map(evaluate_avg, _args)):\n with threading.Lock():\n stats[_size] = _res\n for k, v in stats.items():\n print(f\"{k}: {v}\", flush=True)\n print(f\"loop {n} in {time.time() - start_time}\", flush=True)\n except KeyboardInterrupt as exc:\n print(exc, flush=True)\n finally:\n print(\"===========================================================\", flush=True)\n for k, v in stats.items():\n # for parametrization of unit tests\n print(f\"({k}, {v[0]}, {v[1]}),\", flush=True)\n" }, { "path": "experiment/tools/strength_test.py", "content": "import random\nimport signal\nimport statistics\nimport threading\nimport time\nfrom multiprocessing import Pool\nfrom typing import Tuple, Dict\n\nfrom credsweeper.common.constants import Chars\nfrom credsweeper.utils.hop_stat import HopStat\n\nhopper = HopStat()\nITERATIONS = 10000000\nBASE = Chars.BASE36_CHARS.value\n\n\ndef pool_initializer() -> None:\n signal.signal(signal.SIGINT, signal.SIG_IGN)\n\n\ndef evaluate_avg(size) -> Tuple[Tuple[float, float], Tuple[float, float]]:\n hops = []\n devs = []\n for i in range(ITERATIONS):\n hop, dev = hopper.stat(''.join(random.choices(BASE, k=size)))\n hops.append(hop)\n devs.append(dev)\n avg_hop = statistics.mean(hops)\n dev_hop = statistics.stdev(hops, avg_hop)\n avg_dev = statistics.mean(devs)\n dev_dev = statistics.stdev(devs, avg_dev)\n return (avg_hop, dev_hop), (avg_dev, dev_dev)\n\n\nif __name__ == \"__main__\":\n try:\n stats: Dict[int, Tuple[float, float]] = {}\n sizes = [8, 10, 15, 16, 20, 24, 25, 32, 40, 50, 64]\n start_time = time.time()\n\n with Pool(processes=min(16, len(sizes)), initializer=pool_initializer) as pool:\n for _size, _res in zip(sizes, pool.map(evaluate_avg, sizes)):\n with threading.Lock():\n stats[_size] = _res\n print(f\"done in {time.time() - start_time} for {BASE}\", flush=True)\n for k, v in stats.items():\n print(f\"{k}: {v},\", flush=True)\n except KeyboardInterrupt as exc:\n print(exc, flush=True)\n\n# base32 results\n# 8: ((3.480934, 0.8482364556537906), (1.9280820731422028, 0.5833143826506801)),\n# 10: ((3.4801753333333334, 0.7508676237320747), (1.9558544090983234, 0.5119385414964345)),\n# 15: ((3.4803549285714284, 0.603220270918794), (1.9896690734372564, 0.40640877687972476)),\n# 16: ((3.4798649333333334, 0.5837818960141307), (1.9938368543943692, 0.392547066949958)),\n# 20: ((3.4809878947368422, 0.518785674729997), (2.0058661928593517, 0.34692788889724946)),\n# 24: ((3.480511086956522, 0.4726670109337228), (2.0131379532992537, 0.31476354168931936)),\n# 25: ((3.480877375, 0.4626150412368404), (2.0147828593929953, 0.3075894753390553)),\n# 32: ((3.4809023548387095, 0.4072672632996217), (2.0231609118646867, 0.2700344059876962)),\n# 40: ((3.4801929743589746, 0.36361457820793436), (2.027858606807074, 0.2401498396303172)),\n# 50: ((3.4798551224489795, 0.323708167297437), (2.0318808048208794, 0.2138098551294688)),\n# 64: ((3.4805990476190476, 0.28572156450556774), (2.035756800745673, 0.18815721535870078)),\n\n# base36 result\n# 8: ((3.7190542428571427, 0.8995506118495411), (2.066095086865182, 0.609210293352161)),\n# 10: ((3.719109611111111, 0.7956463384852813), (2.0946299036665494, 0.5322004874842623)),\n# 15: ((3.719274257142857, 0.6401989313894239), (2.129437216268589, 0.42108786288993155)),\n# 16: ((3.7192072666666665, 0.6188627491757901), (2.1336109506109366, 0.4064699817331141)),\n# 20: ((3.719249815789474, 0.5506473627709657), (2.145293932511567, 0.3591543917048417)),\n# 24: ((3.7191934304347827, 0.50051922802262), (2.152858549996053, 0.3252064160191062)),\n# 25: ((3.7192351583333334, 0.4904181410613897), (2.1543202565038735, 0.31823801389315026)),\n# 32: ((3.7190408419354837, 0.4315967526660196), (2.1620321219700767, 0.2788634701820312)),\n# 40: ((3.7191682666666668, 0.3852248727988986), (2.16746680811131, 0.24802261318501675)),\n# 50: ((3.718913744897959, 0.3436564880405547), (2.1715676118603806, 0.22070510537297627)),\n# 64: ((3.7190009761904763, 0.30325954360127116), (2.1751172797904093, 0.1942582237461476)),\n\n# base64 results\n# done in 130.86447429656982 for 0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ-_\n# 8: ((3.7627115714285715, 0.9413431166706269), (2.1378378843992736, 0.6394596814295781)),\n# 10: ((3.7617393333333333, 0.8327986018456262), (2.168873183866972, 0.5605393324056347)),\n# 15: ((3.7619624285714286, 0.6698092646328063), (2.2080058406286702, 0.4447698491992352)),\n# 16: ((3.7618573333333334, 0.6471500119793832), (2.2116826642934453, 0.4288377928263507)),\n# 20: ((3.7618887368421055, 0.575813792926031), (2.224384985667721, 0.37985781543221253)),\n# 24: ((3.7621449565217393, 0.5243297908608613), (2.2326041329976607, 0.34397389723600613)),\n# 25: ((3.762616791666667, 0.5137934920050976), (2.234571917211925, 0.3366547036535176)),\n# 32: ((3.761885838709677, 0.4521158322065318), (2.2426375800006153, 0.29506039075960255)),\n# 40: ((3.7622649487179487, 0.4031261511824518), (2.2485911621253574, 0.2622954601051068)),\n# 50: ((3.762087693877551, 0.3597404118023357), (2.2533774423872956, 0.23384524947332655)),\n# 64: ((3.7625271746031745, 0.31733579704946846), (2.257532519514275, 0.20571908142867643)),\n" }, { "path": "experiment/train.py", "content": "import hashlib\nimport os\nimport pathlib\nimport pickle\nimport random\nimport subprocess\nimport sys\nfrom datetime import datetime\n\nimport keras_tuner as kt\nimport numpy as np\nimport pandas as pd\nimport tensorflow as tf\nfrom keras import Model # type: ignore\nfrom numpy import ndarray\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.utils import compute_class_weight\nfrom tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint\n\nfrom data_loader import read_detected_data, read_metadata, join_label, get_y_labels\nfrom experiment.evaluate_model import evaluate_model\nfrom features import prepare_data\nfrom hyperparameters import HP_DICT\nfrom log_callback import LogCallback\nfrom ml_model import MlModel\nfrom model_config_preprocess import model_config_preprocess, ML_CONFIG_PATH\nfrom plot import save_plot\nfrom prepare_data import prepare_train_data, RESULTS_DIR\n\n\ndef train(\n cred_data_location: str,\n jobs: int,\n epochs: int,\n batch_size: int,\n patience: int,\n doc_target: bool,\n use_tuner: bool,\n eval_test: bool,\n eval_train: bool,\n eval_full: bool,\n) -> str:\n # fixed seed for std.random in main()\n tf.random.set_seed(random.randint(1, 0xffffffff))\n np.random.seed(random.randint(1, 0xffffffff))\n\n print(f\"Memory at start: {LogCallback.get_memory_info()}\", flush=True)\n\n subprocess.check_call(f\"md5sum {ML_CONFIG_PATH.absolute()}\", shell=True) # dbg\n\n current_time = datetime.now().strftime(\"%Y%m%d_%H%M%S\")\n\n os.makedirs(RESULTS_DIR, exist_ok=True)\n\n print(f\"Train model on data from {cred_data_location}\", flush=True)\n meta_checksum, data_checksum = prepare_train_data(cred_data_location, jobs, doc_target)\n\n df_all_file = RESULTS_DIR / f\"{meta_checksum}-{data_checksum}.pkl\"\n if df_all_file.exists():\n df_all = pd.read_pickle(df_all_file)\n print(f\"Read from {df_all_file}\", flush=True)\n else:\n # detected data means which data is passed to ML validator of credsweeper after filters with RuleName\n detected_data = read_detected_data(RESULTS_DIR / f\"detected_data.{data_checksum}.json\")\n print(f\"CredSweeper detected {len(detected_data)} credentials without ML\", flush=True)\n # all markup data\n meta_data = read_metadata(f\"{cred_data_location}/meta\")\n print(f\"Metadata markup: {len(meta_data)} items\", flush=True)\n df_all = join_label(detected_data, meta_data, cred_data_location)\n # np.save(df_all_file, df_all)\n df_all.to_pickle(df_all_file)\n print(f\"Stored to {df_all_file}\", flush=True)\n # to prevent extra memory consumption - delete unnecessary objects\n del detected_data\n del meta_data\n\n # workaround for CI step\n trial_cnt = 3\n while 0 < trial_cnt:\n trial_cnt -= 1\n # there are 2 times possible fails due ml config might be updated\n try:\n thresholds = model_config_preprocess(df_all, doc_target)\n break\n except RuntimeError as exc:\n if \"RESTART:\" in str(exc) and 0 <= trial_cnt:\n print(str(exc), flush=True)\n continue\n else:\n raise exc\n else:\n raise RuntimeError(\"Something went wrong\")\n\n # random split\n df_train, df_test = train_test_split(df_all, test_size=0.15, random_state=random.randint(1, 1 << 32))\n len_df_train = len(df_train)\n print(f\"Train size: {len_df_train}\", flush=True)\n len_df_test = len(df_test)\n print(f\"Test size: {len_df_test}\", flush=True)\n\n print(f\"Prepare full data\", flush=True)\n x_full_line, x_full_variable, x_full_value, x_full_features = prepare_data(df_all)\n y_full: ndarray = get_y_labels(df_all)\n del df_all\n\n print(f\"Prepare train data\", flush=True)\n x_train_line, x_train_variable, x_train_value, x_train_features = prepare_data(df_train)\n print(\"x_train_value dtype \", x_train_value.dtype, flush=True) # dbg\n print(\"x_train_features dtype\", x_train_features.dtype, flush=True) # dbg\n y_train = get_y_labels(df_train)\n print(\"y_train dtype\", y_train.dtype, flush=True) # dbg\n del df_train\n\n print(f\"Class-1 prop on train: {np.mean(y_train):.4f}\", flush=True)\n\n classes = np.unique(y_train)\n class_weights = compute_class_weight(class_weight='balanced', classes=classes, y=y_train)\n max_weight = max(class_weights)\n class_weights = [weight / max_weight for weight in class_weights]\n print(f\"y_train size:{len(y_train)}, 0: {np.count_nonzero(y_train == 0)}, 1: {np.count_nonzero(y_train == 1)}\",\n flush=True)\n class_weight = dict(zip(classes, class_weights))\n print(f\"class_weight: {class_weight}\", flush=True) # information about class weights\n\n print(f\"Prepare test data\", flush=True)\n x_test_line, x_test_variable, x_test_value, x_test_features = prepare_data(df_test)\n y_test = get_y_labels(df_test)\n print(f\"Class-1 prop on test: {np.mean(y_test):.4f}\", flush=True)\n del df_test\n\n print(f\"Memory before search / compile: {LogCallback.get_memory_info()}\", flush=True)\n\n log_callback = LogCallback()\n if use_tuner:\n print(f\"Tuner initial dict:{HP_DICT}\", flush=True)\n tuner_kwargs = {k: v[0] for k, v in HP_DICT.items()}\n print(f\"Tuner kwargs:{tuner_kwargs}\", flush=True)\n\n tuner = kt.BayesianOptimization(\n hypermodel=MlModel(x_full_line.shape, x_full_variable.shape, x_full_value.shape, x_full_features.shape,\n **tuner_kwargs),\n objective='val_loss',\n directory=str(RESULTS_DIR / f\"{current_time}.tuner\"),\n project_name='ml_tuning',\n seed=random.randint(1, 0xffffffff),\n max_trials=30,\n )\n search_early_stopping = EarlyStopping(monitor=\"val_loss\",\n patience=patience,\n mode=\"min\",\n restore_best_weights=True,\n verbose=1)\n tuner.search(\n x=[x_train_line, x_train_variable, x_train_value, x_train_features],\n y=y_train,\n epochs=epochs,\n batch_size=batch_size,\n callbacks=[search_early_stopping, log_callback],\n validation_data=([x_test_line, x_test_variable, x_test_value, x_test_features], y_test),\n verbose=2,\n )\n print(\"Best Hyperparameters:\", flush=True)\n for k, v in tuner.get_best_hyperparameters()[0].values.items():\n print(f\"{k}: {v}\", flush=True)\n param_kwargs = {k: float(v) for k, v in tuner.get_best_hyperparameters()[0].values.items() if k in HP_DICT}\n del tuner\n else:\n print(f\"Model is trained with params from dict:{HP_DICT}\", flush=True)\n param_kwargs = {k: v[1] for k, v in HP_DICT.items()}\n\n print(f\"Model hyper parameters: {param_kwargs}\", flush=True)\n\n # repeat train step to obtain actual history chart\n _model = MlModel(x_full_line.shape, x_full_variable.shape, x_full_value.shape, x_full_features.shape,\n **param_kwargs)\n keras_model = _model.build(hp=None) # this train will be used hyperparam in param_kwargs\n if not eval_full:\n # the data are not necessary\n del x_full_line\n del x_full_variable\n del x_full_value\n del x_full_features\n del y_full\n\n early_stopping = EarlyStopping(monitor=\"val_loss\",\n patience=patience,\n mode=\"min\",\n restore_best_weights=True,\n verbose=1)\n model_checkpoint = ModelCheckpoint(filepath=str(RESULTS_DIR / f\"{current_time}.best_model\"),\n monitor=\"val_loss\",\n save_best_only=True,\n mode=\"min\",\n verbose=1)\n\n print(f\"Memory before train: {LogCallback.get_memory_info()}\", flush=True)\n\n fit_history = keras_model.fit(x=[x_train_line, x_train_variable, x_train_value, x_train_features],\n y=y_train,\n batch_size=batch_size,\n epochs=epochs,\n verbose=2,\n validation_data=([x_test_line, x_test_variable, x_test_value,\n x_test_features], y_test),\n class_weight=class_weight,\n callbacks=[early_stopping, model_checkpoint, log_callback],\n use_multiprocessing=True)\n\n # if best_val_loss is not None and best_val_loss + 0.00001 < early_stopping.best:\n # print(f\"CHECK BEST TUNER EARLY STOP : {best_val_loss} vs CURRENT: {early_stopping.best}\",flush=True)\n\n print(f\"Memory after train: {LogCallback.get_memory_info()}\", flush=True)\n\n with open(RESULTS_DIR / f\"{current_time}.history.pickle\", \"wb\") as f:\n pickle.dump(fit_history, f)\n\n model_file_name = RESULTS_DIR / f\"ml_model_at-{current_time}\"\n keras_model.save(model_file_name, include_optimizer=False)\n\n if eval_test:\n print(f\"Validate results on the test subset. Size: {len(y_test)} {np.mean(y_test):.4f}\", flush=True)\n evaluate_model(thresholds, keras_model, [x_test_line, x_test_variable, x_test_value, x_test_features], y_test)\n # drop small test set first to free a bit more memory for next evaluation\n del x_test_line\n del x_test_variable\n del x_test_value\n del x_test_features\n del y_test\n\n if eval_train:\n print(f\"Validate results on the train subset. Size: {len(y_train)} {np.mean(y_train):.4f}\", flush=True)\n evaluate_model(thresholds, keras_model, [x_train_line, x_train_variable, x_train_value, x_train_features],\n y_train)\n del x_train_line\n del x_train_variable\n del x_train_value\n del x_train_features\n del y_train\n\n if eval_full:\n print(f\"Validate results on the full set. Size: {len(y_full)} {np.mean(y_full):.4f}\", flush=True)\n evaluate_model(thresholds, keras_model, [x_full_line, x_full_variable, x_full_value, x_full_features], y_full)\n del x_full_line\n del x_full_variable\n del x_full_value\n del x_full_features\n del y_full\n\n onnx_model_file = pathlib.Path(__file__).parent.parent / \"credsweeper\" / \"ml_model\" / \"ml_model.onnx\"\n # convert the model to onnx right now\n convert_args = f\"{sys.executable} -m tf2onnx.convert --saved-model {model_file_name.absolute()}\" \\\n f\" --output {str(onnx_model_file)} --verbose\"\n subprocess.check_call(convert_args, shell=True, cwd=pathlib.Path(__file__).parent)\n with open(onnx_model_file, \"rb\") as f:\n onnx_md5 = hashlib.md5(f.read()).hexdigest()\n print(f\"ml_model.onnx:{onnx_md5}\", flush=True)\n\n with open(ML_CONFIG_PATH, \"rb\") as f:\n config_md5 = hashlib.md5(f.read()).hexdigest()\n print(f\"ml_config.json:{config_md5}\", flush=True)\n\n best_epoch = 1 + np.argmin(np.array(fit_history.history['val_loss']))\n\n # ml history analysis\n save_plot(\n stamp=current_time,\n title=f\"batch:{batch_size} train:{len_df_train} test:{len_df_test} weights:{class_weights}\",\n history=fit_history,\n dir_path=RESULTS_DIR,\n best_epoch=int(best_epoch),\n info=f\"ml_config.json:{config_md5} ml_model.onnx:{onnx_md5} best_epoch:{best_epoch}\",\n )\n\n return str(model_file_name.absolute())\n" }, { "path": "fuzz/README.md", "content": "# Fuzzing of CredSweeper API\n\nThe directory is used for dynamic analysis of CredSweeper with using [atheris](https://github.com/google/atheris),\nbased on [LibFuzzer](https://llvm.org/docs/LibFuzzer.html#options)\n\n\n## Preparation\n\n- The same interpreter packages as for CredSweeper + atheris + coverage (optional).\nWorking dir is project root - to be sure current source of credsweeper is used for coverage.\nPreferred to use virtual environment.\n\n```bash\npython3.8 -m virtualenv --copies .venv\n. .venv/bin/activate\npip install -U pip\npip install -r requirements.txt\n```\n\n\n## Fuzzing\n\nLaunch fuzzing script to collect seed files. \n```bash\nfuzzing.sh\n```\n-atheris_runs - must be greater than corpus files in 'corpus' directory.\nMany interactions require more rss memory - the limit must be decided.\nThen after productive fuzzing there will be new corpus files.\nSome of them are reduced from others. Some - new for imported libs.\nThe launch does not require coverage module but requires instumentation.\n\n\n## Coverage\n\nLaunch fuzzing script to calculate coverage with provided corpus files. \n```bash\ncoveraging.sh\n```\nTo generate HTML report use ```coverage html``` in project root (where .coverage file exists) after fuzzing.\nInstrumentation does not required - so it can be skipped.\n\n\n## Reducing\n\nLaunch reducing script to reduce corpus files only for 'NEW'. \n```bash\nreducing.sh\n```\nThe script is used -merge function of libfuzzer to reduce corpus files with multiple interaction.\nFull instrumentation is preferred.\n\n\n## Minimizing\n\nLaunch the script to remove corpus files that do not impact on credsweeper. \n```bash\nminimizing.sh\n```\nThe script uses coverage package to determine which corpus files do not change overall coverage and removes them.\nThe process is slow due each corpus file has to be checked. Instrumentation is not necessary.\n\nNOTE: some seeds may be dropped due complicated expression is assumed like one line/branch.\ne.g.:```if 0x01 == a[0] and 0x02 == a[1]:``` then seed [0x01,0x02] is kept, but [0x01,0x00] will be removed.\n\n## Useful commands for seed files modification\n```base\nfor f in $(ls); do h=$(sha1sum $f|cut -c-40); mv -v $f $h; done\n```\nRename seed file according sha1 digest of content\n" }, { "path": "fuzz/__main__.py", "content": "#!/usr/bin/env python\n\n# Copyright 2022 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\nimport hashlib\nimport io\nimport logging\nimport os\nimport sys\nimport warnings\nfrom unittest.mock import patch\n\nimport atheris\n# # # In simple case interested lib(s) may be imported during 'with'\n# # # It runs quickly but not precisely\n# with atheris.instrument_imports(enable_loader_override=False):\nfrom bs4 import XMLParsedAsHTMLWarning\n\nfrom credsweeper.app import CredSweeper\nfrom credsweeper.common.constants import DiffRowType\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom credsweeper.file_handler.patches_provider import PatchesProvider\nfrom tests import ZERO_ML_THRESHOLD\n\nwarnings.filterwarnings(\"ignore\", category=XMLParsedAsHTMLWarning)\n\n# set log level for fuzzing\nlogging.basicConfig(level=logging.CRITICAL)\nlogger = logging.getLogger(__name__)\n\n# Use depth=3 to deep scan in .zip and .gz files + find by extension feature\ncred_sweeper = CredSweeper(find_by_ext=True, ml_threshold=ZERO_ML_THRESHOLD, color=True, hashed=True,\n subtext=True, sort_output=True, thrifty=True)\n\nINPUT_DATA_SIZE = 0x1000\n\n\ndef fuzz_credsweeper_scan(data: bytes):\n # seed file name is sha1 of the content\n file_name = hashlib.sha1(data).hexdigest()\n fdp = atheris.FuzzedDataProvider(data)\n # offset:0x0000\n to_scan = fdp.ConsumeBytes(INPUT_DATA_SIZE)\n logger.debug(\"%s >>>>>>>> %s\", file_name, to_scan.decode(encoding='ascii', errors=\"ignore\"))\n\n candidates = []\n\n cred_sweeper.config.doc = False\n cred_sweeper.config.depth = 3\n cred_sweeper.credential_manager.candidates.clear()\n patch_provider_add = PatchesProvider([io.BytesIO(to_scan)], change_type=DiffRowType.ADDED)\n with patch.object(CredSweeper, CredSweeper.export_results.__name__):\n cred_sweeper.run(patch_provider_add)\n candidates.extend(cred_sweeper.credential_manager.get_credentials())\n\n cred_sweeper.config.doc = False\n cred_sweeper.config.depth = 0\n cred_sweeper.credential_manager.candidates.clear()\n patch_provider_del = PatchesProvider([io.BytesIO(to_scan)], change_type=DiffRowType.DELETED)\n with patch.object(CredSweeper, CredSweeper.export_results.__name__):\n cred_sweeper.run(patch_provider_del)\n candidates.extend(cred_sweeper.credential_manager.get_credentials())\n\n cred_sweeper.config.doc = True\n cred_sweeper.config.depth = 3\n cred_sweeper.credential_manager.candidates.clear()\n text_provider = FilesProvider([\"dummy\", io.BytesIO(to_scan)])\n with patch.object(CredSweeper, CredSweeper.export_results.__name__):\n cred_sweeper.run(text_provider)\n candidates.extend(cred_sweeper.credential_manager.get_credentials())\n\n cred_sweeper.config.doc = False\n cred_sweeper.config.depth = 0\n cred_sweeper.credential_manager.candidates.clear()\n text_provider = FilesProvider([\"dummy.xml\", io.BytesIO(to_scan)])\n with patch.object(CredSweeper, CredSweeper.export_results.__name__):\n cred_sweeper.run(text_provider)\n candidates.extend(cred_sweeper.credential_manager.get_credentials())\n\n for candidate in candidates:\n candidate.to_dict_list(False, False)\n\n\ndef main():\n # # # Instrument all works with ~30K functions. It is slow, but necessary for fuzzing for new seeds and reducing.\n # # # Instrumentation may being skipped when checking coverage with existing seeds or seeds minimization.\n if os.getenv('DO_ATHERIS_INSTRUMENT'):\n atheris.instrument_all()\n atheris.Setup( #\n sys.argv + [f\"-max_len={INPUT_DATA_SIZE}\"], # -rss_limit_mb=6912\n fuzz_credsweeper_scan, #\n internal_libfuzzer=True, #\n enable_python_coverage=True)\n atheris.Fuzz()\n\n\nif __name__ == \"__main__\":\n main()\n" }, { "path": "fuzz/auxilary.py", "content": "import binascii\nimport random\nimport string\nimport sys\n\nOLD_SEED_SIZE = 2048\nNEW_SEED_SIZE = 4096 - 256\n\n\n# run in fuzz: for f in $(find corpus -type f); do python3 auxilary.py $f; done\n\ndef main(argv):\n ascii_chars = string.digits + string.ascii_letters + string.punctuation + ' '\n responses = [\n b'{\"status\":\"PASS\"}',\n b'{\"status\":\"REQUEST_DENIED\",\"error_message\":\"The provided API key is invalid.\"}',\n b'{\"status\":\"REQUEST_DENIED\",\"error_message\":\"This API project is not authorized to use this API.\"}',\n b'{\"ok\":1}',\n b'{\"error\":1}',\n b'{\"error\":\"invalid_auth\"}',\n b'You are being redirected',\n b'Unable to find client by that `client_id`',\n b'{\"error\":{\"message\":null}}',\n b'{\"error\":{\"message\":\"\"}}',\n b\"\"\"{\"error\":{\"message\":\"The provided key 'rk_xxxHaving the 'rak_charge_read'\"\"\"\n b\"\"\" permission would allow this request to continue.\"}}\"\"\",\n ]\n for i in argv[1:]:\n with open(i, \"rb\") as f:\n data = f.read()\n for n, x in enumerate(responses):\n data_size = OLD_SEED_SIZE if OLD_SEED_SIZE < len(data) else len(data)\n with open(f\"{i}.{n}\", \"wb\") as f:\n f.write(data[:data_size])\n f.write(b'\\n' * (NEW_SEED_SIZE - data_size))\n f.write(x)\n crc32 = binascii.crc32(data)\n random.seed(crc32)\n text = ''.join(random.choice(ascii_chars) for _ in range(NEW_SEED_SIZE))\n with open(f\"{i}.{crc32:08x}\", \"w\") as f:\n f.write(text)\n\n\nif __name__ == \"__main__\":\n main(sys.argv)\n" }, { "path": "fuzz/coveraging.sh", "content": "#!/usr/bin/env bash\n\n#set -x\nset -e\n\nSTART_TIME=$(date +%s)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at $(date)\"\nTHISDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" > /dev/null 2>&1 && pwd )\"\ncd \"${THISDIR}/..\"\n\ncp -vf fuzz/__main__.py .coveraging.py\n\nCORPUS_DIR=fuzz/corpus\n\nrm -vf .coverage\n\npython -m coverage run \\\n --source=credsweeper \\\n .coveraging.py \\\n -rss_limit_mb=4096 \\\n -atheris_runs=$(( 1 + $(ls ${CORPUS_DIR} | wc -l) )) \\\n -verbosity=1 \\\n ${CORPUS_DIR} \\\n ;\n\n# make html report\npython -m coverage html\n# remove uniq data to compare reports\n(cd htmlcov && for f in $(ls . | grep '.*\\.html'); do sed -i \"s/.*created at.*//g\" $f; done)\n\n# report in text format\npython -m coverage report | tee report.txt\n\nSPENT_TIME=$(date -ud \"@$(( $(date +%s) - ${START_TIME} ))\" +\"%H:%M:%S\")\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "fuzz/fuzzing.sh", "content": "#!/usr/bin/env bash\n\n#set -x\nset -e\n\nSTART_TIME=$(date +%s)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at $(date)\"\nTHISDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" > /dev/null 2>&1 && pwd )\"\ncd \"${THISDIR}/..\"\n\ncp -vf fuzz/__main__.py .fuzzing.py\n\nCORPUS_DIR=fuzz/corpus\n\n# DO instrument to find new seeds\nexport DO_ATHERIS_INSTRUMENT=1\n\n# fuzzing with single thread only\npython .fuzzing.py \\\n -rss_limit_mb=6500 \\\n -atheris_runs=$(( 100000 + $(ls -1 ${CORPUS_DIR} | wc -l) )) \\\n -verbosity=1 \\\n ${CORPUS_DIR} \\\n ;\n\n# Multijob works with -runs, ignoring -atheris_runs !!!\n\nSPENT_TIME=$(date -ud \"@$(( $(date +%s) - ${START_TIME} ))\" +\"%H:%M:%S\")\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "fuzz/minimizing.sh", "content": "#!/usr/bin/env bash\n\n#set -x\nset -e\n\nSTART_TIME=$(date +%s)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at $(date)\"\nTHISDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" > /dev/null 2>&1 && pwd )\"\ncd \"${THISDIR}/..\"\n\ncp -vf fuzz/__main__.py .minimizing.py\n\nCORPUS_DIR=fuzz/corpus\nMINIMIZING_DIR=fuzz/.corpus.minimizing\n\nrm -vfr ${MINIMIZING_DIR}\n\nmkdir -vp ${MINIMIZING_DIR}\n\n# ## freeze original coverage\n\nrm -fr ${MINIMIZING_DIR}/htmlcov\n\nrm -vf .coverage\n\npython -m coverage run \\\n --source=credsweeper \\\n .minimizing.py \\\n -rss_limit_mb=2048 \\\n -atheris_runs=$(( 1 + $(ls ${CORPUS_DIR} | wc -l) )) \\\n -verbosity=1 \\\n ${CORPUS_DIR}/ \\\n ;\n\npython -m coverage report >${MINIMIZING_DIR}/report.txt\noriginal_cov=\"$(tail -1 ${MINIMIZING_DIR}/report.txt)\"\n\nif [ -n \"${PRODUCE_HTML}\" ]; then\n python -m coverage html\n mv htmlcov ${MINIMIZING_DIR}\nfi\n\n# ## run minimization for all corpuses\n\ndeclare -a CORPUS\n\ni=0\nfor f in $(ls -S ${CORPUS_DIR}); do\n CORPUS[$i]+=$f\n i=$(( 1 + $i ))\ndone\n\nfor f in ${CORPUS[@]}; do\n\n echo \"test $f\"\n mv -vf ${CORPUS_DIR}/$f ${MINIMIZING_DIR}/\n\n python -m coverage run \\\n --source=credsweeper \\\n .minimizing.py \\\n -rss_limit_mb=2048 \\\n -atheris_runs=$(( 1 + $(ls ${CORPUS_DIR} | wc -l) )) \\\n -verbosity=1 \\\n ${CORPUS_DIR}/ \\\n ;\n if [ -n \"${PRODUCE_HTML}\" ]; then\n python -m coverage html\n mv htmlcov ${MINIMIZING_DIR}/$f.htmlcov\n fi\n python -m coverage report >${MINIMIZING_DIR}/$f.txt\n test_cov=\"$(tail -1 ${MINIMIZING_DIR}/$f.txt)\"\n if [ \"$test_cov\" != \"$original_cov\" ]; then\n echo \"seed file $f impacts on coverage\"\n cp -vf ${MINIMIZING_DIR}/$f ${CORPUS_DIR}/\n else\n echo \"seed file $f does not impact on coverage\"\n fi\n\ndone\n\nSPENT_TIME=$(date -ud \"@$(( $(date +%s) - ${START_TIME} ))\" +\"%H:%M:%S\")\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "fuzz/re-fuzzing.sh", "content": "#!/usr/bin/env bash\n\nset -x\nset -e\n\nSTART_TIME=$(date +%s)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at $(date)\"\nTHISDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" > /dev/null 2>&1 && pwd )\"\nPARENTDIR=\"$(dirname ${THISDIR})\"\n\nCORPUS_DIR=fuzz/corpus\n\n# copy all current samples as additional seeds\nfind $PARENTDIR/tests/samples/* -type f -print0 | while IFS= read -r -d '' f; do\n s=$(sha1sum $f | cut -c-40)\n cp -vf $f $PARENTDIR/$CORPUS_DIR/$s\n # produce an archive without file names\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.gz\n gzip -k $PARENTDIR/$CORPUS_DIR/$s\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.gz $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.gz | cut -c-40)\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.bz2\n bzip2 -k $PARENTDIR/$CORPUS_DIR/$s\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.bz2 $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.bz2 | cut -c-40)\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.xz\n xz -z -k $PARENTDIR/$CORPUS_DIR/$s\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.xz $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.xz | cut -c-40)\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.lzma\n lzma -z -k $PARENTDIR/$CORPUS_DIR/$s\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.lzma $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.lzma | cut -c-40)\n # produce zip archive with simple file names\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.zip\n zip -j -9 -D $PARENTDIR/$CORPUS_DIR/$s.zip $f\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.zip $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.zip | cut -c-40)\n # transform name\n rm -vf $PARENTDIR/$CORPUS_DIR/$s.tar\n tar --transform='s|.*'$(basename $f)'|'$(basename $f)'|' -cf $PARENTDIR/$CORPUS_DIR/$s.tar $f\n mv -vf $PARENTDIR/$CORPUS_DIR/$s.tar $PARENTDIR/$CORPUS_DIR/$(sha1sum $PARENTDIR/$CORPUS_DIR/$s.tar | cut -c-40)\ndone\n\n# DO instrument to find new seeds with multiple jobs - effective for small set of initial seeds (corpus)\nexport DO_ATHERIS_INSTRUMENT=1\n# copy the script to apply multijob fuzzing\ncp -vf ${THISDIR}/__main__.py ${PARENTDIR}/.fuzzing.py\ncd ${PARENTDIR}\n# workers would be equal jobs obviously or it takes unpredictable time\nif [ 4 -le $(nproc) ]; then\n PROCESSES_NUMBER=$(( $(nproc) / 4 ))\nelse\n PROCESSES_NUMBER=1\nfi\n./.fuzzing.py \\\n -rss_limit_mb=6500 \\\n -runs=$(( 10000 + $(ls -1 ${CORPUS_DIR} | wc -l) )) \\\n -verbosity=1 \\\n -jobs=${PROCESSES_NUMBER} \\\n -workers=${PROCESSES_NUMBER} \\\n ${CORPUS_DIR} \\\n ;\n# clean-up\nrm -vf ${PARENTDIR}/.fuzzing.py\n# skip to avoid instrumentation during minimization\nunset DO_ATHERIS_INSTRUMENT\n\n# do reducing in single step\ncd ${THISDIR}\n(./reducing.sh)\n\n# minimization with splitting by first letter of seeds files - 8 jobs\ndeclare -A JOBS\nfor n in $(seq 0 15); do\n x=$(( 15 - ${n} ))\n j=$(printf \"%01x\" ${x})\n t=$(printf \"%01x\" $(( (${x} / 2) * 2 )))\n TARGETDIR=${THISDIR}/${t}\n mkdir -vp ${TARGETDIR}/fuzz/corpus\n cp -r ${PARENTDIR}/credsweeper ${TARGETDIR}/\n cp -v ${PARENTDIR}/.coveragerc ${TARGETDIR}/\n # import NEGLIGIBLE_ML_THRESHOLD from tests ONLY\n mkdir -vp ${TARGETDIR}/tests\n grep NEGLIGIBLE_ML_THRESHOLD ${PARENTDIR}/tests/__init__.py | tee ${TARGETDIR}/tests/__init__.py\n cp -v ${PARENTDIR}/fuzz/__main__.py ${TARGETDIR}/fuzz/\n cp -v ${PARENTDIR}/fuzz/minimizing.sh ${TARGETDIR}/fuzz/\n for f in $(find ${PARENTDIR}/${CORPUS_DIR} -type f -name \"${j}*\"); do mv -vf ${f} ${TARGETDIR}/${CORPUS_DIR}/; done\n if [ \"${t}\" == \"${j}\" ]; then\n cd ${TARGETDIR}/fuzz\n (nohup bash -c \"./minimizing.sh\") &\n job_id=$!\n JOBS[${j}]=${job_id}\n fi\n cd ${THISDIR}\ndone\n\nBUSY=8\n# wait for job finishing\nwhile [ 0 -ne ${BUSY} ]; do\n i=$(( ${BUSY} * 10 ))\n echo -en \"\\nSleep seconds:\"\n while [ 0 -lt $i ]; do\n echo -n \" $i\"\n i=$(( ${i} - 1 ))\n sleep 1\n done\n BUSY=0\n echo -en \"\\nCheck jobs:\"\n for x in $(seq 0 15); do\n j=$(printf \"%01x\" ${x})\n job_id=${JOBS[$j]}\n if [ -z \"${job_id}\" ]; then\n continue\n elif kill -0 ${job_id}; then\n BUSY=$(( 1 + ${BUSY} ))\n echo -n \" job $j is alive\"\n else\n echo -n \" job $j has done\"\n fi\n done\ndone\n\nunset JOBS\n\n# collect\nfor x in $(seq 0 15); do\n j=$(printf \"%01x\" ${x})\n TARGETDIR=${THISDIR}/${j}\n for f in $(find ${TARGETDIR}/${CORPUS_DIR} -type f); do mv -vf ${f} ${PARENTDIR}/${CORPUS_DIR}/; done\n rm -fr ${TARGETDIR}\ndone\n\n# last minimization\ncd ${THISDIR}\n(./minimizing.sh)\n\nSPENT_TIME=$(date -ud \"@$(( $(date +%s) - ${START_TIME} ))\" +\"%H:%M:%S\")\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "fuzz/reducing.sh", "content": "#!/usr/bin/env bash\n\n#set -x\nset -e\n\nSTART_TIME=$(date +%s)\necho \">>> START ${BASH_SOURCE[0]} in $(pwd) at $(date)\"\nTHISDIR=\"$( cd \"$( dirname \"${BASH_SOURCE[0]}\" )\" > /dev/null 2>&1 && pwd )\"\ncd \"${THISDIR}/..\"\n\nCORPUS_DIR=fuzz/corpus\nREDUCING_DIR=fuzz/.corpus.reducing\n\n# DO instrument to find new seeds\nexport DO_ATHERIS_INSTRUMENT=1\n\nfunction get_size()\n{\n r=0\n if [ -d $1 ]; then\n for f in $(find $1 -type f); do\n r=$(( $r + $(stat --format=%s $f) ))\n done\n fi\n echo $r\n}\n\nfunction get_count()\n{\n r=0\n if [ -d $1 ]; then\n r=$(ls $1 | wc -l)\n fi\n echo $r\n}\n\nuniq_corpus_size=$(get_size ${CORPUS_DIR})\nfull_corpus_size=$(get_size ${REDUCING_DIR})\n\nuniq_corpus_count=$(get_count ${CORPUS_DIR})\nfull_corpus_count=$(get_count ${REDUCING_DIR})\n\ncp -vf fuzz/__main__.py .reducing.py\n\nwhile [ $uniq_corpus_size -ne $full_corpus_size ] || [ $uniq_corpus_count -ne $full_corpus_count ]; do\n\n if [ 0 -eq $uniq_corpus_count ]; then\n echo \"ERROR: Empty input ${CORPUS_DIR} dir!\"\n exit 1;\n fi\n\n rm -vfr ${REDUCING_DIR}\n mkdir -vp ${REDUCING_DIR}\n mv -vf ${CORPUS_DIR}/* ${REDUCING_DIR}/\n\n ./.reducing.py \\\n -rss_limit_mb=6000 \\\n -verbosity=1 \\\n -merge=1 \\\n ${CORPUS_DIR}/ \\\n ${REDUCING_DIR}/ \\\n ;\n \n uniq_corpus_size=$(get_size ${CORPUS_DIR})\n full_corpus_size=$(get_size ${REDUCING_DIR})\n\n uniq_corpus_count=$(get_count ${CORPUS_DIR})\n full_corpus_count=$(get_count ${REDUCING_DIR})\n\n if [ 0 -eq $uniq_corpus_size ] || \\\n [ 0 -eq $full_corpus_size ] || \\\n [ 0 -eq $uniq_corpus_count ] || \\\n [ 0 -eq $full_corpus_count ]; then\n echo \"something went wrong\"\n exit 1\n fi\ndone\n\nif [ $uniq_corpus_size -eq $full_corpus_size ] && [ $uniq_corpus_count -eq $full_corpus_count ]; then\n rm -vfr .reducing.py ${REDUCING_DIR}\nfi\n\nSPENT_TIME=$(date -ud \"@$(( $(date +%s) - ${START_TIME} ))\" +\"%H:%M:%S\")\necho \"<<< DONE ${BASH_SOURCE[0]} in $(pwd) at $(date) elapsed ${SPENT_TIME}\"\n" }, { "path": "fuzz/requirements.txt", "content": "# Fuzzing\natheris==2.3.0; python_version < '3.12'\natheris==3.0.0; python_version >= '3.12' and python_version < '3.14'\n\n# auxiliary. should be installed from ../requirements.txt (pytest-cov)\ncoverage\n" }, { "path": "pyproject.toml", "content": "[project]\nname = \"credsweeper\"\ndynamic = [\"version\"]\ndescription = \"Credential Sweeper\"\nauthors = [\n]\ndependencies = [\n \"base58\",\n \"beautifulsoup4>=4.11.0\",\n \"colorama\",\n \"cryptography\",\n \"GitPython\",\n \"humanfriendly\",\n \"lxml\",\n \"numpy\",\n \"odfpy\",\n \"onnxruntime\",\n \"openpyxl\",\n \"pandas\",\n \"pdfminer.six\",\n \"pybase62\",\n \"pyjks\",\n \"python-dateutil\",\n \"python-docx\",\n \"python-pptx\",\n \"PyYAML\",\n \"pyxlsb\",\n \"rpmfile\",\n \"striprtf\",\n \"whatthepatch\",\n \"xlrd\",\n]\nrequires-python = \">=3.10\"\nreadme = \"README.md\"\nlicense = {text = \"MIT\"}\nclassifiers = [\n \"License :: OSI Approved :: MIT License\",\n \"Operating System :: OS Independent\",\n \"Programming Language :: Python :: 3\",\n \"Programming Language :: Python :: 3 :: Only\",\n \"Programming Language :: Python :: 3.10\",\n \"Programming Language :: Python :: 3.11\",\n \"Programming Language :: Python :: 3.12\",\n \"Programming Language :: Python :: 3.13\",\n \"Programming Language :: Python :: 3.14\",\n \"Topic :: Security\",\n \"Topic :: Software Development :: Quality Assurance\",\n]\n\n[project.urls]\nHomepage = \"https://github.com/Samsung/CredSweeper\"\n\"Bug Tracker\" = \"https://github.com/Samsung/CredSweeper/issues\"\n\n[build-system]\nrequires = [\"hatchling\"]\nbuild-backend = \"hatchling.build\"\n\n[tool.hatch.version]\npath = \"credsweeper/__init__.py\"\n\n[tool.hatch.build.targets.sdist]\nignore-vcs = true\nonly-include = [\"/credsweeper\"]\n\n[project.scripts]\ncredsweeper = \"credsweeper.__main__:main\"\n" }, { "path": "pytest.ini", "content": "[pytest]\npythonpath = credsweeper\ntestpaths = tests\n" }, { "path": "requirements.txt", "content": "# Python 3.10.20\n# pip 26.0.1\n\n# build requirement\nbuild==1.5.0\nhatchling==1.29.0\n# 1.27.0 creates Metadata-Version: 2.4 which is not supported fully by publish github action\n#hatchling==1.26.3\n# check build\ntwine==6.2.0\n\n# Common requirements\nbase58==2.1.1\nbeautifulsoup4==4.14.3\ncolorama==0.4.6\ncryptography==48.0.0\nGitPython==3.1.50\nhumanfriendly==10.0\nlxml==6.1.0\nnumpy==2.2.6; python_version == '3.10'\nnumpy==2.4.4; python_version > '3.10'\nodfpy==1.4.1\nxlrd==2.0.2\nstriprtf==0.0.32\n\n# onnxruntime - ML engine\nonnxruntime==1.23.2; python_version < '3.14'\nonnxruntime==1.26.0; python_version >= '3.14'\n\n# openpyxl - A Python library to read/write Excel 2010 xlsx/xlsm files\nopenpyxl==3.1.5\n\n# pandas - ML requirement and excel data reading\npandas==2.3.3; python_version == '3.10'\npandas==3.0.3; python_version > '3.10'\n\npdfminer.six==20260107\npybase62==1.0.0\npyjks==20.0.0\npython-dateutil==2.9.0.post0\npython-docx==1.2.0\npython-pptx==1.0.2\nPyYAML==6.0.3\npyxlsb==1.0.10\nrpmfile==2.2.1\nwhatthepatch==1.0.7\n\n# Auxiliary packages for development\n# tests\ndeepdiff\nflake8\nhypothesis\npytest\npytest-cov\npytest-html\npytest-random-order\n\n# linters\npylint\nmypy\nyapf\n\n# stubs\nlxml-stubs\npandas-stubs\n\n# types\ntypes-beautifulsoup4\ntypes-colorama\ntypes-lxml\ntypes-PyYAML\ntypes-python-dateutil\ntypes-pyjks\ntypes-regex\ntypes-humanfriendly\ntypes-whatthepatch\n" }, { "path": "tests/README.md", "content": "# About the test credentials\n\nAll credentials that in this directory are invalid credentials.\nThey are just test purpose credentials for CredSweeper.\nSo don't confuse it as an actual credential.\n" }, { "path": "tests/__init__.py", "content": "from pathlib import Path\n\n# total number of files in test samples\nSAMPLES_FILES_COUNT = 198\n\n# ML_DELTA for different platforms which may produce a dribbling in ml_probability\nML_DELTA = 0.0001\n\n# float value of ML threshold is used to display possible lowest values\nZERO_ML_THRESHOLD = 0.0\n\n# with option --doc & ZERO_ML_THRESHOLD\nSAMPLES_IN_DOC = 959\n\n# credentials count after scan without filters and ML validations\nSAMPLES_REGEX_COUNT = 716\n\n# credentials count after scan with filters and without ML validation\nSAMPLES_FILTERED_COUNT = 579\n\n# credentials count after default post-processing\nSAMPLES_POST_CRED_COUNT = 531\n\n# archived credentials that are not found without --depth\nSAMPLES_IN_DEEP_1 = SAMPLES_POST_CRED_COUNT + 140\nSAMPLES_IN_DEEP_2 = SAMPLES_IN_DEEP_1 + 13\nSAMPLES_IN_DEEP_3 = SAMPLES_IN_DEEP_2 + 4\n\n# well known string with all latin letters\nAZ_DATA = b\"The quick brown fox jumps over the lazy dog\"\n# Assume, there should be only ASCII symbols\nAZ_STRING = AZ_DATA.decode(encoding=\"ascii\", errors=\"strict\")\n\n# tests directory - use ONLY this file relevance for \"release_test\" workflow\nTESTS_PATH = Path(__file__).resolve().parent\n# test samples directory\nSAMPLES_PATH = TESTS_PATH / \"samples\"\nSAMPLE_TAR = SAMPLES_PATH / \"pem_key.tar\"\nSAMPLE_ZIP = SAMPLES_PATH / \"pem_key.zip\"\nSAMPLE_HTML = SAMPLES_PATH / \"test.html\"\nSAMPLE_DOCX = SAMPLES_PATH / \"sample.docx\"\nSAMPLE_PY = SAMPLES_PATH / \"sample.py\"\nSAMPLE_DEB = SAMPLES_PATH / \"sample.deb\"\nSAMPLE_SQLITE = SAMPLES_PATH / \"sample.sqlite\"\n" }, { "path": "tests/common/__init__.py", "content": "" }, { "path": "tests/common/test_confidence.py", "content": "import unittest\n\nfrom credsweeper.common.constants import Confidence\n\n\nclass TestConfidence(unittest.TestCase):\n\n def test_severity_p(self):\n self.assertEqual(Confidence.MODERATE, Confidence.get(Confidence.MODERATE))\n self.assertEqual(Confidence.WEAK, Confidence.get(\"WeaK\"))\n self.assertEqual(Confidence.MODERATE, Confidence.get(\"MODERATE\"))\n self.assertEqual(Confidence.STRONG, Confidence.get(\"strong\"))\n\n def test_severity_n(self):\n self.assertIsNone(Confidence.get(None))\n self.assertIsNone(Confidence.get(1))\n self.assertIsNone(Confidence.get([1, 2, 3]))\n self.assertIsNone(Confidence.get({1, 2, 3}))\n self.assertIsNone(Confidence.get(\"None\"))\n self.assertIsNone(Confidence.get(\"HI-GH\"))\n self.assertIsNone(Confidence.get(\" HI GH \"))\n\n def test_severity_comparison_p(self):\n self.assertTrue(Confidence.WEAK < Confidence.MODERATE)\n self.assertTrue(Confidence.WEAK < Confidence.STRONG)\n self.assertTrue(Confidence.MODERATE < Confidence.STRONG)\n test_list = [Confidence.MODERATE, Confidence.STRONG, Confidence.WEAK]\n test_list.sort()\n self.assertListEqual([Confidence.WEAK, Confidence.MODERATE, Confidence.STRONG], test_list)\n\n def test_severity_comparison_n(self):\n self.assertFalse(Confidence.MODERATE < Confidence.WEAK)\n self.assertFalse(Confidence.WEAK > Confidence.MODERATE)\n self.assertFalse(Confidence.WEAK > Confidence.STRONG)\n self.assertFalse(Confidence.MODERATE > Confidence.STRONG)\n" }, { "path": "tests/common/test_keyword_checklist.py", "content": "from unittest import TestCase\n\nfrom credsweeper.common import KeywordChecklist\nfrom credsweeper.utils.util import Util\n\n\nclass TestKeywordChecklist(TestCase):\n\n def test_keyword_set_p(self):\n # quick test to match all keywords for regex\n for i in KeywordChecklist().keyword_set:\n self.assertLessEqual(3, len(i))\n self.assertRegex(i, r\"[a-z0-9.]{3,500}\")\n\n def test_morpheme_set_p(self):\n # quick test to match all morphemes for regex\n for i in KeywordChecklist().morpheme_set:\n self.assertLessEqual(3, len(i))\n # valid symbols for variable names\n self.assertRegex(i, r\"[a-z0-9_/.\\\\:]{3,500}\")\n\n def test_keyword_set_n(self):\n # checks whether the keywords are unique, in lower case and not shorter than 3 symbols\n keyword_checklist_bytes = Util.read_data(KeywordChecklist.KEYWORD_PATH)\n keyword_set = set(keyword_checklist_bytes.decode().split())\n new_set = set()\n wrong_items = []\n for i in keyword_set:\n if i.lower() == i and 3 <= len(i):\n new_set.add(i)\n else:\n wrong_items.append(i)\n if wrong_items:\n # writes correct checklist to output file - it must be applied\n with open(KeywordChecklist.KEYWORD_PATH, \"w\") as f:\n # use alphabet sorting to keep constant order and reduce git diff\n text = '\\n'.join(sorted(list(new_set)))\n f.write(text)\n f.write('\\n')\n self.assertFalse(wrong_items, \"Keywords list has been rearranged and updated\")\n\n def test_morpheme_set_n(self):\n # check whether the morphemes are optimized and updates the file with optimized list\n morpheme_checklist_data = Util.read_data(KeywordChecklist.MORPHEME_PATH)\n original_morpheme_list = morpheme_checklist_data.decode().split()\n original_morpheme_list_len = len(original_morpheme_list)\n morpheme_set = set(original_morpheme_list)\n optimized_morpheme_list = sorted(list(morpheme_set), key=lambda e: len(e))\n\n is_optimized = False\n while not is_optimized:\n morphemes_to_remove_set = set()\n optimized_morpheme_list_len = len(optimized_morpheme_list)\n idx = 0\n for optimized_morpheme in optimized_morpheme_list:\n idx += 1\n if optimized_morpheme.lower() == optimized_morpheme and 3 <= len(optimized_morpheme):\n # search in rest list whether the items have the substring\n local_idx = idx\n while local_idx < optimized_morpheme_list_len:\n if optimized_morpheme in optimized_morpheme_list[local_idx]:\n # longer morpheme should be removed because it includes short morpheme inside\n morphemes_to_remove_set.add(optimized_morpheme_list[local_idx])\n local_idx += 1\n else:\n # wrong - must be removed\n morphemes_to_remove_set.add(optimized_morpheme)\n for to_remove in morphemes_to_remove_set:\n optimized_morpheme_list.remove(to_remove)\n is_optimized = 0 == len(morphemes_to_remove_set)\n diff = original_morpheme_list_len - len(optimized_morpheme_list)\n if diff:\n with open(KeywordChecklist.MORPHEME_PATH, \"w\") as f:\n # use alphabet sorting to keep constant order and reduce git diff\n text = '\\n'.join(sorted(optimized_morpheme_list))\n f.write(text)\n f.write('\\n')\n self.assertEqual(0, diff, \"Morpheme list has been rearranged and updated\")\n" }, { "path": "tests/common/test_keyword_pattern.py", "content": "import pytest\n\nfrom credsweeper.common.keyword_pattern import KeywordPattern\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.utils.util import Util\nfrom tests.filters.conftest import KEYWORD_PASSWORD_PATTERN\n\n\nclass TestKeywordPattern:\n\n @pytest.mark.parametrize(\"line\", [\"melon is 'banana'\"])\n def test_separator_n(self, config: Config, file_path: pytest.fixture, line: str) -> None:\n pattern = KeywordPattern.get_keyword_pattern(\"melon\")\n line_data = LineData(config,\n line,\n 0,\n 1,\n file_path,\n Util.get_extension(file_path),\n info=\"dummy\",\n pattern=pattern)\n assert line_data.value is None\n\n @pytest.mark.parametrize(\"line\", [\"melon = 'banAna'\", \"melon : 'banAna'\", \"melon := 'banAna'\"])\n def test_separator_p(self, config: Config, file_path: pytest.fixture, line: str) -> None:\n pattern = KeywordPattern.get_keyword_pattern(\"melon\")\n line_data = LineData(config,\n line,\n 0,\n 1,\n file_path,\n Util.get_extension(file_path),\n info=\"dummy\",\n pattern=pattern)\n assert line_data.value == \"banAna\"\n\n @pytest.mark.parametrize(\n \"line, value\",\n [\n # [\"\"\"password='\\\\\\\\'secret-1\\\\\\\\''\"\"\", \"\"\"\\\\'secret-1\\\\'\"\"\"], # todo\n # ['''password=\"\\\\\"secret-2\\\\\"\"''', '''\\\\\"secret-2\\\\\"'''], # todo\n # [\"\"\"password=rb'\\\\'secret=1\\\\''\"\"\", \"\"\"\\\\'secret=1\\\\'\"\"\"], # todo\n # ['''password=f\"\\\\\"secret=2\\\\\"\"''', '''\\\\\"secret=2\\\\\"'''], # todo\n # ['''password=r\"\\\\\\\\\"secret=3\\\\\\\\\"\"''', '''\\\\\"secret=3\\\\\"'''], # todo\n # ['''\"password = 'sec;$2`\\\\'[\\\\/*;ret';\";''', '''sec;$2`\\\\'[\\\\/*;ret'''], # todo\n ['PASSWORD = os.environ.get(\"PASSWORD\") or \"at5G6zi!m\"', \"at5G6zi!m\"],\n [\"deFINE \\\\n\\\\t('DB_PASSWORD',\\\\n\\\\t'devSeCrEt');\", \"devSeCrEt\"],\n ['''...log=1;User ID=X3;password=Quantum42!\\\\\"\"''', '''Quantum42!'''],\n [\n 'Password: []byte{134, 217, 176, 23, 206, 245, 164, 94, 102, 114, 172, 33, 248, 215, 246, 357},',\n '134, 217, 176, 23, 206, 245, 164, 94, 102, 114, 172, 33, 248, 215, 246, 357'\n ],\n [\n 'password = util.getPasswordFromHex(\"c275ecec7b5eda8a330bec5bc275b3f1\", None)',\n \"c275ecec7b5eda8a330bec5bc275b3f1\"\n ],\n ['password = util.getPassword(\"User1\", \"D3fa9UL7Pa5s\")', \"D3fa9UL7Pa5s\"],\n ['password = i[2].get(\"PASS\", \"D3fA9UL7Pa5s\")', \"D3fA9UL7Pa5s\"],\n ['password = os.getenv(\"DB_PASS\", \"D3fA9Ul7pAs5\")', \"D3fA9Ul7pAs5\"],\n [\"password = data.get ( 'MY_PASS' , default = 'D3fA9Ul7pA5s' ) \", \"D3fA9Ul7pA5s\"],\n [\n 'PASSWORD = bytes([0xDF, 0x42, 0xD8, 0x34, 0xDD, 0x1E, 0xD8, 0x24, 0xD8, 0x37, 0xD8, 0x01, 0xD8, 0x52])',\n \"0xDF, 0x42, 0xD8, 0x34, 0xDD, 0x1E, 0xD8, 0x24, 0xD8, 0x37, 0xD8, 0x01, 0xD8, 0x52\"\n ],\n ['password = superCrypto ( \"CEKPET\" ) ;', \"CEKPET\"],\n ['self.setPassword(\"0bead47f3c5bc275ec7b5eda8a333f\")', \"0bead47f3c5bc275ec7b5eda8a333f\"],\n ['if str(password) == \"0bead47f3c5bc275ec7b5eda8a333f\":', \"0bead47f3c5bc275ec7b5eda8a333f\"],\n ['if [[ \"%{password}\" =~ \"himmelsrand\" ]]; then', 'himmelsrand'],\n [\"setPasssword ( 'MY_TEST&PASSWORD!',\", \"MY_TEST&PASSWORD!\"],\n [\"setPasssword('MY_TEST&PASSWORD!')\", \"MY_TEST&PASSWORD!\"],\n ['#define password {0x35, 0x34, 0x65, 0x9b, 0x1c, 0x2e}', '0x35, 0x34, 0x65, 0x9b, 0x1c, 0x2e'],\n ['#define password {0x35, 0x34, 0x65, 0x9b, 0x1c, 0x2e \\\\', '0x35, 0x34, 0x65, 0x9b, 0x1c, 0x2e \\\\'],\n ['#define password \";,}d4s@\\\\on\"', \";,}d4s@\\\\on\"],\n ['%define password \"CEKPET\"', \"CEKPET\"],\n [\"set password CEKPET\", \"CEKPET\"],\n ['password = get_password(option1=\"CEKPET\", option2=\"KOMETA\")', \"CEKPET\"],\n [\n '{\"PWD\":[{\"kty\":\"oct\",\"kid\":\"25b58GCM\",\"k\":\"Xc_2A\"},{\"kty\":\"oct\",\"kid\":\"09b51KW\",\"k\":\"KG6wlB-6sIVQ\"}]',\n '\"kty\":\"oct\",\"kid\":\"25b58GCM\",\"k\":\"Xc_2A\"'\n ],\n [\n '{\"PWD\":[{\"ktyX\":\"oct\",\"kid\":\"25b58GCM\",\"k\":\"Xc_2A\"},{\"kty\":\"oct\",\"kid\":\"09b51KW\",\"k\":\"KG6wlB-6sIVQ\"}]',\n 'ktyX' # todo \"ktyX\":\"oct\",\"kid\":\"25b58GCM\",\"k\":\"Xc_2A\"\n ],\n [\"pass = Super::Encryptor('seCreT', 'secRet2');\", \"seCreT\"],\n ['PWD = {\"123\": \"08c8b5b3\", 456: \"07c6aa05\"}', '\"123\": \"08c8b5b3\", 456: \"07c6aa05\"'],\n ['PWD = {\"1234\": \"abcd\", 1: \"efgh\"}', '1234'],\n [\"password: { other_secret: 'GehE1mNi5',\", \"GehE1mNi5\"],\n [\"byte[] password = new byte[]{0x3, 0x5, 0x8, 0x3, 0x5, 0x8};\", \"0x3, 0x5, 0x8, 0x3, 0x5, 0x8\"],\n [\"byte[]password=new byte[]{0x3,0x5,0x8,0x3,0x5,0x8};\", \"0x3,0x5,0x8,0x3,0x5,0x8\"],\n [\"char[] password = new char[]{'f',\\\\x03, 02 ,'1', 0};\", \"'f',\\\\x03, 02 ,'1', 0\"],\n [\"char password[] = {'H', 'e', 'l', 'l', 'o', '\\0'};\", \"'H', 'e', 'l', 'l', 'o', '\\0'\"],\n [\"char password[] = {0x34, 0x53, 0x53, 0x62, 000};\", \"0x34, 0x53, 0x53, 0x62, 000\"],\n [\"char[] password = new char[]{'b', 'y', 't', 'e', 's', '\\\\0'};\", \"'b', 'y', 't', 'e', 's', '\\\\0'\"],\n [\"char[] password = new char[]{023, 010, 041, 033, 043, 000};\", \"023, 010, 041, 033, 043, 000\"],\n ['final String [] password = new String [] { \"GehE1mNi5\",', 'GehE1mNi5'],\n [\"private static readonly byte[] password = new byte[] { 'X','3', '4', '0' \\\\\", \"'X','3', '4', '0' \\\\\"],\n [\"password=${REMOVE_PREFIX#prefix}\", \"${REMOVE_PREFIX#prefix}\"],\n [\"password='${REMOVE_PREFIX#prefix}'\", \"${REMOVE_PREFIX#prefix}\"],\n [\"password=${cat pass}\", \"${cat\"],\n ['password=$(echo \"pass\")', \"$(echo\"],\n [\"password='$(( 1 + 2 + 3 + 4 ))'\", \"$(( 1 + 2 + 3 + 4 ))\"],\n [\"password=$(( 1 + 2 + 3 + 4 ))\", \"$(( 1 + 2 + 3 + 4 ))\"],\n [\"password='$[[ 1 + 2 + 3 + 4 ]]'\", \"$[[ 1 + 2 + 3 + 4 ]]\"],\n [\"password=$[[ 1 + 2 + 3 + 4 ]]\", \"\"], # obsolete\n [\"password=$[[_1_+_2_+_3_+_4_]]\", \"$[[_1_+_2_+_3_+_4_]]\"],\n [\"password=${array[@]:7:2}\", \"${array[@]:7:2}\"],\n [\"password=${1#*=}\", \"${1#*=}\"],\n [\"A2 ID:master,PW:dipPr10Gg!\", \"dipPr10Gg!\"],\n [\"pass=get->pass(arg1='seCreT', arg2='secRet2'...\", \"seCreT\"],\n [\"The test password => skWu850\", \"skWu850\"],\n [\"$password = Hash::make('GehE1mNi5');\", \"GehE1mNi5\"],\n ['password = new[] {\"GehE1mNi5\"}', \"GehE1mNi5\"],\n [\"password, _ = hex.DecodeString('e1efa5ca09a6beac387c04a5cdc1d491')\", \"e1efa5ca09a6beac387c04a5cdc1d491\"],\n [\"MY_TEST_PASSWORD='(MY_TEST_PASSWORD)'\", \"(MY_TEST_PASSWORD)\"],\n [\"MY_TEST_PASSWORD=$(MY_TEST_PASSWORD)\", \"$(MY_TEST_PASSWORD)\"],\n [\"MY_TEST_PASSWORD='$(MY_TEST_PASSWORD)'\", \"$(MY_TEST_PASSWORD)\"],\n # https://www.gnu.org/savannah-checkouts/gnu/bash/manual/bash.html#Shell-Expansions\n [\"MY_TEST_PASSWORD=${MY_VAR:?THE VAR IS UNSET}\", \"${MY_VAR:?THE\"],\n ['''ClientPasswords = new[] { new Password( \"SECRET\".Sha256() ) },''', \"SECRET\"],\n ['''\"$password = \"10qoakxncnfh47t_''', '''10qoakxncnfh47t_'''], #\n [\n '''copes\\\":[\\\"user\\\"],\\\"note\\\":\\\"Note\\\",\\\"password\\\":\\\"cc6323cb2223f82f01\\\",\\\"upd_at\\\":\\\"1765....\\\",''',\n '''cc6323cb2223f82f01'''\n ], #\n ['''\"password = pas:sword # comment''', '''pas:sword'''],\n ['''x.password=pK5C4tlA/w1cO\\\\=\\\\=''', '''pK5C4tlA/w1cO\\\\=\\\\='''], #\n ['''final String body = \\\"{ \\\\\"passwords\\\\\":\\\\\"i0sEcReT\\\\\\\\/MwX3X\\\\\",\"''', '''i0sEcReT\\\\\\\\/MwX3X'''],\n [\n '''\\\\\\\"password\\\\\\\"=\\\\u0026gt;\\t\\\\n\\\\t\\\\\\\"lfFTfDT1roc4YbG9hy5cnvX\\\\n oZ+Sc/wb+CvdF4s==\\\\\\\",\\\\n\",''',\n '''lfFTfDT1roc4YbG9hy5cnvX\\\\n oZ+Sc/wb+CvdF4s=='''\n ],\n [\n '''var request = {\"password\": \"{\\\\\"wks\\\\\": \\\\\"8x9s3ga7\\\\\", \\\\\"uzr\\\": \\\\\"wbm\\\\\"}\",\"Any-Tail\":\"x\\r\"};''',\n '''{\\\\\"wks\\\\\": \\\\\"8x9s3ga7\\\\\", \\\\\"uzr\": \\\\\"wbm\\\\\"}'''\n ],\n ['''passwords: [\"1029384756\",''', '''1029384756'''], #\n ['''passwords:[ \"1029384756\", \"9801726354\" ]''', '''1029384756'''], #\n ['''password=\"\\\\\"secret-line-wrap\\\\''', '''secret-line-wrap'''], #\n ['''password=r\"\"\"secret4\"\"\"''', '''secret4'''], #\n ['''password=r\\\\\"\\\\\"\\\\\"secret5\\\\\"\\\\\"\\\\\"''', '''secret5'''], #\n ['''password=\"\"\"secret6\"\"\"''', '''secret6'''], #\n ['''password=\\\\\\\\\"\\\\\\\\\"\\\\\\\\\"secret7\\\\\\\\\"\\\\\\\\\"\\\\\\\\\"''', '''secret7'''], #\n ['''password=\\\\\\\\\"\\\\\\\\\"\\\\\\\\\"secret\"7\\\\\\\\\"\\\\\\\\\"\\\\\\\\\"''', '''secret\"7'''], #\n ['''password=\"\"\"{\\\\\"secret8\\\\\"}\"\"\"''', '''{\\\\\"secret8\\\\\"}'''], #\n ['''password=\"\"\"secret'9\"\"\"''', '''secret'9'''], #\n [\"\"\"password='''secret'6'''\"\"\", '''secret'6'''], #\n [\"\"\"password='''secret`8'''\"\"\", '''secret`8'''], #\n [\"\"\"password=``secret`7``\"\"\", '''secret`7'''], #\n [\"\"\"password=``secret 5``\"\"\", '''secret 5'''], #\n [\"\"\"password='secret\\\\ 5''\"\"\", '''secret\\\\ 5'''], #\n [\"\"\"password=secret\\\\ 5\"\"\", '''secret\\\\ 5'''], #\n [\"\"\"password=secret 0\"\"\", '''secret'''], #\n [\"\"\"password=secret0\\\\\"\"\", '''secret0'''], #\n [\"\"\"password=r'\\\\\"secret\\\\\"'\"\"\", '''\\\\\"secret\\\\\"'''], #\n ['''password=r\\\\\"{\\\\\\\\\"secret\\\\\\\\\"}\\\\\"''', '{\\\\\\\\\"secret\\\\\\\\\"}'], #\n ['''password=r\"{\\\\\"secret\\\\\"}\"''', '{\\\\\"secret\\\\\"}'], #\n [\"\"\"password=b'\"secret4\"'\"\"\", '\"secret4\"'], #\n [\"\"\"password=rb'\\\\\\\\\"secret\\\\\\\\\"'\"\"\", '\\\\\\\\\"secret\\\\\\\\\"'], #\n [\"\"\"password=r\\\\'\"sec'\"'\"'\"ret\"\\\\'\"\"\", '''\"sec'\"'\"'\"ret\"'''], #\n [\"\"\"\\\\'\\\\\\\\\\\\\\\\'password\\\\\\\\\\\\\\\\': b\\\\\\\\\\\\\\\\'secret\\\\\\\\\\\\\\\\'\\\\'\"\"\", \"secret\"], #\n [\"\"\"'password': b'secret'\"\"\", \"\"\"secret\"\"\"], #\n [\"\"\"'password': r'secret'\"\"\", \"\"\"secret\"\"\"], #\n [\"\"\"'password': fr'secret'\"\"\", \"\"\"secret\"\"\"], #\n [\"\"\"'password': t'{secret}'\"\"\", \"\"\"{secret}\"\"\"], #\n [\"\"\"\\\\'password\\\\': \\\\'secret\\\\'\"\"\", \"\"\"secret\"\"\"], #\n ['''db.setCred(\"{ \\\"password\\\" : \\\"\" + SECRET + \"\\\" }\");''', ''' + SECRET + '''],\n ['''\\\\\"password\\\\\": \\\\\"{\\\\\\\\\"secret\\\\\\\\\": \\\\\\\\\"test\\\\\\\\\"}\\\\\"''', '{\\\\\\\\\"secret\\\\\\\\\": \\\\\\\\\"test\\\\\\\\\"}'], #\n ['''\"password\": \"{\\\\\\\\\"secret\\\\\\\\\": \\\\\\\\\"test\\\\\\\\\"}\"''', '{\\\\\\\\\"secret\\\\\\\\\": \\\\\\\\\"test\\\\\\\\\"}'], #\n # normal_str = \"First line.\\nSecond line.\\nEnd of message.\\n\";\n ['''std::string password = R\"multiline\\\\npassword\";''', '''multiline\\\\npassword'''], #\n ['''const wchar_t* password = L\"wchar_t*secret\";''', '''wchar_t*secret'''], #\n ['''const char16_t* password = U\"char16_t*secret\";''', '''char16_t*secret'''], #\n [\"\"\"char password[] = {'S', 'E', 'C', 'R', 'E', 'T', '\\\\0'};\"\"\", \"\"\"'S', 'E', 'C', 'R', 'E', 'T', '\\\\0'\"\"\"\n ], #\n ['''\"password\": \"{8vi6wL+10fI/eibC7wFwc}\"''', '{8vi6wL+10fI/eibC7wFwc}'], #\n ['''final String password = new String(\"SECRET\") {''', '''SECRET'''], #\n ['''final OAuth2AccessToken password = new OAuth2AccessToken(\\\"SEC.RET\\\");''', '''SEC.RET'''], #\n ['''password = obfuscate(arg=\"SECRET\") {''', '''SECRET'''], #\n ['''final String password = new String(Super(Encrypted(\"SECRET\"))) {''', '''SECRET'''], #\n ['''final String password = new String(Super( Encrypted(\"SECRET\", \"dummy\"))) {''', '''SECRET'''], #\n [\"\"\"'password': 'ENC(lqjdoxlandicpfpqk)'\"\"\", \"\"\"ENC(lqjdoxlandicpfpqk)\"\"\"], #\n [\"\"\"'password': 'ENC[lqjdoxlandicpfpqk]'\"\"\", \"\"\"ENC[lqjdoxlandicpfpqk]\"\"\"], #\n ['''password24=secret42''', 'secret42'], #\n ['''password24=secret42\\\\ ''', 'secret42\\\\ '], #\n ['''password24=secret42\\\\''', 'secret42'], #\n ['''password24=secret42\\\\n''', 'secret42'], #\n ['password = 3VNdhWT3oFo5I7faffKO\\\\\\neEagnK7tYBcGxhla\\n;', '''3VNdhWT3oFo5I7faffKO'''],\n ['password = \"3VNdhWT3oFo5I7faffKO\\n gnK7tYBcGxhla\\n\";', '''3VNdhWT3oFo5I7faffKO\\n gnK7tYBcGxhla\\n'''],\n [\n \"//&user%5Bemail%5D=credsweeper%40example.com&user%5Bpassword%5D=Dmdkesfdsq452%23%40!&user%5Bpassword_\",\n \"Dmdkesfdsq452%23%40!\"\n ],\n [\"password%3dDmsfdsq452!&user%5Bpassword_\", \"Dmsfdsq452!\"],\n [\"MY_TEST_PASSWORD={MY_TEST_PASSWORD}\", \"MY_TEST_PASSWORD\"],\n [\"MY_TEST_PASSWORD=(MY_TEST_PASSWORD)\", \"MY_TEST_PASSWORD\"],\n [\"MY_TEST_PASSWORD=\", \"\"], # <> are used in future to detect a template\n [\"MY_TEST_PASSWORD=[MY_TEST_PASSWORD]\", \"MY_TEST_PASSWORD\"],\n [\"MY_TEST_PASSWORD=MY_TEST&PASSWORD!\", \"MY_TEST&PASSWORD!\"],\n [\"MY_TEST_PASSWORD='MY_TEST&PASSWORD!'\", \"MY_TEST&PASSWORD!\"],\n ])\n def test_keyword_pattern_p(self, config: Config, file_path: pytest.fixture, line: str, value: str) -> None:\n line_data = LineData(config,\n line,\n 0,\n 1,\n file_path,\n Util.get_extension(file_path),\n info=\"dummy\",\n pattern=KEYWORD_PASSWORD_PATTERN)\n assert line_data.value == value, KEYWORD_PASSWORD_PATTERN.pattern\n\n @pytest.mark.parametrize(\"line\", [\n \"set_unusable_api() should not found\",\n \"https://fonts.googleapis.com/css2?family=Montserrat:wght@500;700;900&family=Roboto:wght@300;400;500;700;900\"\n \"&family=Roboto+Mono:wght@300;400;600;900&display=swap\",\n \"reset api example\",\n ])\n def test_keyword_pattern_n(self, config: Config, file_path: pytest.fixture, line: str) -> None:\n pattern = KeywordPattern.get_keyword_pattern(\"api\")\n line_data = LineData(config, line, 0, 1, file_path, \"file_type\", \"info\", pattern)\n assert line_data.value is None\n" }, { "path": "tests/common/test_regex.py", "content": "import re\n\nimport pytest\n\n\nclass TestRegex:\n TEST_AWS_ID = \"ASIA0123456789ABCDEF\"\n TEST_AWS_REGEX = re.compile(\"(^|[^0-9A-Za-z])(?P(AKIA|ASIA)[0-9A-Z]{16,17})([^0-9A-Za-z]|$)\")\n\n @pytest.mark.parametrize( #\n 'text', #\n [ #\n f\"{TEST_AWS_ID}XX\", # 22 symbols\n f\"i{TEST_AWS_ID}\", #\n f\"X{TEST_AWS_ID}\", #\n f\"{TEST_AWS_ID[0:18]}\", #\n f\"{TEST_AWS_ID[0:18]}x\", #\n f\"{TEST_AWS_ID[0:18]}+\", #\n f\"{TEST_AWS_ID[0:18]}/\", #\n f\"{TEST_AWS_ID[1:19]}\" #\n ])\n def test_regex_n(self, text: str):\n assert TestRegex.TEST_AWS_REGEX.search(text) is None\n\n @pytest.mark.parametrize( #\n 'text', #\n [ #\n f\"{TEST_AWS_ID}\", #\n f\"#@(-{TEST_AWS_ID})+*&^%$\", # obviously inside delimiters\n f\"N={TEST_AWS_ID}\", #\n f\"\\\"{TEST_AWS_ID}\\\"\", #\n f\"{TEST_AWS_ID}/6/g'\", #\n f\"={TEST_AWS_ID}%2F\", #\n f\"sed 's/{TEST_AWS_ID}/6/g'\", #\n f\"{TEST_AWS_ID}X\", # 21 symbols in ID\n f\"--key {TEST_AWS_ID}X --help\" # 21 symbols in ID\n ])\n def test_regex_p(self, text: str):\n obtained = TestRegex.TEST_AWS_REGEX.search(text)\n assert obtained is not None\n found = False\n for i in obtained.groups():\n pos = i.find(TestRegex.TEST_AWS_ID)\n if -1 != pos and 0 == pos:\n found = True\n break\n assert found\n" }, { "path": "tests/common/test_severity.py", "content": "import unittest\n\nfrom credsweeper.common.constants import Severity\n\n\nclass TestSeverity(unittest.TestCase):\n\n def test_severity_p(self):\n self.assertEqual(Severity.MEDIUM, Severity.get(Severity.MEDIUM))\n self.assertEqual(Severity.INFO, Severity.get(\"inFo\"))\n self.assertEqual(Severity.LOW, Severity.get(\"LoW\"))\n self.assertEqual(Severity.MEDIUM, Severity.get(\"MEDIUM\"))\n self.assertEqual(Severity.HIGH, Severity.get(\" HIGH \"))\n self.assertEqual(Severity.CRITICAL, Severity.get(\"critical\"))\n\n def test_severity_n(self):\n self.assertIsNone(Severity.get(None))\n self.assertIsNone(Severity.get(1))\n self.assertIsNone(Severity.get([1, 2, 3]))\n self.assertIsNone(Severity.get({1, 2, 3}))\n self.assertIsNone(Severity.get(\"None\"))\n self.assertIsNone(Severity.get(\"HI-GH\"))\n self.assertIsNone(Severity.get(\" HI GH \"))\n\n def test_severity_comparison_p(self):\n self.assertTrue(Severity.INFO < Severity.LOW)\n self.assertTrue(Severity.INFO < Severity.MEDIUM)\n self.assertTrue(Severity.INFO < Severity.HIGH)\n self.assertTrue(Severity.INFO < Severity.CRITICAL)\n\n self.assertTrue(Severity.LOW < Severity.MEDIUM)\n self.assertTrue(Severity.LOW < Severity.HIGH)\n self.assertTrue(Severity.LOW < Severity.CRITICAL)\n\n self.assertTrue(Severity.MEDIUM < Severity.HIGH)\n self.assertTrue(Severity.MEDIUM < Severity.CRITICAL)\n\n self.assertTrue(Severity.HIGH < Severity.CRITICAL)\n\n def test_severity_comparison_n(self):\n self.assertFalse(Severity.CRITICAL < Severity.HIGH)\n self.assertFalse(Severity.HIGH < Severity.MEDIUM)\n self.assertFalse(Severity.MEDIUM < Severity.LOW)\n self.assertFalse(Severity.LOW < Severity.INFO)\n\n self.assertFalse(Severity.INFO > Severity.LOW)\n self.assertFalse(Severity.INFO > Severity.MEDIUM)\n self.assertFalse(Severity.INFO > Severity.HIGH)\n self.assertFalse(Severity.INFO > Severity.CRITICAL)\n\n self.assertFalse(Severity.LOW > Severity.MEDIUM)\n self.assertFalse(Severity.LOW > Severity.HIGH)\n self.assertFalse(Severity.LOW > Severity.CRITICAL)\n\n self.assertFalse(Severity.MEDIUM > Severity.HIGH)\n self.assertFalse(Severity.MEDIUM > Severity.CRITICAL)\n\n self.assertFalse(Severity.HIGH > Severity.CRITICAL)\n" }, { "path": "tests/config/__init__.py", "content": "" }, { "path": "tests/config/test_config.py", "content": "from unittest import TestCase\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.utils.util import Util\n\n\nclass ConfigTest(TestCase):\n\n def test_extension_check_p(self):\n file_name = APP_PATH / \"secret\" / \"config.json\"\n self.config = Util.json_load(str(file_name))\n self.assertIsNotNone(self.config)\n self.assertTrue(isinstance(self.config, dict))\n self.assertIn(\"exclude\", self.config.keys())\n self.assertTrue(isinstance(self.config[\"exclude\"], dict))\n self.assertIn(\"containers\", self.config[\"exclude\"].keys())\n self.assertTrue(isinstance(self.config[\"exclude\"][\"containers\"], list))\n self.assertIn(\"extension\", self.config[\"exclude\"].keys())\n self.assertTrue(isinstance(self.config[\"exclude\"][\"extension\"], list))\n container_set = set(self.config[\"exclude\"][\"containers\"])\n extension_set = set(self.config[\"exclude\"][\"extension\"])\n # the sets MUST have no intersection\n self.assertFalse(container_set.intersection(extension_set))\n # all extensions MUST be in lower\n self.assertTrue(all(i.islower() for i in container_set))\n self.assertTrue(all(i.islower() for i in extension_set))\n" }, { "path": "tests/conftest.py", "content": "import datetime\nfrom argparse import Namespace\nfrom typing import Optional\n\nimport pytest\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.common.constants import Severity\nfrom credsweeper.config.config import Config\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scanner import Scanner, RULES_PATH\nfrom credsweeper.utils.util import Util\nfrom tests import SAMPLES_PATH\n\n\n@pytest.fixture\ndef python_file_path() -> str:\n return f\"test_file_{str(datetime.datetime.now())}.py\"\n\n\n@pytest.fixture\ndef file_path() -> str:\n return f\"test_file_{str(datetime.datetime.now())}\"\n\n\n@pytest.fixture\ndef args() -> Namespace:\n file_name = SAMPLES_PATH / \"password.gradle\"\n return Namespace(path=[file_name], json_filename=None)\n\n\n@pytest.fixture\ndef config() -> Config:\n file_name = APP_PATH / \"secret\" / \"config.json\"\n config_dict = Util.json_load(file_name)\n\n config_dict[\"use_filters\"] = True\n config_dict[\"find_by_ext\"] = False\n config_dict[\"exclude\"][\"containers\"] = [\".gz\", \".zip\"]\n config_dict[\"exclude\"][\"documents\"] = [\".docx\", \".pdf\"]\n config_dict[\"exclude\"][\"extension\"] = [\".jpg\", \".bmp\"]\n config_dict[\"pedantic\"] = False\n config_dict[\"depth\"] = 0\n config_dict[\"doc\"] = False\n config_dict[\"find_by_ext_list\"] = [\".txt\", \".inf\"]\n config_dict[\"size_limit\"] = None\n config_dict[\"severity\"] = Severity.INFO\n return Config(config_dict)\n\n\n@pytest.fixture\ndef rule(rule_name: str, config: Config, rule_path: str) -> Optional[Rule]:\n scanner = Scanner(config, rule_path)\n for rule, scanner in scanner.rules_scanners:\n if rule.rule_name == rule_name:\n return rule\n return None\n\n\n@pytest.fixture\ndef rule_path() -> str:\n return str(RULES_PATH)\n\n\n@pytest.fixture\ndef scanner(rule: Rule, config: Config, rule_path: str) -> Scanner:\n scanner = Scanner(config, rule_path)\n scanner.rules_scanners = [(rule, Scanner.get_scanner(rule))]\n return scanner\n\n\n@pytest.fixture\ndef scanner_without_filters(rule: Rule, config: Config, rule_path: str):\n config.use_filters = False\n scanner = Scanner(config, rule_path)\n scanner.rules_scanners = [(rule, Scanner.get_scanner(rule))]\n return scanner\n" }, { "path": "tests/credentials/__init__.py", "content": "" }, { "path": "tests/credentials/test_augment_candidates.py", "content": "import copy\nimport unittest\nfrom unittest.mock import patch\n\nfrom credsweeper.credentials.augment_candidates import augment_candidates\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.line_data import LineData\nfrom tests import AZ_STRING\n\n\nclass TestAugmentCandidates(unittest.TestCase):\n\n def test_augment_candidates_p(self):\n with patch.object(LineData, LineData.initialize.__name__):\n candidate = Candidate.get_dummy_candidate(None, \"file_path\", \"file_type\", \"info\", \"rule_name\")\n candidate.line_data_list[0].value = AZ_STRING\n candidates = [candidate]\n additional_candidates = copy.deepcopy(candidates)\n self.assertTrue(candidate.compare(additional_candidates[0]))\n # the value is different\n additional_candidates[0].line_data_list[0].value = f\"\\\"{AZ_STRING}\\\"\"\n self.assertFalse(candidate.compare(additional_candidates[0]))\n # additional candidates must be added\n augment_candidates(candidates, additional_candidates)\n self.assertEqual(2, len(candidates))\n self.assertEqual(AZ_STRING, candidates[0].line_data_list[0].value)\n self.assertEqual(f\"\\\"{AZ_STRING}\\\"\", candidates[1].line_data_list[0].value)\n\n def test_augment_candidates_n(self):\n with patch.object(LineData, LineData.initialize.__name__):\n candidate = Candidate.get_dummy_candidate(None, \"file_path\", \"file_type\", \"info\", \"rule_name\")\n candidate.line_data_list[0].value = AZ_STRING\n candidates = [candidate]\n\n # empty additional candidates\n augment_candidates(candidates, [])\n self.assertEqual(1, len(candidates))\n\n # the same value\n augment_candidates(candidates, copy.deepcopy(candidates))\n self.assertEqual(1, len(candidates))\n\n self.assertEqual(AZ_STRING, candidates[0].line_data_list[0].value)\n" }, { "path": "tests/credentials/test_credential_manager.py", "content": "import pytest\n\nfrom credsweeper.app import CredSweeper\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\n\nclass TestCredentialManager:\n\n @pytest.mark.parametrize(\n \"line\", [\"apiKeyToken = 'mybstscrt'\", \"SecretToken = 'mybstscrt'\", \"secret = AKIAGIREOGIAWSKEY123\"])\n def test_groups_p(self, line):\n cred_sweeper = CredSweeper()\n provider = StringContentProvider([line])\n detections = cred_sweeper.scanner.scan(provider)\n cred_sweeper.credential_manager.set_credentials(detections)\n groups = cred_sweeper.credential_manager.group_credentials()\n # Assert that credentials can be grouped\n assert len(groups) == 1\n\n @pytest.mark.parametrize(\"line\", [\n \"func(secret='acbd22', token='longscrttok')\", \"single_token='acbd22'\",\n \"{secret: 'acbd22', token: 'longscrttok'}\"\n ])\n def test_groups_n(self, line):\n cred_sweeper = CredSweeper()\n provider = StringContentProvider([line])\n detections = cred_sweeper.scanner.scan(provider)\n cred_sweeper.credential_manager.set_credentials(detections)\n groups = cred_sweeper.credential_manager.group_credentials()\n # Assert that no credentials can be grouped in tested cases\n assert len(groups) == len(detections)\n" }, { "path": "tests/credentials/test_line_data.py", "content": "import re\nimport string\nimport unittest\n\nimport pytest\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH, StartEnd\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.utils.util import Util\nfrom tests import AZ_STRING\n\n\nclass TestLineData:\n\n @pytest.mark.parametrize(\"line\", [\n '\"url\" : \"https://my.site?a=b&{}=ngh679x&c=d\"',\n '\"url\" : \"https://my.site?{}=ngh679x&c=d\"',\n '\"url\" : \"https://my.site?a=b&{}=ngh679x\"',\n ])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"mysecret\", \"Secret\"), (\"password\", \"Password\"),\n (\"aws_token\", \"Token\")])\n def test_url_params_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"\n Test that URL args are parsed correctly with regard to ? and & characters.\n Rerun few times with different variable names to assure that different rules behave in a same way\n \"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.value == \"ngh679x\"\n assert line_data.variable == var_name\n\n @pytest.mark.parametrize(\"line\", ['{} = \"ngh679x\"'])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"mysecret\", \"Secret\"), (\"password\", \"Password\"),\n (\"aws_token\", \"Token\")])\n def test_simple_case_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"Check that most simple case for credentials is parsed correctly\"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.value == \"ngh679x\"\n assert line_data.variable == var_name\n\n @pytest.mark.parametrize(\"line, varname, value, rule_name\",\n [('\"my password\": \"ngh671x\"', \"my password\", \"ngh671x\", \"Password\"),\n ('\"my password\": ‘ngh672x“', \"my password\", \"‘ngh672x“\", \"Password\"),\n ('\"my password\": “““ngh672x”””', \"my password\", \"ngh672x\", \"Password\"),\n ('\"my password\": \"example: “ngh6794”\"', \"my password\", \"example: “ngh6794”\", \"Password\"),\n ('\"my password in JSON\": \"ngh679x\"', \"my password in JSON\", \"ngh679x\", \"Password\")])\n def test_multiple_word_variable_name_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str,\n varname: str, value: str, rule_name: str, config: Config) -> None:\n \"\"\"Check that if variable name contain spaces (like field in JSON) it would be parsed correctly\"\"\"\n line_data = LineData(config, line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.variable == varname\n assert line_data.value == value\n\n @pytest.mark.parametrize(\"line, varname, value, rule_name\", [\n ('\"dummy password\": “““‘‘‘”””', \"dummy password\", '', \"Password\"),\n ])\n def test_multiple_word_variable_name_n(self, file_path: pytest.fixture, rule: pytest.fixture, line: str,\n varname: str, value: str, rule_name: str, config: Config) -> None:\n \"\"\"Check correctness sanitize value - no exception raises\"\"\"\n line_data = LineData(config, line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.variable == varname\n assert line_data.value == value\n\n @pytest.mark.parametrize(\n \"line\", ['{} = my_func(\"ngh679x\")', '{} = my_func(arg1=\"ngh679x\")', '{} = my_func1(my_func2(\"ngh679x\"))'])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"mysecret\", \"Secret\"), (\"password\", \"Password\"),\n (\"aws_token\", \"Token\")])\n def test_function_call_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"Check that secrets in function arguments parsed in a correct way (without argument name)\"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.value == \"ngh679x\"\n assert line_data.variable == var_name\n\n @pytest.mark.parametrize(\"line\", [\n 'something = my_func({}=\"ngh679x\")',\n 'something = my_func(a=b, {}=\"ngh679x\")',\n 'something = my_func(a=b, {}=\"ngh679x\", c=d)',\n ])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"mysecret\", \"Secret\"), (\"password\", \"Password\"),\n (\"aws_token\", \"Token\")])\n def test_function_argument_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"Check that secrets in function arguments parsed in a correct way (with argument name)\"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.value == \"ngh679x\"\n assert line_data.variable == var_name\n\n @pytest.mark.parametrize(\"line\", [\n \"./myprog --{}='ngh679x' --path=/home/me\",\n \"./myprog --{}=ngh679x --path=/home/me\",\n \"./myprog --{}=ngh679x -d library/mysql:5.7.13\",\n \"./myprog --{}=ngh679x >> logfile.log\",\n \"./myprog --{}=ngh679x | tee logfile.log\",\n \"./myprog --{}=ngh679x &> logfile.log\",\n \"./myprog --{}=ngh679x 2> logfile.log\",\n ])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"mysecret\", \"Secret\"), (\"password\", \"Password\"),\n (\"aws_token\", \"Token\")])\n def test_cli_arguments_p(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"Check credentials declared in CLI arguments\"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.value == \"ngh679x\"\n assert line_data.variable == var_name\n\n @pytest.mark.parametrize(\"line\", [\n \"./myprog --{}=' --no-password ' --path=/home/me\",\n ])\n @pytest.mark.parametrize(\"var_name, rule_name\", [(\"password\", \"Password\")])\n def test_cli_arguments_n(self, file_path: pytest.fixture, rule: pytest.fixture, line: str, var_name: str,\n rule_name: str, config: Config) -> None:\n \"\"\"Check clean_bash_parameters negative case \"\"\"\n formatted_line = line.format(var_name)\n line_data = LineData(config, formatted_line, 0, 1, file_path, Util.get_extension(file_path), \"test_info\",\n rule.patterns[0])\n assert line_data.variable == var_name\n\n\nclass TestLineDataStartEnd(unittest.TestCase):\n\n def test_start_end_p(self) -> None:\n \"\"\"Check start-end of found credential\"\"\"\n\n line_data = LineData(None, \"0123456789\", 0, 1, \"\", \"\", \"\", re.compile(r\"(?P[3-7]+)\"))\n self.assertEqual(\"34567\", line_data.value)\n self.assertEqual(3, line_data.value_start)\n self.assertEqual(8, line_data.value_end)\n\n def test_search_start_end_p(self) -> None:\n \"\"\"Check property search start-end\"\"\"\n line = \"_\" * MAX_LINE_LENGTH + \"X\" + \"_\" * MAX_LINE_LENGTH\n pattern = re.compile(r\"(?PX)\")\n line_data = LineData(None, line, 0, 1, \"\", \"\", \"\", pattern, pattern.search(line))\n self.assertEqual(\"X\", line_data.value)\n self.assertEqual(MAX_LINE_LENGTH, line_data.value_start)\n self.assertEqual(1 + MAX_LINE_LENGTH, line_data.value_end)\n\n def test_part_url_sanitize_p(self) -> None:\n line_data = LineData(None,\n \"39084?token=3487263-2384579834-234732875-345&key=DnBeiGdgy6253fytfdDHGg&hasToBeFound=2\",\n 0, 1, \"\", \"\", \"\", re.compile(r\"(?Ptoken)(?P=)(?P.+)\"))\n self.assertEqual(\"token\", line_data.variable)\n self.assertEqual(\"3487263-2384579834-234732875-345\", line_data.value)\n\n def test_hash_text_n(self):\n self.assertEqual(\"\", LineData.get_hash_or_subtext('', hashed=True))\n\n def test_hash_text_p(self):\n # $ echo -n \"The quick brown fox jumps over the lazy dog\" | sha256sum\n self.assertEqual(\"d7a8fbb307d7809469ca9abcb0082e4f8d5651e46d3cdb762d02d0bf37c9e592\",\n LineData.get_hash_or_subtext(AZ_STRING, hashed=True))\n\n def test_sub_text_n(self):\n subtext = LineData.get_hash_or_subtext(None, hashed=False, cut_pos=StartEnd(4, 9))\n self.assertIsNone(subtext)\n\n def test_sub_text_p(self):\n subtext = LineData.get_hash_or_subtext(AZ_STRING, hashed=False, cut_pos=StartEnd(4, 9))\n self.assertEqual(AZ_STRING, subtext)\n text200sym = f\"\\t {''.join(string.digits for _ in range(20))}\"\n subtext = LineData.get_hash_or_subtext(text200sym, hashed=False, cut_pos=StartEnd(4, 9))\n self.assertEqual((''.join(string.digits for _ in range(13)))[:-2], subtext)\n\n def test_toml_parenthesis_sanitize_n(self) -> None:\n line_data = LineData(None, \"secure_cmd token=$(get_token)\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ptoken)(?P=)(?P.+)\"))\n self.assertEqual(\"token\", line_data.variable)\n self.assertEqual(\"$(get_token)\", line_data.value)\n\n self.assertEqual(\n \"ieUW47@\",\n LineData(None, \"$(secure_cmd password=ieUW47@)\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n\n def test_toml_parenthesis_sanitize_p(self) -> None:\n line_data = LineData(None, \"$(secure_cmd token=get_token)\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ptoken)(?P=)(?P.+)\"))\n self.assertEqual(\"token\", line_data.variable)\n self.assertEqual(\"get_token\", line_data.value)\n\n def test_toml_parenthesis_pass_sanitize_p(self) -> None:\n self.assertEqual(\n \"ieUW47@)\",\n LineData(None, \"$(secure_cmd) password=ieUW47@)\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n self.assertEqual(\n \"ieUW47@}\",\n LineData(None, \"password: ieUW47@}\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P:) (?P.+)\")).value)\n\n def test_toml_quoted_sanitize_p(self) -> None:\n self.assertEqual(\n \"ieUW47@}\",\n LineData(\n None, \"${secure_cmd password='ieUW47@}'}\", 0, 1, \"\", \"\", \"\",\n re.compile(\n r\".*(?Ppassword)(?P=)(?P')(?P[^']+)(?P')\"\n )).value)\n\n def test_toml_curly_brackets_sanitize_n(self) -> None:\n self.assertEqual(\n \"ieUW47@}\",\n LineData(None, \"${secure_cmd} password=ieUW47@}\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n\n def test_toml_square_brackets_sanitize_n(self) -> None:\n self.assertEqual(\n \"ieUW47@]\",\n LineData(None, \"$[secure_cmd] password=ieUW47@]\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n\n def test_toml_extra_sanitize_n(self) -> None:\n # dummy variant with wrong order\n self.assertEqual(\n \"\",\n LineData(None, \"[{(extra-cleaned-value password=}}]})]}}])\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n\n def test_tag_sanitize_n(self) -> None:\n # all tags in value\n self.assertEqual(\n \"PASS\",\n LineData(None, \"password=PASS\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n # no opened tag\n self.assertEqual(\n \"PASS\",\n LineData(None, \"password=PASS\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n # example to filter or drop\n self.assertEqual(\n \"\",\n LineData(None, \"password=\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n # a case\n self.assertEqual(\n \"Kdpassword=Kd\", 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n\n def test_tag_sanitize_p(self) -> None:\n # code\n self.assertEqual(\n \"PASS\",\n LineData(None, 'password=PASS', 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n # anchor\n self.assertEqual(\n \"PASS\",\n LineData(None, 'password=PASS', 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n # various\n self.assertEqual(\n \"PASS\",\n LineData(None, 'password=PASS', 0, 1, \"\", \"\", \"\",\n re.compile(r\".*(?Ppassword)(?P=)(?P.+)\")).value)\n" }, { "path": "tests/data/__init__.py", "content": "from typing import Dict, Any, List\n\nfrom tests import SAMPLES_POST_CRED_COUNT, SAMPLES_IN_DEEP_3, SAMPLES_FILTERED_COUNT, SAMPLES_IN_DOC, \\\n ZERO_ML_THRESHOLD, SAMPLES_REGEX_COUNT\n\nDATA_TEST_CFG: List[Dict[str, Any]] = [{\n \"__cred_count\": SAMPLES_IN_DOC,\n \"pool_count\": 1,\n \"thrifty\": False,\n \"sort_output\": True,\n \"subtext\": True,\n \"json_filename\": \"doc.json\",\n \"doc\": True,\n \"ml_threshold\": ZERO_ML_THRESHOLD\n}, {\n \"__cred_count\": SAMPLES_REGEX_COUNT,\n \"pool_count\": 1,\n \"thrifty\": True,\n \"sort_output\": True,\n \"json_filename\": \"no_filters_no_ml.json\",\n \"use_filters\": False,\n \"ml_threshold\": 0\n}, {\n \"__cred_count\": SAMPLES_FILTERED_COUNT,\n \"pool_count\": 1,\n \"thrifty\": True,\n \"sort_output\": True,\n \"json_filename\": \"no_ml.json\",\n \"ml_threshold\": ZERO_ML_THRESHOLD\n}, {\n \"__cred_count\": SAMPLES_POST_CRED_COUNT,\n \"pool_count\": 2,\n \"thrifty\": True,\n \"sort_output\": True,\n \"json_filename\": \"output.json\"\n}, {\n \"__cred_count\": SAMPLES_IN_DEEP_3 + 19,\n \"pool_count\": 2,\n \"thrifty\": True,\n \"sort_output\": True,\n \"json_filename\": \"depth_3_pedantic.json\",\n \"pedantic\": True,\n \"depth\": 3\n}]\n" }, { "path": "tests/data/depth_3_pedantic.json", "content": "[\n {\n \"rule\": \"1Password Account Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ops_eyJb11xLqNoZodWhBSRZjgXFblnyPe_NKm9AQtqj1-g2NkK6QBDIjHwxGYNea8w7cImHWxSXc4ISxk4G9R85CVS1TqBvOOOXycTTH0eqOnwcIGDCQelSMcMIXfHNQVE2pDBHWIsRHmjR-uMUS4SnCU3odPaE9i7BTpHI8mKYEyJzCXzsmLu-mfHfhPM2WffsDLSvlHGwNzVa6wCQio7lsOSrhsjsYkH_boPMB4ZUQ01hn-ix_yBaGvTrMEN6lAy4Z6Pd3KvPb9Pr6c-kI1ifadgIJfRUQJse3IuwLfxeqBUYdHXVgknJ71YECM0-Xg3xwcFjO8oQC1b6kJs2jGX-vdtbLt8MlGzUEn-zYmAam5cj5ye-b_4lVyQjzYrWTI2CP4EkWT7Jsv9KQPVlNye6HwOvUvpm2VHEQDrl-9Kb3XZwo6C53Df0xBfU5Rr6b9p8_r6XrrBGLZWqf2xZkh8pC4OXECo_JzZWNyZXRLZXkiO-jd180LqEfYwfv8_tnxyLXVDX989lmYjZGyJDisytEIwIIcsnnZLCabN-0bOgT_Api9RTXZt7q-9IVxSSm4sgK8ZJ96roIIeukKC_FWVfvZ7uCmGT-TrDc0Kvit44ulvWgt6uoTtMrLGzZYyAx8COjniLSpKk6OOv\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/1password\",\n \"info\": \"FILE:./tests/samples/1password|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ops_eyJb11xLqNoZodWhBSRZjgXFblnyPe_NKm9AQtqj1-g2NkK6QBDIjHwxGYNea8w7cImHWxSXc4ISxk4G9R85CVS1TqBvOOOXycTTH0eqOnwcIGDCQelSMcMIXfHNQVE2pDBHWIsRHmjR-uMUS4SnCU3odPaE9i7BTpHI8mKYEyJzCXzsmLu-mfHfhPM2WffsDLSvlHGwNzVa6wCQio7lsOSrhsjsYkH_boPMB4ZUQ01hn-ix_yBaGvTrMEN6lAy4Z6Pd3KvPb9Pr6c-kI1ifadgIJfRUQJse3IuwLfxeqBUYdHXVgknJ71YECM0-Xg3xwcFjO8oQC1b6kJs2jGX-vdtbLt8MlGzUEn-zYmAam5cj5ye-b_4lVyQjzYrWTI2CP4EkWT7Jsv9KQPVlNye6HwOvUvpm2VHEQDrl-9Kb3XZwo6C53Df0xBfU5Rr6b9p8_r6XrrBGLZWqf2xZkh8pC4OXECo_JzZWNyZXRLZXkiO-jd180LqEfYwfv8_tnxyLXVDX989lmYjZGyJDisytEIwIIcsnnZLCabN-0bOgT_Api9RTXZt7q-9IVxSSm4sgK8ZJ96roIIeukKC_FWVfvZ7uCmGT-TrDc0Kvit44ulvWgt6uoTtMrLGzZYyAx8COjniLSpKk6OOv\",\n \"value_start\": 0,\n \"value_end\": 656,\n \"entropy\": 5.94326\n }\n ]\n },\n {\n \"rule\": \"BASE64 encoded PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": 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\"value_start\": 0,\n \"value_end\": 3078,\n \"entropy\": 5.49785\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" -----BEGIN EC PRIVATE KEY-----\",\n \"line_num\": 22,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|BASE64|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN EC PRIVATE KEY-----\",\n \"value_start\": 8,\n \"value_end\": 38,\n \"entropy\": 3.30775\n },\n {\n \"line\": \" MHcCAQEEIAAe8nfbzZu9c/OB2gdfkjglidfkjbnxjkhbghbfghbjhbdjhbsjxck9\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|BASE64|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"MHcCAQEEIAAe8nfbzZu9c/OB2gdfkjglidfkjbnxjkhbghbfghbjhbdjhbsjxck9\",\n \"value_start\": 8,\n \"value_end\": 72,\n \"entropy\": 4.54632\n },\n {\n \"line\": \" odifjvijdfvoijdfoivjdfoijdjgnfdkjgnkjdfgkjdfkjgbkjjhbkgJjXgZtM72\",\n \"line_num\": 24,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|BASE64|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"odifjvijdfvoijdfoivjdfoijdjgnfdkjgnkjdfgkjdfkjgbkjjhbkgJjXgZtM72\",\n \"value_start\": 8,\n \"value_end\": 72,\n \"entropy\": 3.63842\n },\n {\n \"line\": \" dfiohguxhbkjgnkljdfnkljdngkjnkgjn+==\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|BASE64|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dfiohguxhbkjgnkljdfnkljdngkjnkgjn+==\",\n \"value_start\": 8,\n \"value_end\": 44,\n \"entropy\": 3.62593\n },\n {\n \"line\": \" -----END EC PRIVATE KEY-----\",\n \"line_num\": 26,\n \"path\": \"./tests/samples/LS0t_p\",\n \"info\": \"FILE:./tests/samples/LS0t_p|BASE64|RAW\",\n \"variable\": 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\"moderate\",\n \"ml_probability\": 0.941,\n \"line_data_list\": [\n {\n \"line\": \"id:master@example.com,pw:IHQSB1GG!\",\n \"line_num\": 102,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 22,\n \"variable_end\": 24,\n \"value\": \"IHQSB1GG!\",\n \"value_start\": 25,\n \"value_end\": 34,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.882,\n \"line_data_list\": [\n {\n \"line\": \"98.76.54.32(ID:master/PW:iPp10@GRq) # todo: move into other sample ?\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"PW\",\n \"variable_start\": 22,\n \"variable_end\": 24,\n \"value\": \"iPp10@GRq\",\n \"value_start\": 25,\n \"value_end\": 34,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n 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\"value_start\": 9,\n \"value_end\": 71,\n \"entropy\": 4.71236\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"pkey = 'LS0tLS1CRUdJTiBQUklWQVRFIENDcUdTTTQ5QXdFSEJHMHdhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJBTkNBQVNnRlRLandKQUFVOTVnKysvdnpLV0hrekFWbU5NSQp0QjV2VGpaT09Jd25FYjcwTXNXWkZJeVVGRDFQOUd3c3R6NCtha0hYN3ZJOEJINmhIbUJtZmVRbAotLS0tLUVORCBQUklWJNR0J5cUdTTTQ5QW5aUHhmQXl4cUUKWlYwNdFR0QVRFIEtFWS0tLS0tCgtFWS0tLS0tCk1JR0hBZ0VBTU=='\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|STRUCT|STRING:0|RAW\",\n \"variable\": \"pkey\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": 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4.96282\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"PKEY = \\\"\\\"\\\"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 10,\n \"value_end\": 45,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.18903\n },\n {\n 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\"value_start\": 0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.994,\n \"line_data_list\": [\n {\n \"line\": \"api_key = 'QMEFk2TZGlkGcOkG-R9UwV1ZmlNkWEYvQzF'\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/key_value.json\",\n \"info\": \"FILE:./tests/samples/key_value.json|STRUCT|KEYWORD\",\n \"variable\": \"api_key\",\n \"variable_start\": 0,\n \"variable_end\": 7,\n \"value\": \"QMEFk2TZGlkGcOkG-R9UwV1ZmlNkWEYvQzF\",\n \"value_start\": 11,\n \"value_end\": 46,\n \"entropy\": 4.47914\n }\n ]\n },\n {\n \"rule\": \"API\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.994,\n \"line_data_list\": [\n {\n \"line\": \"api_key = 'QMEFk2TZGlkGcOkG-R9UwV1ZmlNkWEYvQzF'\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/key_value.json\",\n \"info\": \"FILE:./tests/samples/key_value.json|STRUCT|KEYWORD\",\n \"variable\": \"api_key\",\n \"variable_start\": 0,\n \"variable_end\": 7,\n \"value\": \"QMEFk2TZGlkGcOkG-R9UwV1ZmlNkWEYvQzF\",\n \"value_start\": 11,\n \"value_end\": 46,\n \"entropy\": 4.47914\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"FILE:./tests/samples/llama|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.03958\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"line_num\": 2,\n \"path\": 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[\n {\n \"line\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"FILE:./tests/samples/mailgun|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.91661\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"FILE:./tests/samples/mailgun|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 3.85669\n }\n ]\n },\n {\n \"rule\": \"Google API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AIzaGiReoGiCrackleCrackle12315618112315\\u0000\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|PATCH:google_api_key_with_null_terminator:added|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AIzaGiReoGiCrackleCrackle12315618112315\",\n \"value_start\": 0,\n \"value_end\": 39,\n \"entropy\": 4.13105\n }\n ]\n },\n {\n \"rule\": \"Google API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AIzaGiReoGiCrackleCrackle12315618112315\\u0000\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|PATCH:google_api_key_with_null_terminator:deleted|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AIzaGiReoGiCrackleCrackle12315618112315\",\n \"value_start\": 0,\n \"value_end\": 39,\n \"entropy\": 4.13105\n }\n ]\n },\n {\n \"rule\": \"Dynatrace API Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMODIDAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|PATCH:dynatrace_api.zip:added|ZIP:dynatrace_api|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMODIDAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"value_start\": 0,\n \"value_end\": 96,\n \"entropy\": 4.92454\n }\n ]\n },\n {\n \"rule\": \"Dynatrace API Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMODIDAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|PATCH:dynatrace_api.zip:deleted|ZIP:dynatrace_api|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMODIDAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"value_start\": 0,\n \"value_end\": 96,\n \"entropy\": 4.92454\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"FILE:./tests/samples/multiline.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"FILE:./tests/samples/multiline.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"FILE:./tests/samples/multiline.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"FILE:./tests/samples/multiline.patch|RAW\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Netlify Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/netlify\",\n \"info\": \"FILE:./tests/samples/netlify|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"value_start\": 0,\n \"value_end\": 40,\n \"entropy\": 4.61531\n }\n ]\n },\n {\n \"rule\": \"NKEY Seed\",\n \"severity\": \"high\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"// SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/nkey_seed\",\n \"info\": \"FILE:./tests/samples/nkey_seed|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"value_start\": 3,\n \"value_end\": 61,\n \"entropy\": 4.55826\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_multi = 'KJHfdjs8767gr54534wsFHGf5hJKhK\\\\nU7yguyuyFHGf5=='\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|STRUCT|STRING:3|RAW\",\n \"variable\": \"key_multi\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"KJHfdjs8767gr54534wsFHGf5hJKhK\\\\nU7yguyuyFHGf5==\",\n \"value_start\": 13,\n \"value_end\": 60,\n \"entropy\": 4.49556\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_wrap = 'KJHhJKhKU7yguyuyfrtsdESffhjgkhYTfdjs8Gf5jlli=='\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|STRUCT|STRING:2|RAW\",\n \"variable\": \"key_wrap\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"KJHhJKhKU7yguyuyfrtsdESffhjgkhYTfdjs8Gf5jlli==\",\n \"value_start\": 12,\n \"value_end\": 58,\n \"entropy\": 4.48282\n }\n ]\n },\n {\n \"rule\": \"Nonce\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"nonce = 'bsfcvir57nt40rydvtbhs8lzbgljmet5'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|RAW\",\n \"variable\": \"nonce\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"bsfcvir57nt40rydvtbhs8lzbgljmet5\",\n \"value_start\": 9,\n \"value_end\": 41,\n \"entropy\": 4.39032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password: F1lT3ReDw17hQoT3s\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"F1lT3ReDw17hQoT3s\",\n \"value_start\": 10,\n \"value_end\": 27,\n \"entropy\": 3.73452\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_wrap = 'KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\\\\\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|RAW\",\n \"variable\": \"key_wrap\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\",\n \"value_start\": 12,\n \"value_end\": 44,\n \"entropy\": 4.11673\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_multi = '''KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"FILE:./tests/samples/nonce.py|RAW\",\n \"variable\": \"key_multi\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"value_start\": 15,\n \"value_end\": 45,\n \"entropy\": 4.12323\n }\n ]\n },\n {\n \"rule\": \"Notion Integration Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/notion\",\n \"info\": \"FILE:./tests/samples/notion|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 5.06876\n }\n ]\n },\n {\n \"rule\": \"NPM Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"positive: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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/npm\",\n \"info\": \"FILE:./tests/samples/npm|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 9,\n \"value_end\": 49,\n \"entropy\": 4.80306\n }\n ]\n },\n {\n \"rule\": \"NTLM Token\",\n \"severity\": \"medium\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"Positive: TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/ntlm\",\n \"info\": \"FILE:./tests/samples/ntlm|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=\",\n \"value_start\": 10,\n \"value_end\": 190,\n \"entropy\": 3.79713\n }\n ]\n },\n {\n \"rule\": \"NuGet API key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"k = 'oy2mlf2v7jl2firuegfqwzc4zxyebz3ethzd14g4hw4iam'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nuget_api_key\",\n \"info\": \"FILE:./tests/samples/nuget_api_key|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"oy2mlf2v7jl2firuegfqwzc4zxyebz3ethzd14g4hw4iam\",\n \"value_start\": 5,\n \"value_end\": 51,\n \"entropy\": 4.56129\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"FILE:./tests/samples/open_ai_token|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 51,\n \"entropy\": 5.22625\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"FILE:./tests/samples/open_ai_token|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 5.25816\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"FILE:./tests/samples/open_ai_token|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 4.12555\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"WXFES7QNTET5DQYC\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"FILE:./tests/samples/otp_2fa|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"WXFES7QNTET5DQYC\",\n \"value_start\": 0,\n \"value_end\": 16,\n \"entropy\": 3.625\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"FILE:./tests/samples/otp_2fa|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.14032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.99,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"FILE:./tests/samples/passwd.groovy|RAW\",\n \"variable\": \"gi_reo_gi_passwd\",\n \"variable_start\": 0,\n \"variable_end\": 16,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 20,\n \"value_end\": 30,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"FILE:./tests/samples/passwd.groovy|RAW\",\n \"variable\": \"password_confirmation\",\n \"variable_start\": 33,\n \"variable_end\": 54,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 58,\n \"value_end\": 68,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"cackle!\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.gradle\",\n \"info\": \"FILE:./tests/samples/password.gradle|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password.patch\",\n \"info\": \"FILE:./tests/samples/password.patch|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"MYPSWRD!@#$%^&*\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.tfvars\",\n \"info\": \"FILE:./tests/samples/password.tfvars|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"MYPSWRD!@#$%^&*\",\n \"value_start\": 12,\n \"value_end\": 27,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.996,\n \"line_data_list\": [\n {\n \"line\": \"MYSQLPASS: Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"MYSQLPASS\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"value_start\": 11,\n \"value_end\": 37,\n \"entropy\": 3.8693\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"my_pw: nCzx8A8#!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"my_pw\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 7,\n \"value_end\": 16,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"val password: String = \\\"exord13Paw64\\\", // scala\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"exord13Paw64\",\n \"value_start\": 24,\n \"value_end\": 36,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"def connect(passwd: str = \\\"cq2tPr1a2\\\"): # python default arg\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"passwd\",\n \"variable_start\": 12,\n \"variable_end\": 18,\n \"value\": \"cq2tPr1a2\",\n \"value_start\": 27,\n \"value_end\": 36,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd == \\\"q4c1a2oPd\\\": # __eq__ separator\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"q4c1a2oPd\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd != \\\"x6s7djtEa\\\": # __ne__ separator\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"x6s7djtEa\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password=2bkJgtJDiLcq1t\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"2bkJgtJDiLcq1t\",\n \"value_start\": 9,\n \"value_end\": 23,\n \"entropy\": 3.52164\n }\n ]\n },\n {\n \"rule\": \"CMD Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"passin\",\n \"variable_start\": 33,\n \"variable_end\": 39,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"pass\",\n \"variable_start\": 41,\n \"variable_end\": 45,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"MYSQL_DATABASE_USER=CRED;MYSQL_DATABASE_PASSWORD=2IWJD88FH4Y;\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"FILE:./tests/samples/password_TRUE|RAW\",\n \"variable\": \"MYSQL_DATABASE_PASSWORD\",\n 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GqXBumHAZco0bRhfhZjmeZ64SmmAM0NpM3j8hwhTyWHRXpW21gv8cumYJqb/ilf7\\\\r\\\\n#5 0.228 62oRDQIDAQABAkBYiY64SZQzBGUQQnt0hmgvOsI7BHUm31G2OtWyL7T/90UhnksH\\\\r\\\\n#5 0.228 w2YF31p/TJULL44SV3HpxiY+T1vOPl138ulhAiEA9LcC28UMotvF0z/CVofas5Fh\\\\r\\\\n#5 0.228 eKZSGLykNZ7FkKd0t+cCIQDFVgG6lreao/UzHcVk75fZG3lG3k0xvqdsZTIMAOjA\\\\r\\\\n#5 0.228 6wIgV033ehqJ0IxhvmUP2zkqoEeso5OK1IJwfyS+zUXA0V8CIQCvKySHvAgpRkd/\\\\r\\\\n#5 0.228 Y3r4mVICj8e859JASQwXRVECpL/3lwIhANcg6iGD9S4zdbvVxYjJogRVbi7U6YUU\\\\r\\\\n#5 0.228 ivYSmyJQhq+V\\\\r\\\\n#5 0.228 -----END PRIVATE KEY-----\",\n \"value_start\": 82,\n \"value_end\": 711,\n \"entropy\": 5.91095\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"-----BEGIN PRIVATE KEY-----\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.ec\",\n \"info\": \"FILE:./tests/samples/pem_key.p.ec|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\",\n \"value_start\": 0,\n \"value_end\": 27,\n \"entropy\": 3.20029\n },\n {\n \"line\": \"MIGHAgEAMBMGByqGSM49AgEGCCqGSM49AwEHBG0wawIBAQQgyK82YrlPyJb7FLsk\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/pem_key.p.ec\",\n \"info\": \"FILE:./tests/samples/pem_key.p.ec|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"MIGHAgEAMBMGByqGSM49AgEGCCqGSM49AwEHBG0wawIBAQQgyK82YrlPyJb7FLsk\",\n \"value_start\": 0,\n \"value_end\": 64,\n \"entropy\": 4.72268\n },\n {\n \"line\": \"1hg6SN+UI2R/QIVPPomtVY0yeH6hRANCAAStXqONgR32XCE3nfIkmYjk28Kn0wsK\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/pem_key.p.ec\",\n \"info\": \"FILE:./tests/samples/pem_key.p.ec|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"1hg6SN+UI2R/QIVPPomtVY0yeH6hRANCAAStXqONgR32XCE3nfIkmYjk28Kn0wsK\",\n \"value_start\": 0,\n \"value_end\": 64,\n \"entropy\": 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openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 gx1/q1EgS5w2ciAuC8u5gitd1ie43B5lsysO0MY31Qy1eGO1Sj0g4pxM2szbpwso\\\\r\\\\n2026-04-26 12:36:01 0RZL8aKk645hElitcXDx8wUVc0Zm/Av4FsSiZkhFeKaHSAXJtTtlAkLMMTZaNwBA\\\\r\\\\n2026-04-26 12:36:01 hqmHqqtalptZmwGz2F0dmXF9cy+gOxzaBhQbVcH8SDdchpgTl14B93qh2iY2RjxY\\\\r\\\\n2026-04-26 12:36:01 Eb3kpsPG0cdLTAAahEALuMu26YFpglJXAkwSwSLPYsGRPHjJFiXfWBR05x5y5wdB\\\\r\\\\n2026-04-26 12:36:01 1jhhqlV6ZHO/osEJKb6tSHH0mYf0uMNu2speu2DgsjCjHHJwtSJMayfO1WZcSF+G\\\\r\\\\n2026-04-26 12:36:01 wFXOY77MgB3VwMRcCoTMNwoBswcJeZRyNL+cHLZZcK0kpEJbBY60W5pHUceKrDDJ\\\\r\\\\n2026-04-26 12:36:01 sr63qzPaUVNj0Vu2zFG8sEEMES55/JIKCoj6O66j821/qJ97RLPP5pKUpp2gCS7F\\\\r\\\\n2026-04-26 12:36:01 GyCzMBiTsF4zNCr+FA1rQUCZqa50S3Gu90KANsv7VX1krJXXaSXQFaiDAyB+zL0f\\\\r\\\\n2026-04-26 12:36:01 SQR7WrimYwMQaGX8c75+8L7NK2zdxMQH0chtdqv79WmoOn+fWGupCq7NlA32s7rb\\\\r\\\\n2026-04-26 12:36:01 Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 Kqmr2XMicIWCxQoiW4YT5UYfNsfwmRUWkJwmCahUFSzo5swUpBbeCo6bsEdkyxMM\\\\r\\\\n2026-04-26 12:36:01 I5bNV1cjSII5liHOyxnvZ77+giZAKglsiI3ZmmVh+l8fvDBDaLVmmMRfcwRHOxu1\\\\r\\\\n2026-04-26 12:36:01 UMRr047T8ggKgEnyhQLK/FJh+Yp8ubo6wsTUwyyVcRULUVWeJbka6EDkMbPucHHb\\\\r\\\\n2026-04-26 12:36:01 vDdO61eP2yB+uQlwbBr1UquiQD1XrBHXFVwDw6rJoJxTkGQggaofpsUPa3F561LV\\\\r\\\\n2026-04-26 12:36:01 aQAFxU9BAgmdYb4uJxtlt46DCbx2tFW2OnoqQrpFW7nWlwmLJ2dUhIRkySTyhJpq\\\\r\\\\n2026-04-26 12:36:01 K0hnrLThhA1tu8q3dTXOCDs+8csKnI9vVSqAFm6ax3lI6ilBFVIgyZi7dBI1TCKp\\\\r\\\\n2026-04-26 12:36:01 rDbvCzcWY6dxEUzHqTELG5sd955LQgoei2/86QDquRIgB2PGqblBYylUOA9tBTAv\\\\r\\\\n2026-04-26 12:36:01 wSVKoZuonI4ijDZz5yec2C9DiCZva6MbxASOLBl05qfeeDbzkhOWsas2ZpMRmaS8\\\\r\\\\n2026-04-26 12:36:01 dI0Tmp732GkddM2R879ULHp0x4CI4Vh42mN/m22OInwW4mlPaUAy4MQUOWvuWb6/\\\\r\\\\n2026-04-26 12:36:01 o2/HcXJCoj9JsULCKXchFrawJHTgCTpi9BicMpmnPHpnpxlYRw77p4qWcmGqs2Yi\\\\r\\\\n2026-04-26 12:36:01 gQLAAQhZxzpT8MPgsomgC2nySQthEHsvF4XVbL60ImBv9Qig2hd7Jh4cI0D/+TdC\\\\r\\\\n2026-04-26 12:36:01 tky6B1MyPAxYCTN2QXXCo6CbdzMoVBhXuAI7prv2DA5zUwNCpxBKs2BgSIZ9677J\\\\r\\\\n2026-04-26 12:36:01 RlxpsqbbVLVJl6BdbJcMRjIWEW0flKwbSb/PdEuEGheu5UuRZ4/MxrzrciW35CxX\\\\r\\\\n2026-04-26 12:36:01 +XYlHBLCOQ6MCCSYtAy9olSBxQ1iMkiP0V20Crzm6JapZWxTC1EEFgMXAJERMXin\\\\r\\\\n2026-04-26 12:36:01 NiY0wK8f8JFABRBxMZeHyBtT6EobR2Q1Ozcjmhb98rK6wUVhorCGV0mbZ4jzVFtH\\\\r\\\\n2026-04-26 12:36:01 YD9UoTAQrI22NGLy+BupkM7OmaQ82SWZlZ8eiSqv5z7aBI8AAWOORHCYW07i9kCy\\\\r\\\\n2026-04-26 12:36:01 OJ4nB3/Ko4OTiUeGYamtlj9/k7alhM5BE2fkEoygYFvL1cfFXMHH+wOEonSMi5qo\\\\r\\\\n2026-04-26 12:36:01 smQrWalr8aPEPGkXWYDjMsBZ4rHQ00z+cE3YiXJXMj2Y8JMY9LJrR1asaEY3IoBx\\\\r\\\\n2026-04-26 12:36:01 ose+UxmIsZr1OD/Jy1euBJo0IQX3gnrvdGl9u8zQeCes+g5xl68gAU8n1J/Z4DoB\\\\r\\\\n2026-04-26 12:36:01 Y0mUMEgOuMu6aAvmQc/lqqP7lwrCKCfVe6SS6w2w3I9GrL2/3GkQkXJSc4rmZb7u\\\\r\\\\n2026-04-26 12:36:01 JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"FILE:./tests/samples/pem_key.p.log.json|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 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2.58496\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"ANYid:master pw:dipPr194Gg! ip:98.76.54.32\",\n \"line_num\": 95,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 13,\n \"variable_end\": 15,\n \"value\": \"dipPr194Gg!\",\n \"value_start\": 16,\n \"value_end\": 27,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.188,\n \"line_data_list\": [\n {\n \"line\": \"\\uacc4\\uc815:master \\uc554\\ud638:dipPr195Gg!\",\n \"line_num\": 96,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"\\uc554\\ud638\",\n \"variable_start\": 10,\n 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\"pw\",\n \"variable_start\": 11,\n \"variable_end\": 13,\n \"value\": \"dipPr197Gg!\",\n \"value_start\": 14,\n \"value_end\": 25,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"ID_PAIR_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"id: master pw:dipPr197Gg!\",\n \"line_num\": 98,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 11,\n \"variable_end\": 13,\n \"value\": \"dipPr197Gg!\",\n \"value_start\": 14,\n \"value_end\": 25,\n \"entropy\": 3.45943\n },\n {\n \"line\": \"id: master pw:dipPr197Gg!\",\n \"line_num\": 98,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"id\",\n \"variable_start\": 0,\n \"variable_end\": 2,\n \"value\": \"master\",\n \"value_start\": 4,\n 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24,\n \"value\": \"dipPr198Gg!\",\n \"value_start\": 25,\n \"value_end\": 36,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"ID_PAIR_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.804,\n \"line_data_list\": [\n {\n \"line\": \"id:master@example.com,pw:dipPr198Gg!\",\n \"line_num\": 99,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 22,\n \"variable_end\": 24,\n \"value\": \"dipPr198Gg!\",\n \"value_start\": 25,\n \"value_end\": 36,\n \"entropy\": 3.45943\n },\n {\n \"line\": \"id:master@example.com,pw:dipPr198Gg!\",\n \"line_num\": 99,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_pair_passwd_pair|RAW\",\n \"variable\": \"id\",\n \"variable_start\": 0,\n \"variable_end\": 2,\n \"value\": \"master@example.com,pw:dipPr198Gg!\",\n \"value_start\": 3,\n 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\"variable_end\": 24,\n \"value\": \"IHQSB1GG!\",\n \"value_start\": 25,\n \"value_end\": 34,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.868,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW:master/iPp0@GRq\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"ID/PW\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"iPp0@GRq\",\n \"value_start\": 13,\n \"value_end\": 21,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.005,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW:master/iPp0@GRq\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master/iPp0@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.679,\n \"line_data_list\": [\n {\n \"line\": \"ANYID(PW):master(iPp1@GRq)\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"ANYID(PW\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"iPp1@GRq\",\n \"value_start\": 17,\n \"value_end\": 25,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.989,\n \"line_data_list\": [\n {\n \"line\": \"ID/Password:master/iPp2@GRq\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"ID/Password\",\n \"variable_start\": 0,\n \"variable_end\": 11,\n \"value\": \"iPp2@GRq\",\n \"value_start\": 19,\n \"value_end\": 27,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.104,\n \"line_data_list\": [\n {\n \"line\": \"ID/Password:master/iPp2@GRq\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"Password\",\n \"variable_start\": 3,\n \"variable_end\": 11,\n \"value\": \"master/iPp2@GRq\",\n \"value_start\": 12,\n \"value_end\": 27,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.02,\n \"line_data_list\": [\n {\n \"line\": \"ID/Pass:master/iPp3@GRq\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": 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\"value\": \"master:iPp4@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.982,\n \"line_data_list\": [\n {\n \"line\": \"ID:PW=master:iPp4@GRq\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"ID:PW\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"iPp4@GRq\",\n \"value_start\": 13,\n \"value_end\": 21,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.027,\n \"line_data_list\": [\n {\n \"line\": \"ID:PW=master:iPp4@GRq\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master:iPp4@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.952,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW=master/iPp5@GRq\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"ID/PW\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"iPp5@GRq\",\n \"value_start\": 13,\n \"value_end\": 21,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.008,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW=master/iPp5@GRq\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master/iPp5@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.967,\n \"line_data_list\": [\n {\n \"line\": \"id/pw master/iPp6@GRq\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"id/pw\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"iPp6@GRq\",\n \"value_start\": 13,\n \"value_end\": 21,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.985,\n \"line_data_list\": [\n {\n \"line\": \"username/password:master/iPp7@GRq\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"username/password\",\n \"variable_start\": 0,\n \"variable_end\": 17,\n \"value\": \"iPp7@GRq\",\n \"value_start\": 25,\n \"value_end\": 33,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.212,\n \"line_data_list\": [\n {\n \"line\": \"username/password:master/iPp7@GRq\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"FILE:./tests/samples/doc_id_passwd_pair|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 9,\n \"variable_end\": 17,\n \"value\": \"master/iPp7@GRq\",\n \"value_start\": 18,\n \"value_end\": 33,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"ID_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.956,\n \"line_data_list\": [\n {\n \"line\": \"id/passwd:master/iPp8@GRq\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": 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\"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:gildong.hong@xxx.com mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 102,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 35,\n \"variable_end\": 43,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n },\n {\n \"line\": \"id:gildong.hong@xxx.com mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 102,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"id\",\n \"variable_start\": 0,\n \"variable_end\": 2,\n \"value\": \"gildong.hong@xxx.com\",\n \"value_start\": 3,\n \"value_end\": 23,\n \"entropy\": 3.40869\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:gildong.hong@xxx.com mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 102,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 35,\n \"variable_end\": 43,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"ssh gildong.hong@98.76.54.32 mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 104,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 40,\n \"variable_end\": 48,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 49,\n \"value_end\": 57,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"ssh gildong.hong@98.76.54.32 mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 104,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 40,\n \"variable_end\": 48,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 49,\n \"value_end\": 57,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.98,\n \"line_data_list\": [\n {\n \"line\": \"-ANYID:gildong.hong@example.com mailto:{1} -pw:IhqSb1Gg\",\n \"line_num\": 105,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 44,\n \"variable_end\": 46,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 47,\n \"value_end\": 55,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"ID_PAIR_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.98,\n \"line_data_list\": [\n {\n \"line\": \"-ANYID:gildong.hong@example.com mailto:{1} -pw:IhqSb1Gg\",\n \"line_num\": 105,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 44,\n \"variable_end\": 46,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 47,\n \"value_end\": 55,\n \"entropy\": 3.0\n },\n {\n \"line\": \"-ANYID:gildong.hong@example.com mailto:{1} -pw:IhqSb1Gg\",\n \"line_num\": 105,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"ID\",\n \"variable_start\": 4,\n \"variable_end\": 6,\n \"value\": \"gildong.hong@example.com\",\n \"value_start\": 7,\n \"value_end\": 31,\n \"entropy\": 3.77206\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.98,\n \"line_data_list\": [\n {\n \"line\": \"-ANYID:gildong.hong@example.com mailto:{1} -pw:IhqSb1Gg\",\n \"line_num\": 105,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 44,\n \"variable_end\": 46,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 47,\n \"value_end\": 55,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"ID:gildong.hong@xxxx.net mailto:{1} pw:IhqSb1Gg\",\n \"line_num\": 106,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 36,\n \"variable_end\": 38,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 39,\n \"value_end\": 47,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"ID:gildong.hong@xxxx.net mailto:{1} pw:IhqSb1Gg\",\n \"line_num\": 106,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 36,\n \"variable_end\": 38,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 39,\n \"value_end\": 47,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.989,\n \"line_data_list\": [\n {\n \"line\": \"http://98.76.54.32:xxx(pw:IhqSb1Gg)\",\n \"line_num\": 108,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 23,\n \"variable_end\": 25,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 26,\n \"value_end\": 34,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.989,\n \"line_data_list\": [\n {\n \"line\": \"http://98.76.54.32:xxx(pw:IhqSb1Gg)\",\n \"line_num\": 108,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"FILE:./tests/samples/doc_various|RAW\",\n \"variable\": \"pw\",\n \"variable_start\": 23,\n \"variable_end\": 25,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 26,\n \"value_end\": 34,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: dckr_pat_mcF-hLK_JoBxXUNJy1kU7-WSbk0\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"FILE:./tests/samples/docker|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_pat_mcF-hLK_JoBxXUNJy1kU7-WSbk0\",\n \"value_start\": 10,\n \"value_end\": 46,\n \"entropy\": 4.68354\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"NEGATIVE: dckr_pat_EXAMPLE-EXAMPLE-EXAMPLE-123\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"FILE:./tests/samples/docker|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_pat_EXAMPLE-EXAMPLE-EXAMPLE-123\",\n \"value_start\": 10,\n \"value_end\": 46,\n \"entropy\": 3.89106\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: dckr_oat_fXUgJy1nU2WSbk_0vH2S-mcF-hLKJoB-\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"FILE:./tests/samples/docker|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_oat_fXUgJy1nU2WSbk_0vH2S-mcF-hLKJoB-\",\n \"value_start\": 10,\n \"value_end\": 51,\n \"entropy\": 4.78414\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: SWMTKN-1-edmua5ub12inlget8wkvz35kckxkeyznuvc49brsy84wgfssrw-otjll8wdy3yikfrksskvqzqh1\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"FILE:./tests/samples/docker|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMTKN-1-edmua5ub12inlget8wkvz35kckxkeyznuvc49brsy84wgfssrw-otjll8wdy3yikfrksskvqzqh1\",\n \"value_start\": 10,\n \"value_end\": 95,\n \"entropy\": 5.06757\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: SWMKEY-1-fySn8TY4w5lKcWcJPIpKufejh9hxx5KYwx6XZigx3Q4\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"FILE:./tests/samples/docker|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMKEY-1-fySn8TY4w5lKcWcJPIpKufejh9hxx5KYwx6XZigx3Q4\",\n \"value_start\": 10,\n \"value_end\": 62,\n \"entropy\": 4.95515\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"password is NsIdksKJdj\\ttoken is bace4d19-fa7e-b2e4-1afe-9129474bcd81\\tPassword: \\\"Dw7^&ndgf\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": \"textpassword\",\n \"variable_start\": 0,\n \"variable_end\": 12,\n \"value\": \"Df34D<345&>gf\",\n \"value_start\": 14,\n \"value_end\": 27,\n \"entropy\": 3.08506\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.038,\n \"line_data_list\": [\n {\n \"line\": \"mypass is Mkd<.dI34s&3\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": \"mypass\",\n \"variable_start\": 0,\n \"variable_end\": 6,\n \"value\": \"Mkd<.dI34s&3\",\n \"value_start\": 10,\n \"value_end\": 22,\n \"entropy\": 3.25163\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.035,\n \"line_data_list\": [\n {\n \"line\": \"Heading\\tLorem ipsum dolor sit amet, secret is \\\"Nner,4<563^%$&5w\",\n \"line_num\": 31,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": \"secret\",\n \"variable_start\": 0,\n \"variable_end\": 6,\n \"value\": \">4<563^%$&5w\",\n \"value_start\": 8,\n \"value_end\": 20,\n \"entropy\": 3.4183\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"pass: Dsfgh%$d<>s&\",\n \"line_num\": 34,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": \"pass\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": \"Dsfgh%$d<>s&\",\n \"value_start\": 6,\n \"value_end\": 18,\n \"entropy\": 3.4183\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"page2 secret is ce49dba1-e4fe-b2a7-4ffa-132bcd819474\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ce49dba1-e4fe-b2a7-4ffa-132bcd819474\",\n \"value_start\": 16,\n \"value_end\": 52,\n \"entropy\": 3.68703\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"page2 secret is ce49dba1-e4fe-b2a7-4ffa-132bcd819474\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"FILE:./tests/samples/drawio|MXFILE\",\n \"variable\": \"secret\",\n \"variable_start\": 6,\n \"variable_end\": 12,\n \"value\": \"ce49dba1-e4fe-b2a7-4ffa-132bcd819474\",\n \"value_start\": 16,\n \"value_end\": 52,\n \"entropy\": 3.68703\n }\n ]\n },\n {\n \"rule\": \"Dropbox API secret (long term)\",\n \"severity\": \"high\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var g = '7rBynGo0b1cAAAAAAAAAAc72L3T6rQK51mB5a06ijnwRG91deTxvSqdZNAlxq8pZ'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_api_secret_long_term\",\n \"info\": \"FILE:./tests/samples/dropbox_api_secret_long_term|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"7rBynGo0b1cAAAAAAAAAAc72L3T6rQK51mB5a06ijnwRG91deTxvSqdZNAlxq8pZ\",\n \"value_start\": 9,\n \"value_end\": 73,\n \"entropy\": 4.89362\n }\n ]\n },\n {\n \"rule\": \"Dropbox App secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var app_unique_val_s = 'wpv1jq9xwanbn3n';\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_app_secret\",\n \"info\": \"FILE:./tests/samples/dropbox_app_secret|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wpv1jq9xwanbn3n\",\n \"value_start\": 24,\n \"value_end\": 39,\n \"entropy\": 3.45656\n }\n ]\n },\n {\n \"rule\": \"Dropbox OAuth2 API Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sl.BdmpmC82mhhySscKk2oQGyE5l--8LdAQftLTXVGQhP39Z8FtAK1BhePhyevurA-Elt7ToIr6OpwzKAYE7RBqpu6VVyQU5WlCTL_Q7N4gElXahaWou6aPpOIwgGCIOq9aeC3YFoc\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_oauth_token\",\n \"info\": \"FILE:./tests/samples/dropbox_oauth_token|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sl.BdmpmC82mhhySscKk2oQGyE5l--8LdAQftLTXVGQhP39Z8FtAK1BhePhyevurA-Elt7ToIr6OpwzKAYE7RBqpu6VVyQU5WlCTL_Q7N4gElXahaWou6aPpOIwgGCIOq9aeC3YFoc\",\n \"value_start\": 15,\n \"value_end\": 153,\n \"entropy\": 5.61894\n }\n ]\n },\n {\n \"rule\": \"Dynatrace API Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMOD1DAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dynatrace_api.hs\",\n \"info\": \"FILE:./tests/samples/dynatrace_api.hs|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMOD1DAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"value_start\": 0,\n \"value_end\": 96,\n \"entropy\": 4.93241\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.965,\n \"line_data_list\": [\n {\n \"line\": \"# this is encrypted key that should be not found {\\\"secretKey\\\": \\\"ENC(2dfRFqV/cS6TzRd+JyO=)\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/encrypted_credential\",\n \"info\": \"FILE:./tests/samples/encrypted_credential|RAW\",\n \"variable\": \"secretKey\",\n \"variable_start\": 51,\n \"variable_end\": 60,\n \"value\": \"ENC(2dfRFqV/cS6TzRd+JyO=\",\n \"value_start\": 64,\n \"value_end\": 88,\n \"entropy\": 4.4183\n }\n ]\n },\n {\n \"rule\": \"Facebook Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"GI_REO_GI_FACEBOOK_TOKEN = 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\"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var PKEY = `-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 12,\n \"value_end\": 47,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.18903\n },\n {\n \"line\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.74471\n },\n {\n \"line\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 5.24555\n },\n {\n \"line\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.94996\n },\n {\n \"line\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.47641\n },\n {\n \"line\": \"-----END OPENSSH PRIVATE KEY-----\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"FILE:./tests/samples/key.go|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----END OPENSSH PRIVATE KEY-----\",\n \"value_start\": 0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"$key = 'gmUGWxhQW9KQWdhd0lCQVFRZ0ViVnpwrLzZYdDJPNG1PQjYxMXNPaFJ1\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.php\",\n \"info\": \"FILE:./tests/samples/key.php|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 1,\n \"variable_end\": 4,\n \"value\": \"gmUGWxhQW9KQWdhd0lCQVFRZ0ViVnpwrLzZYdDJPNG1PQjYxMXNPaFJ1\",\n \"value_start\": 8,\n \"value_end\": 64,\n \"entropy\": 4.96772\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.776,\n \"line_data_list\": [\n {\n \"line\": \"pkey = (\\\"LS0tLS1CRUdJTiBQUklWQVRFIENDcUdTTTQ5QXdFSEJHMHdhd0lCQVFRZ0ViVn\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": \"pkey\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": \"(\\\"LS0tLS1CRUdJTiBQUklWQVRFIENDcUdTTTQ5QXdFSEJHMHdhd0lCQVFRZ0ViVn\\\"\",\n \"value_start\": 7,\n \"value_end\": 72,\n \"entropy\": 4.80708\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"print(\\\"https://example.com/api/js?key=dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB&bug=true\\\")\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 34,\n \"variable_end\": 37,\n \"value\": \"dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB\",\n \"value_start\": 38,\n \"value_end\": 93,\n \"entropy\": 4.96282\n }\n ]\n },\n {\n \"rule\": \"SECRET_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"print(\\\"https://example.com/api/js?key=dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB&bug=true\\\")\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 34,\n \"variable_end\": 37,\n \"value\": \"dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB\",\n \"value_start\": 38,\n \"value_end\": 93,\n \"entropy\": 4.96282\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"PKEY = \\\"\\\"\\\"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 10,\n \"value_end\": 45,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.18903\n },\n {\n \"line\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.74471\n },\n {\n \"line\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 5.24555\n },\n {\n \"line\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.94996\n },\n {\n \"line\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.47641\n },\n {\n \"line\": \"-----END OPENSSH PRIVATE KEY-----\\\"\\\"\\\"\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"FILE:./tests/samples/key.py|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----END OPENSSH PRIVATE KEY-----\",\n \"value_start\": 0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.0,\n \"line_data_list\": [\n {\n \"line\": \"\\\"key\\\": \\\"api_key\\\",\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/key_value.json\",\n \"info\": \"FILE:./tests/samples/key_value.json|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 5,\n \"variable_end\": 8,\n \"value\": \"api_key\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.433,\n \"line_data_list\": [\n {\n \"line\": \"\\\"pass_mask32\\\": \\\"0x31c45018\\\",\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/key_value.json\",\n \"info\": \"FILE:./tests/samples/key_value.json|RAW\",\n \"variable\": \"pass_mask32\",\n \"variable_start\": 9,\n \"variable_end\": 20,\n \"value\": \"0x31c45018\",\n \"value_start\": 24,\n \"value_end\": 34,\n \"entropy\": 2.92193\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.529,\n \"line_data_list\": [\n {\n \"line\": \"\\\"pass_mask64\\\": \\\"0x81103c1452dd61cd\\\",\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/key_value.json\",\n \"info\": \"FILE:./tests/samples/key_value.json|RAW\",\n \"variable\": \"pass_mask64\",\n \"variable_start\": 9,\n \"variable_end\": 20,\n \"value\": \"0x81103c1452dd61cd\",\n \"value_start\": 24,\n \"value_end\": 42,\n \"entropy\": 3.2391\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"FILE:./tests/samples/llama|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.03958\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"FILE:./tests/samples/llama|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.05602\n }\n ]\n },\n {\n \"rule\": \"MailChimp API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"mailchimp = \\\"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailchimp_key\",\n \"info\": \"FILE:./tests/samples/mailchimp_key|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\",\n \"value_start\": 13,\n \"value_end\": 50,\n \"entropy\": 4.75662\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"FILE:./tests/samples/mailgun|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.91661\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"FILE:./tests/samples/mailgun|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 3.85669\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"FILE:./tests/samples/multifile.patch|RAW\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"SECRET_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n 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4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"FILE:./tests/samples/pem_key.p.log.json|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 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0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"ID_PAIR_PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n },\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"LOGIN\",\n \"variable_start\": 7,\n \"variable_end\": 12,\n \"value\": \"username\",\n \"value_start\": 13,\n \"value_end\": 21,\n \"entropy\": 2.75\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE LOGIN username WITH PASSWORD =\",\n \"variable_start\": 0,\n \"variable_end\": 37,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER chuck WITH PASSWORD 'SqLpa5sW0rD' SUPERUSER;\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE USER chuck WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 31,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 33,\n \"value_end\": 44,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD 'SqLpa5sW0rD' NOSUPERUSER;\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 45,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 47,\n \"value_end\": 58,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": 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\"confidence\": \"weak\",\n \"ml_probability\": 0.964,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 17,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 47,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.553,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'super_user'@'10.10.10.%' identified by 'SqLpa5sW0rD';\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"ALTER USER 'super_user'@'10.10.10.%' identified by\",\n \"variable_start\": 0,\n \"variable_end\": 50,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 52,\n \"value_end\": 63,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.899,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"ALTER USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.991,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 48,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 50,\n \"value_end\": 61,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"mysql -u root -pdbadmin -e \\\"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\\\"\\u2013\",\n \"line_num\": 22,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 28,\n \"variable_end\": 77,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 79,\n \"value_end\": 90,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"-c \\\"CREATE ROLE scram_test login password 'SqLpa5sW0rD'\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE ROLE scram_test login password\",\n \"variable_start\": 4,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 43,\n \"value_end\": 54,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.995,\n \"line_data_list\": [\n {\n \"line\": \"CREATE ROLE app_admin WITH LOGIN PASSWORD SqLpa5sW0rD;\",\n \"line_num\": 24,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE ROLE app_admin WITH LOGIN PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 42,\n \"value_end\": 53,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 42,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 44,\n \"value_end\": 55,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.702,\n \"line_data_list\": [\n {\n \"line\": \"create role forum_example_graph_demo login password 'SqLpa5sW0rD';\",\n \"line_num\": 26,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"create role forum_example_graph_demo login password\",\n \"variable_start\": 0,\n \"variable_end\": 51,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 53,\n \"value_end\": 64,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.722,\n \"line_data_list\": [\n {\n \"line\": \"create role forum_example_graph login password 'SqLpa5sW0rD';\",\n \"line_num\": 27,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": 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\"line\": \"insert into mysql.user values(PASSWORD('SqLpa5sW0rD') );\",\n \"line_num\": 29,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"insert into mysql.user values(PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 38,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 40,\n \"value_end\": 51,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.12,\n \"line_data_list\": [\n {\n \"line\": \"UPDATE mysql.user SET authentication_string = PASSWORD ('SqLpa5sW0rD') WHERE User = 'username';\",\n \"line_num\": 30,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"FILE:./tests/samples/sql_password|RAW\",\n \"variable\": \"UPDATE mysql.user SET authentication_string = PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 54,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 57,\n \"value_end\": 68,\n 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\"tp_token_value=\\\"b035d48j9X2dfjF0hb9sd8Guf5hWu2ia\\\"\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/token.toml\",\n \"info\": \"FILE:./tests/samples/token.toml|RAW\",\n \"variable\": \"tp_token_value\",\n \"variable_start\": 0,\n \"variable_end\": 14,\n \"value\": \"b035d48j9X2dfjF0hb9sd8Guf5hWu2ia\",\n \"value_start\": 16,\n \"value_end\": 48,\n \"entropy\": 4.22641\n }\n ]\n },\n {\n \"rule\": \"Tavily API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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 # TP\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/tvly\",\n \"info\": \"FILE:./tests/samples/tvly|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 37,\n \"entropy\": 4.84432\n }\n ]\n },\n {\n \"rule\": \"Twilio Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SK4D2F64E2A108CD72F648B1984C3B5A13\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/twilio_credentials_p\",\n \"info\": \"FILE:./tests/samples/twilio_credentials_p|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SK4D2F64E2A108CD72F648B1984C3B5A13\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 4.02086\n }\n ]\n },\n {\n \"rule\": \"Twilio Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AC4d2f64e2a108cd72f648b1984c3b5a13\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/twilio_credentials_p\",\n \"info\": \"FILE:./tests/samples/twilio_credentials_p|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AC4d2f64e2a108cd72f648b1984c3b5a13\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 4.02086\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"const connection_url = require('dbconnection://ad%6Din:5WdF4f2jE76a@db-host-local');\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"dbconnection://\",\n \"variable_start\": 32,\n \"variable_end\": 47,\n \"value\": \"5WdF4f2jE76a\",\n \"value_start\": 55,\n \"value_end\": 67,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"url = \\\"https://secure.com/83675/39084?Credential=546DFS64N90P3AW7DX%2Fkeep%26cut\\\";\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"Credential\",\n \"variable_start\": 38,\n \"variable_end\": 48,\n \"value\": \"546DFS64N90P3AW7DX%2Fkeep%26cut\\\"\",\n \"value_start\": 49,\n \"value_end\": 81,\n \"entropy\": 4.47641\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.033,\n \"line_data_list\": [\n {\n \"line\": \"// \\\"fp://no.host.real/any/path/to/nowhere/\\\",\\\"key\\\":\\\"f45VgF8jX79o@anydata.com\\\"\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 45,\n \"variable_end\": 48,\n \"value\": \"f45VgF8jX79o@anydata.com\",\n \"value_start\": 51,\n \"value_end\": 75,\n \"entropy\": 4.30351\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"39084?Credential=546DFS64N90P3AW7DX&key=3487263-2384579834-234732875-345&hasToBefound=2\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"key\",\n \"variable_start\": 36,\n \"variable_end\": 39,\n \"value\": \"3487263-2384579834-234732875-345\",\n \"value_start\": 40,\n \"value_end\": 72,\n \"entropy\": 2.97591\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"39084?Credential=546DFS64N90P3AW7DX&key=3487263-2384579834-234732875-345&hasToBefound=2\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"Credential\",\n \"variable_start\": 6,\n \"variable_end\": 16,\n \"value\": \"546DFS64N90P3AW7DX\",\n \"value_start\": 17,\n \"value_end\": 35,\n \"entropy\": 3.83659\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"email_as_login = \\\"smtps://example@gmail.com:FnD83JZs@smtp.gmail.com:465\\\";\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"smtps://\",\n \"variable_start\": 18,\n \"variable_end\": 26,\n \"value\": \"FnD83JZs\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"url3d = \\\"https://localhost.com/013948?26timestamp%3D1395782596%26token%3Dh1d3Me4ch534d801sl3jdk%26version%3D3.14%26si\\\";\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"26token\",\n \"variable_start\": 63,\n \"variable_end\": 70,\n \"value\": \"h1d3Me4ch534d801sl3jdk\",\n \"value_start\": 73,\n \"value_end\": 95,\n \"entropy\": 3.75444\n }\n ]\n },\n {\n \"rule\": \"DOC_CREDENTIALS\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"if (password !== \\\"PaS5w0rD2#\\\"){\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"PaS5w0rD2#\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"PASSWD_PAIR\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"if (password !== \\\"PaS5w0rD2#\\\"){\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"PaS5w0rD2#\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.933,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"line\\\": \\\"url: mongodb://jrfdeg42:p4Dsr8b@127.0.0.1:32768/architecture\\\"}\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"FILE:./tests/samples/url_cred.js|RAW\",\n \"variable\": \"mongodb://\",\n \"variable_start\": 15,\n \"variable_end\": 25,\n \"value\": \"p4Dsr8b\",\n \"value_start\": 34,\n \"value_end\": 41,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"bace4d19-fa7e-beef-cafe-9129474bcd81 # tp\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/uuid\",\n \"info\": \"FILE:./tests/samples/uuid|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"bace4d19-fa7e-beef-cafe-9129474bcd81\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.58954\n }\n ]\n },\n {\n \"rule\": \"Vercel Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/vercel\",\n \"info\": \"FILE:./tests/samples/vercel|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"value_start\": 0,\n \"value_end\": 60,\n \"entropy\": 5.23581\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wxe191bc54fc7d529a\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"FILE:./tests/samples/wechat_p|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wxe191bc54fc7d529a\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.72548\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wx2274a335e18222d6\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"FILE:./tests/samples/wechat_p|RAW\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wx2274a335e18222d6\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.41383\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n 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password:dipPr17Gg!\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 12,\n \"variable_end\": 20,\n \"value\": \"dipPr17Gg!\",\n \"value_start\": 21,\n \"value_end\": 31,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"username:master,password:dipPr19Gg!\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 16,\n \"variable_end\": 24,\n \"value\": \"dipPr19Gg!\",\n \"value_start\": 25,\n \"value_end\": 35,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"username:master pwd:dipPr110Gg!\",\n \"line_num\": 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23,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ID:PW=master:iPp4@GRq\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master:iPp4@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW=master/iPp5@GRq\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master/iPp5@GRq\",\n \"value_start\": 6,\n \"value_end\": 21,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": 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{\n \"line\": \"\\uc544\\uc774\\ub514/PW:master/iPp16@GRq\",\n \"line_num\": 17,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 4,\n \"variable_end\": 6,\n \"value\": \"master/iPp16@GRq\",\n \"value_start\": 7,\n \"value_end\": 23,\n \"entropy\": 4.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"\\uacc4\\uc815/PW:master/iPp17@GRq\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/doc_id_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 3,\n \"variable_end\": 5,\n \"value\": \"master/iPp17@GRq\",\n \"value_start\": 6,\n \"value_end\": 22,\n \"entropy\": 4.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"98.76.54.32 id/pw:master/iPp19@GRq\",\n 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\"value\": \"IhqSb1Gg\",\n \"value_start\": 45,\n \"value_end\": 53,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gildong.hong@98.76.54.32 mailto:{1} (pass:IhqSb1Gg)\",\n \"line_num\": 97,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 37,\n \"variable_end\": 41,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 42,\n \"value_end\": 50,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ssh gildong.hong@98.76.54.32 mailto:{1} pw:IhqSb1Gg\",\n \"line_num\": 100,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pw\",\n \"variable_start\": 40,\n \"variable_end\": 42,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 43,\n \"value_end\": 51,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ssh gildong.hong@98.76.54.32 mailto:{1} pass:IhqSb1Gg\",\n \"line_num\": 101,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 40,\n \"variable_end\": 44,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 45,\n \"value_end\": 53,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"id:gildong.hong@xxx.com mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 102,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 35,\n \"variable_end\": 43,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ID PW gildong.hong@example.com mailto:{1} IhqSb1Gg\",\n \"line_num\": 103,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"PW gildong.hong@example.com mailto\",\n \"variable_start\": 3,\n \"variable_end\": 37,\n \"value\": \"\",\n \"value_start\": 38,\n \"value_end\": 38,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ssh gildong.hong@98.76.54.32 mailto:{1}/password:IhqSb1Gg\",\n \"line_num\": 104,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 40,\n \"variable_end\": 48,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 49,\n \"value_end\": 57,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"-ANYID:gildong.hong@example.com mailto:{1} -pw:IhqSb1Gg\",\n \"line_num\": 105,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pw\",\n \"variable_start\": 44,\n \"variable_end\": 46,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 47,\n \"value_end\": 55,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ID:gildong.hong@xxxx.net mailto:{1} pw:IhqSb1Gg\",\n \"line_num\": 106,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pw\",\n \"variable_start\": 36,\n \"variable_end\": 38,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 39,\n \"value_end\": 47,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ID/PW 98.76.54.32:xxx master/IhqSb1Gg\",\n \"line_num\": 107,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"PW 98.76.54.32\",\n \"variable_start\": 3,\n \"variable_end\": 17,\n \"value\": \"\",\n \"value_start\": 18,\n \"value_end\": 18,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"http://98.76.54.32:xxx(pw:IhqSb1Gg)\",\n \"line_num\": 108,\n \"path\": \"./tests/samples/doc_various\",\n \"info\": \"\",\n \"variable\": \"pw\",\n \"variable_start\": 23,\n \"variable_end\": 25,\n \"value\": \"IhqSb1Gg\",\n \"value_start\": 26,\n \"value_end\": 34,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: dckr_pat_mcF-hLK_JoBxXUNJy1kU7-WSbk0\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_pat_mcF-hLK_JoBxXUNJy1kU7-WSbk0\",\n \"value_start\": 10,\n \"value_end\": 46,\n \"entropy\": 4.68354\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"NEGATIVE: dckr_pat_EXAMPLE-EXAMPLE-EXAMPLE-123\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_pat_EXAMPLE-EXAMPLE-EXAMPLE-123\",\n \"value_start\": 10,\n \"value_end\": 46,\n \"entropy\": 3.89106\n }\n ]\n },\n {\n \"rule\": \"Docker Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: dckr_oat_fXUgJy1nU2WSbk_0vH2S-mcF-hLKJoB-\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dckr_oat_fXUgJy1nU2WSbk_0vH2S-mcF-hLKJoB-\",\n \"value_start\": 10,\n \"value_end\": 51,\n \"entropy\": 4.78414\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: SWMTKN-1-edmua5ub12inlget8wkvz35kckxkeyznuvc49brsy84wgfssrw-otjll8wdy3yikfrksskvqzqh1\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMTKN-1-edmua5ub12inlget8wkvz35kckxkeyznuvc49brsy84wgfssrw-otjll8wdy3yikfrksskvqzqh1\",\n \"value_start\": 10,\n \"value_end\": 95,\n \"entropy\": 5.06757\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"NEGATIVE: SWMTKN-1-7here4ar3not7he7oken5you4re1ooking4or1samplingonly-nh7cr8ap4o4fl58ektr42c8ek\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMTKN-1-7here4ar3not7he7oken5you4re1ooking4or1samplingonly-nh7cr8ap4o4fl58ektr42c8ek\",\n \"value_start\": 10,\n \"value_end\": 95,\n \"entropy\": 4.65986\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"POSITIVE: SWMKEY-1-fySn8TY4w5lKcWcJPIpKufejh9hxx5KYwx6XZigx3Q4\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMKEY-1-fySn8TY4w5lKcWcJPIpKufejh9hxx5KYwx6XZigx3Q4\",\n \"value_start\": 10,\n \"value_end\": 62,\n \"entropy\": 4.95515\n }\n ]\n },\n {\n \"rule\": \"Docker Swarm Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"NEGATIVE: SWMKEY-1-7c37Cc8654o6pExampleKeyTestOnlytbdZEgtKxZu8\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/docker\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SWMKEY-1-7c37Cc8654o6pExampleKeyTestOnlytbdZEgtKxZu8\",\n \"value_start\": 10,\n \"value_end\": 62,\n \"entropy\": 4.95006\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 7,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 1178,\n \"variable_end\": 1186,\n \"value\": \"String<\",\n \"value_start\": 1188,\n \"value_end\": 1197,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Salt\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 7,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"salt\",\n \"variable_start\": 2348,\n \"variable_end\": 2352,\n \"value\": \"String<\",\n \"value_start\": 2354,\n \"value_end\": 2363,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 13,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"Password\",\n \"variable_start\": 146,\n \"variable_end\": 154,\n \"value\": \"Dw7^&amp;nd&lt;dj\",\n \"value_start\": 162,\n \"value_end\": 187,\n \"entropy\": 3.59327\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 13,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"bace4d19-fa7e-b2e4-1afe-9129474bcd81\",\n \"value_start\": 100,\n \"value_end\": 136,\n \"entropy\": 3.60702\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 16,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"textpassword\",\n \"variable_start\": 46,\n \"variable_end\": 58,\n \"value\": \"Df34D&\",\n \"value_start\": 60,\n \"value_end\": 69,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 28,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 35,\n \"variable_end\": 40,\n \"value\": \"String\",\n \"value_start\": 42,\n \"value_end\": 48,\n \"entropy\": 2.58496\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 31,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"secret\",\n \"variable_start\": 35,\n \"variable_end\": 41,\n \"value\": \"&\",\n \"value_start\": 43,\n \"value_end\": 47,\n \"entropy\": 2.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 34,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 35,\n \"variable_end\": 39,\n \"value\": \"Dsfgh%$d&\",\n \"value_start\": 41,\n \"value_end\": 53,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 45,\n \"path\": \"./tests/samples/drawio\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ce49dba1-e4fe-b2a7-4ffa-132bcd819474\",\n \"value_start\": 52,\n \"value_end\": 88,\n \"entropy\": 3.68703\n }\n ]\n },\n {\n \"rule\": \"Dropbox API secret (long term)\",\n \"severity\": \"high\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var g = '7rBynGo0b1cAAAAAAAAAAc72L3T6rQK51mB5a06ijnwRG91deTxvSqdZNAlxq8pZ'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_api_secret_long_term\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"7rBynGo0b1cAAAAAAAAAAc72L3T6rQK51mB5a06ijnwRG91deTxvSqdZNAlxq8pZ\",\n \"value_start\": 9,\n \"value_end\": 73,\n \"entropy\": 4.89362\n }\n ]\n },\n {\n \"rule\": \"Dropbox App secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var app_unique_val_s = 'wpv1jq9xwanbn3n';\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_app_secret\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wpv1jq9xwanbn3n\",\n \"value_start\": 24,\n \"value_end\": 39,\n \"entropy\": 3.45656\n }\n ]\n },\n {\n \"rule\": \"Dropbox App secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"negative case: inconshreveable\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/dropbox_app_secret\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"inconshreveable\",\n \"value_start\": 15,\n \"value_end\": 30,\n \"entropy\": 3.45656\n }\n ]\n },\n {\n \"rule\": \"Dropbox OAuth2 API Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var dropbox = 'sl.BdmpmC82mhhySscKk2oQGyE5l--8LdAQftLTXVGQhP39Z8FtAK1BhePhyevurA-Elt7ToIr6OpwzKAYE7RBqpu6VVyQU5WlCTL_Q7N4gElXahaWou6aPpOIwgGCIOq9aeC3YFoc';\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dropbox_oauth_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sl.BdmpmC82mhhySscKk2oQGyE5l--8LdAQftLTXVGQhP39Z8FtAK1BhePhyevurA-Elt7ToIr6OpwzKAYE7RBqpu6VVyQU5WlCTL_Q7N4gElXahaWou6aPpOIwgGCIOq9aeC3YFoc\",\n \"value_start\": 15,\n \"value_end\": 153,\n \"entropy\": 5.61894\n }\n ]\n },\n {\n \"rule\": \"Dynatrace API Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMOD1DAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/dynatrace_api.hs\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMOD1DAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\",\n \"value_start\": 0,\n \"value_end\": 96,\n \"entropy\": 4.93241\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"# this is encrypted key that should be not found {\\\"secretKey\\\": \\\"ENC(2dfRFqV/cS6TzRd+JyO=)\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/encrypted_credential\",\n \"info\": \"\",\n \"variable\": \"secretKey\",\n \"variable_start\": 51,\n \"variable_end\": 60,\n \"value\": \"ENC(2dfRFqV/cS6TzRd+JyO=)\",\n \"value_start\": 64,\n \"value_end\": 89,\n \"entropy\": 4.48386\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"# this is encrypted key that should be not found {\\\"secretKey\\\": \\\"ENC(2dfRFqV/cS6TzRd+JyO=)\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/encrypted_credential\",\n \"info\": \"\",\n \"variable\": \"secretKey\",\n \"variable_start\": 51,\n \"variable_end\": 60,\n \"value\": \"ENC(2dfRFqV/cS6TzRd+JyO=)\",\n \"value_start\": 64,\n \"value_end\": 89,\n \"entropy\": 4.48386\n }\n ]\n },\n {\n \"rule\": \"Facebook Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"GI_REO_GI_FACEBOOK_TOKEN = \\\"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/facebook_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\",\n \"value_start\": 28,\n \"value_end\": 115,\n \"entropy\": 4.93612\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"GI_REO_GI_FACEBOOK_TOKEN = \\\"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/facebook_key\",\n \"info\": \"\",\n \"variable\": \"GI_REO_GI_FACEBOOK_TOKEN\",\n \"variable_start\": 0,\n \"variable_end\": 24,\n \"value\": \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\",\n \"value_start\": 28,\n \"value_end\": 115,\n \"entropy\": 4.93612\n }\n ]\n },\n {\n \"rule\": \"Facebook App Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"1527194624358273|qbBf2-fdB9zZpqLA0_2nNzZDw2M\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/facebook_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"1527194624358273|qbBf2-fdB9zZpqLA0_2nNzZDw2M\",\n \"value_start\": 0,\n \"value_end\": 44,\n \"entropy\": 4.60694\n }\n ]\n },\n {\n \"rule\": \"Figma Personal Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"figd__fU7rxH-KUAmCv5vI78kKlnEF6bne_yvSvPLz3JO\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/figma\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"figd__fU7rxH-KUAmCv5vI78kKlnEF6bne_yvSvPLz3JO\",\n \"value_start\": 0,\n \"value_end\": 45,\n \"entropy\": 4.98619\n }\n ]\n },\n {\n \"rule\": \"Figma Personal Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"figd_h65Ugiu76WD3xf233a6KAmo9ZmbWNnNrny9Q6IHl\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/figma\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"figd_h65Ugiu76WD3xf233a6KAmo9ZmbWNnNrny9Q6IHl\",\n \"value_start\": 0,\n \"value_end\": 45,\n \"entropy\": 4.85286\n }\n ]\n },\n {\n \"rule\": \"Figma Personal Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"figd_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/figma\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"figd_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\",\n \"value_start\": 0,\n \"value_end\": 45,\n \"entropy\": 0.76125\n }\n ]\n },\n {\n \"rule\": \"Firebase Domain\",\n \"severity\": \"info\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"test-app-domain-42.firebaseapp.com\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/firebase_domain\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"test-app-domain-42.firebaseapp.com\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 3.98423\n }\n ]\n },\n {\n \"rule\": \"Firebase Domain\",\n \"severity\": \"info\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"test2.io.firebaseio.com\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/firebase_domain\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"test2.io.firebaseio.com\",\n \"value_start\": 0,\n \"value_end\": 23,\n \"entropy\": 3.52271\n }\n ]\n },\n {\n \"rule\": \"Github Classic Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ghp_00000000000000000000000000000004WZ4EQ # classic\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/github_classic_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ghp_00000000000000000000000000000004WZ4EQ\",\n \"value_start\": 0,\n \"value_end\": 41,\n \"entropy\": 1.56292\n }\n ]\n },\n {\n \"rule\": \"Github Classic Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ghp_1010110010001010101001010101010101011001 # random\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/github_classic_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ghp_1010110010001010101001010101010101011001\",\n \"value_start\": 0,\n \"value_end\": 44,\n \"entropy\": 1.52877\n }\n ]\n },\n {\n \"rule\": \"Github Fine-granted Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/github_fine_granted_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 93,\n \"entropy\": 5.41519\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glpat-8d5ri2n9g85LAnC9YW85.01.cgpAsnEmP # Personal access token, Impersonation token, Project access token, Group access token\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glpat-8d5ri2n9g85LAnC9YW85.01.cgpAsnEmP\",\n \"value_start\": 0,\n \"value_end\": 39,\n \"entropy\": 4.59259\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gloas-7fc1974b38580e6ceca8c077863cd5e88745895dfcbe1ae3c36eab9c498103dc # OAuth Application Secret\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"gloas-7fc1974b38580e6ceca8c077863cd5e88745895dfcbe1ae3c36eab9c498103dc\",\n \"value_start\": 0,\n \"value_end\": 70,\n \"entropy\": 4.0466\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gldt-9BeUoeWu2V9uUS3uLoMy # Deploy token\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"gldt-9BeUoeWu2V9uUS3uLoMy\",\n \"value_start\": 0,\n \"value_end\": 25,\n \"entropy\": 4.13366\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glrt-2CR8_eVxiio-1QmzPZwa # Runner authentication token\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glrt-2CR8_eVxiio-1QmzPZwa\",\n \"value_start\": 0,\n \"value_end\": 25,\n \"entropy\": 4.48386\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glcbt-1375_cgpAsnEmP-79kcfRLyK_\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glcbt-1375_cgpAsnEmP-79kcfRLyK_\",\n \"value_start\": 0,\n \"value_end\": 31,\n \"entropy\": 4.54275\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glcbt-0_c1k_AsgyRp4mP-Kcn8fL # CI/CD Job token\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glcbt-0_c1k_AsgyRp4mP-Kcn8fL\",\n \"value_start\": 0,\n \"value_end\": 28,\n \"entropy\": 4.42325\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glptt-33276248c9748113e978392e5c074b7f974f8683 # Trigger token\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glptt-33276248c9748113e978392e5c074b7f974f8683\",\n \"value_start\": 0,\n \"value_end\": 46,\n \"entropy\": 3.96956\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glft-Aafqn5A31G-2VipZMh28 # Feed token\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glft-Aafqn5A31G-2VipZMh28\",\n \"value_start\": 0,\n \"value_end\": 25,\n \"entropy\": 4.32386\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glimt-1jpqzsnw2n71om0r9kgt06os3 # Incoming mail token\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glimt-1jpqzsnw2n71om0r9kgt06os3\",\n \"value_start\": 0,\n \"value_end\": 31,\n \"entropy\": 4.43807\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glagent-ZQmgbRr-Ydu5YehnXCGiiSLxjd53EkFnYapS7A4TwyNE8Y2XVg # GitLab agent for Kubernetes token\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glagent-ZQmgbRr-Ydu5YehnXCGiiSLxjd53EkFnYapS7A4TwyNE8Y2XVg\",\n \"value_start\": 0,\n \"value_end\": 58,\n \"entropy\": 5.18979\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"_gitlab_session=8d2a78c080a3af1e6a4677be474432f2 # GitLab session cookies\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"_gitlab_session=8d2a78c080a3af1e6a4677be474432f2\",\n \"value_start\": 0,\n \"value_end\": 48,\n \"entropy\": 4.32185\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glsoat-971om0ecn5A386r9k481 # SCIM Tokens\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glsoat-971om0ecn5A386r9k481\",\n \"value_start\": 0,\n \"value_end\": 27,\n \"entropy\": 4.45859\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glffct-AnRWYdo3Si_Xm2Q6n7zu # Feature Flags Client token\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glffct-AnRWYdo3Si_Xm2Q6n7zu\",\n \"value_start\": 0,\n \"value_end\": 27,\n \"entropy\": 4.60674\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glrtr-KZX7Mizo7RYFKh2JScz6aeqZ3WG8nxujE21QpZVIr # Registration runner token\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glrtr-KZX7Mizo7RYFKh2JScz6aeqZ3WG8nxujE21QpZVIr\",\n \"value_start\": 0,\n \"value_end\": 47,\n \"entropy\": 5.18204\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"glwt-G9dr9LJjGiSfBdxzDVyHi7vSdDcAftOmJ # Workspace token\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"glwt-G9dr9LJjGiSfBdxzDVyHi7vSdDcAftOmJ\",\n \"value_start\": 0,\n \"value_end\": 38,\n \"entropy\": 4.70175\n }\n ]\n },\n {\n \"rule\": \"Gitlab Prefix Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"GR1348941jG6xeSsmN8DFVKoyBYu2 # Runner registration token\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/gitlab_prefix_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"GR1348941jG6xeSsmN8DFVKoyBYu2\",\n \"value_start\": 0,\n \"value_end\": 29,\n \"entropy\": 4.58212\n }\n ]\n },\n {\n \"rule\": \"Google API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AIzaGiReoG-Cr0ckleCr0ckle12315618_12315 # Google API Key\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/google_creds\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AIzaGiReoG-Cr0ckleCr0ckle12315618_12315\",\n \"value_start\": 0,\n \"value_end\": 39,\n \"entropy\": 4.35298\n }\n ]\n },\n {\n \"rule\": \"Google OAuth Secret\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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 # Google OAuth Secret\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/google_creds\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 35,\n \"entropy\": 4.67214\n }\n ]\n },\n {\n \"rule\": \"Google OAuth Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ya29.zmZDrADaFxE_IS6fl4sbDxCpH-ltO2BoHEwXOglsXbgd_S # Google OAuth Access Token\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/google_creds\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ya29.zmZDrADaFxE_IS6fl4sbDxCpH-ltO2BoHEwXOglsXbgd_S\",\n \"value_start\": 0,\n \"value_end\": 51,\n \"entropy\": 5.01537\n }\n ]\n },\n {\n \"rule\": \"Google OAuth Refresh Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": 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-2,\n \"variable_end\": -2,\n \"value\": \"WXFES7QN4EXAMPLE\",\n \"value_start\": 0,\n \"value_end\": 16,\n \"entropy\": 3.57782\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"https://oauth.myapp.com/v3/access_token?app_id=my-client-id&app_secret=my-client-password&code=q4C1a20qS&redirect_uri=http%3A%2F%2Flocalhost%2Fdummy-demo\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/pass_filtered\",\n \"info\": \"\",\n \"variable\": \"app_secret\",\n \"variable_start\": 60,\n \"variable_end\": 70,\n \"value\": \"my-client-password\",\n \"value_start\": 71,\n \"value_end\": 89,\n \"entropy\": 3.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"0xAb19D82E7f546cC3\\\"\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/pass_filtered\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"0xAb19D82E7f546cC3\",\n \"value_start\": 12,\n \"value_end\": 30,\n \"entropy\": 4.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password_id = 2938479\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/pass_filtered\",\n \"info\": \"\",\n \"variable\": \"password_id\",\n \"variable_start\": 0,\n \"variable_end\": 11,\n \"value\": \"2938479\",\n \"value_start\": 14,\n \"value_end\": 21,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"gi_reo_gi_passwd\",\n \"variable_start\": 0,\n \"variable_end\": 16,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 20,\n \"value_end\": 30,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"password_confirmation\",\n \"variable_start\": 33,\n \"variable_end\": 54,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 58,\n \"value_end\": 68,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"mypw: KrAcMe12345,\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"mypw\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": \"KrAcMe12345\",\n \"value_start\": 6,\n \"value_end\": 17,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"masked_password = *****1*****2;\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"masked_password\",\n \"variable_start\": 0,\n \"variable_end\": 15,\n \"value\": \"*****1*****2\",\n \"value_start\": 18,\n \"value_end\": 30,\n \"entropy\": 0.81669\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"cackle!\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.gradle\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"MYPSWRD!@#$%^&*\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.tfvars\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"MYPSWRD!@#$%^&*\",\n \"value_start\": 12,\n \"value_end\": 27,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"#define PASSWORD 0x0dead1beef7cafe2\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password_FALSE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"0x0dead1beef7cafe2\",\n \"value_start\": 17,\n \"value_end\": 35,\n \"entropy\": 3.28104\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"abc\\\"\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/password_FALSE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"\",\n \"value_start\": 11,\n \"value_end\": 11,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"M[@%]PW:2Z.Q?2M^S;`4G?E0C.@V&?0KY]]\\\"H3Y@6$#I4V*R^\\\"+B,2P6`A)UL\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_FALSE\",\n \"info\": \"\",\n \"variable\": \"]PW\",\n \"variable_start\": 4,\n \"variable_end\": 7,\n \"value\": \"2Z.Q?2M^S\",\n \"value_start\": 8,\n \"value_end\": 17,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"MYSQLPASS: Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQLPASS\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"value_start\": 11,\n \"value_end\": 37,\n \"entropy\": 3.8693\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"my_pw: nCzx8A8#!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"my_pw\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 7,\n \"value_end\": 16,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"val password: String = \\\"exord13Paw64\\\", // scala\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"exord13Paw64\",\n \"value_start\": 24,\n \"value_end\": 36,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"def connect(passwd: str = \\\"cq2tPr1a2\\\"): # python default arg\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passwd\",\n \"variable_start\": 12,\n \"variable_end\": 18,\n \"value\": \"cq2tPr1a2\",\n \"value_start\": 27,\n \"value_end\": 36,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd == \\\"q4c1a2oPd\\\": # __eq__ separator\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"q4c1a2oPd\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd != \\\"x6s7djtEa\\\": # __ne__ separator\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"x6s7djtEa\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password=2bkJgtJDiLcq1t\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"2bkJgtJDiLcq1t\",\n \"value_start\": 9,\n \"value_end\": 23,\n \"entropy\": 3.52164\n }\n ]\n },\n {\n \"rule\": \"CMD Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passin\",\n \"variable_start\": 33,\n \"variable_end\": 39,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 41,\n \"variable_end\": 45,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"MYSQL_DATABASE_USER=CRED;MYSQL_DATABASE_PASSWORD=2IWJD88FH4Y;\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQL_DATABASE_PASSWORD\",\n \"variable_start\": 25,\n \"variable_end\": 48,\n \"value\": \"2IWJD88FH4Y\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"#define password \\\"n84ASM54y4\\\"\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"#define password {0x48, 0x65, 0x6C, 0x6C, 0x30}\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"0x48, 0x65, 0x6C, 0x6C, 0x30\",\n \"value_start\": 18,\n \"value_end\": 46,\n \"entropy\": 3.02613\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"%define PASSWORD \\\"n84ASM54y4\\\"\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"%global PASSWORD \\\"n84RPM54y4\\\"\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84RPM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SET password \\\"n83.bat47Fy4\\\"\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"n83.bat47Fy4\",\n \"value_start\": 14,\n \"value_end\": 26,\n \"entropy\": 3.4183\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"\\\"#define\\\\tpassword\\\\t\\\\\\\"n84ASM54y4\\\\\\\"\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 22,\n \"value_end\": 32,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"WPA2_PASSWORD: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"WPA2_PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 13,\n \"value\": \"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"value_start\": 15,\n \"value_end\": 79,\n \"entropy\": 3.67082\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/password_utf16.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajc\\u00f61\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password_western.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajc\\u00f61\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"PayPal Braintree Access Token\",\n 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t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 gx1/q1EgS5w2ciAuC8u5gitd1ie43B5lsysO0MY31Qy1eGO1Sj0g4pxM2szbpwso\\\\r\\\\n2026-04-26 12:36:01 0RZL8aKk645hElitcXDx8wUVc0Zm/Av4FsSiZkhFeKaHSAXJtTtlAkLMMTZaNwBA\\\\r\\\\n2026-04-26 12:36:01 hqmHqqtalptZmwGz2F0dmXF9cy+gOxzaBhQbVcH8SDdchpgTl14B93qh2iY2RjxY\\\\r\\\\n2026-04-26 12:36:01 Eb3kpsPG0cdLTAAahEALuMu26YFpglJXAkwSwSLPYsGRPHjJFiXfWBR05x5y5wdB\\\\r\\\\n2026-04-26 12:36:01 1jhhqlV6ZHO/osEJKb6tSHH0mYf0uMNu2speu2DgsjCjHHJwtSJMayfO1WZcSF+G\\\\r\\\\n2026-04-26 12:36:01 wFXOY77MgB3VwMRcCoTMNwoBswcJeZRyNL+cHLZZcK0kpEJbBY60W5pHUceKrDDJ\\\\r\\\\n2026-04-26 12:36:01 sr63qzPaUVNj0Vu2zFG8sEEMES55/JIKCoj6O66j821/qJ97RLPP5pKUpp2gCS7F\\\\r\\\\n2026-04-26 12:36:01 GyCzMBiTsF4zNCr+FA1rQUCZqa50S3Gu90KANsv7VX1krJXXaSXQFaiDAyB+zL0f\\\\r\\\\n2026-04-26 12:36:01 SQR7WrimYwMQaGX8c75+8L7NK2zdxMQH0chtdqv79WmoOn+fWGupCq7NlA32s7rb\\\\r\\\\n2026-04-26 12:36:01 Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 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JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 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Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 Kqmr2XMicIWCxQoiW4YT5UYfNsfwmRUWkJwmCahUFSzo5swUpBbeCo6bsEdkyxMM\\\\r\\\\n2026-04-26 12:36:01 I5bNV1cjSII5liHOyxnvZ77+giZAKglsiI3ZmmVh+l8fvDBDaLVmmMRfcwRHOxu1\\\\r\\\\n2026-04-26 12:36:01 UMRr047T8ggKgEnyhQLK/FJh+Yp8ubo6wsTUwyyVcRULUVWeJbka6EDkMbPucHHb\\\\r\\\\n2026-04-26 12:36:01 vDdO61eP2yB+uQlwbBr1UquiQD1XrBHXFVwDw6rJoJxTkGQggaofpsUPa3F561LV\\\\r\\\\n2026-04-26 12:36:01 aQAFxU9BAgmdYb4uJxtlt46DCbx2tFW2OnoqQrpFW7nWlwmLJ2dUhIRkySTyhJpq\\\\r\\\\n2026-04-26 12:36:01 K0hnrLThhA1tu8q3dTXOCDs+8csKnI9vVSqAFm6ax3lI6ilBFVIgyZi7dBI1TCKp\\\\r\\\\n2026-04-26 12:36:01 rDbvCzcWY6dxEUzHqTELG5sd955LQgoei2/86QDquRIgB2PGqblBYylUOA9tBTAv\\\\r\\\\n2026-04-26 12:36:01 wSVKoZuonI4ijDZz5yec2C9DiCZva6MbxASOLBl05qfeeDbzkhOWsas2ZpMRmaS8\\\\r\\\\n2026-04-26 12:36:01 dI0Tmp732GkddM2R879ULHp0x4CI4Vh42mN/m22OInwW4mlPaUAy4MQUOWvuWb6/\\\\r\\\\n2026-04-26 12:36:01 o2/HcXJCoj9JsULCKXchFrawJHTgCTpi9BicMpmnPHpnpxlYRw77p4qWcmGqs2Yi\\\\r\\\\n2026-04-26 12:36:01 gQLAAQhZxzpT8MPgsomgC2nySQthEHsvF4XVbL60ImBv9Qig2hd7Jh4cI0D/+TdC\\\\r\\\\n2026-04-26 12:36:01 tky6B1MyPAxYCTN2QXXCo6CbdzMoVBhXuAI7prv2DA5zUwNCpxBKs2BgSIZ9677J\\\\r\\\\n2026-04-26 12:36:01 RlxpsqbbVLVJl6BdbJcMRjIWEW0flKwbSb/PdEuEGheu5UuRZ4/MxrzrciW35CxX\\\\r\\\\n2026-04-26 12:36:01 +XYlHBLCOQ6MCCSYtAy9olSBxQ1iMkiP0V20Crzm6JapZWxTC1EEFgMXAJERMXin\\\\r\\\\n2026-04-26 12:36:01 NiY0wK8f8JFABRBxMZeHyBtT6EobR2Q1Ozcjmhb98rK6wUVhorCGV0mbZ4jzVFtH\\\\r\\\\n2026-04-26 12:36:01 YD9UoTAQrI22NGLy+BupkM7OmaQ82SWZlZ8eiSqv5z7aBI8AAWOORHCYW07i9kCy\\\\r\\\\n2026-04-26 12:36:01 OJ4nB3/Ko4OTiUeGYamtlj9/k7alhM5BE2fkEoygYFvL1cfFXMHH+wOEonSMi5qo\\\\r\\\\n2026-04-26 12:36:01 smQrWalr8aPEPGkXWYDjMsBZ4rHQ00z+cE3YiXJXMj2Y8JMY9LJrR1asaEY3IoBx\\\\r\\\\n2026-04-26 12:36:01 ose+UxmIsZr1OD/Jy1euBJo0IQX3gnrvdGl9u8zQeCes+g5xl68gAU8n1J/Z4DoB\\\\r\\\\n2026-04-26 12:36:01 Y0mUMEgOuMu6aAvmQc/lqqP7lwrCKCfVe6SS6w2w3I9GrL2/3GkQkXJSc4rmZb7u\\\\r\\\\n2026-04-26 12:36:01 JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\",\n \"value_start\": 157,\n \"value_end\": 6245,\n \"entropy\": 5.8771\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 gx1/q1EgS5w2ciAuC8u5gitd1ie43B5lsysO0MY31Qy1eGO1Sj0g4pxM2szbpwso\\\\r\\\\n2026-04-26 12:36:01 0RZL8aKk645hElitcXDx8wUVc0Zm/Av4FsSiZkhFeKaHSAXJtTtlAkLMMTZaNwBA\\\\r\\\\n2026-04-26 12:36:01 hqmHqqtalptZmwGz2F0dmXF9cy+gOxzaBhQbVcH8SDdchpgTl14B93qh2iY2RjxY\\\\r\\\\n2026-04-26 12:36:01 Eb3kpsPG0cdLTAAahEALuMu26YFpglJXAkwSwSLPYsGRPHjJFiXfWBR05x5y5wdB\\\\r\\\\n2026-04-26 12:36:01 1jhhqlV6ZHO/osEJKb6tSHH0mYf0uMNu2speu2DgsjCjHHJwtSJMayfO1WZcSF+G\\\\r\\\\n2026-04-26 12:36:01 wFXOY77MgB3VwMRcCoTMNwoBswcJeZRyNL+cHLZZcK0kpEJbBY60W5pHUceKrDDJ\\\\r\\\\n2026-04-26 12:36:01 sr63qzPaUVNj0Vu2zFG8sEEMES55/JIKCoj6O66j821/qJ97RLPP5pKUpp2gCS7F\\\\r\\\\n2026-04-26 12:36:01 GyCzMBiTsF4zNCr+FA1rQUCZqa50S3Gu90KANsv7VX1krJXXaSXQFaiDAyB+zL0f\\\\r\\\\n2026-04-26 12:36:01 SQR7WrimYwMQaGX8c75+8L7NK2zdxMQH0chtdqv79WmoOn+fWGupCq7NlA32s7rb\\\\r\\\\n2026-04-26 12:36:01 Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 Kqmr2XMicIWCxQoiW4YT5UYfNsfwmRUWkJwmCahUFSzo5swUpBbeCo6bsEdkyxMM\\\\r\\\\n2026-04-26 12:36:01 I5bNV1cjSII5liHOyxnvZ77+giZAKglsiI3ZmmVh+l8fvDBDaLVmmMRfcwRHOxu1\\\\r\\\\n2026-04-26 12:36:01 UMRr047T8ggKgEnyhQLK/FJh+Yp8ubo6wsTUwyyVcRULUVWeJbka6EDkMbPucHHb\\\\r\\\\n2026-04-26 12:36:01 vDdO61eP2yB+uQlwbBr1UquiQD1XrBHXFVwDw6rJoJxTkGQggaofpsUPa3F561LV\\\\r\\\\n2026-04-26 12:36:01 aQAFxU9BAgmdYb4uJxtlt46DCbx2tFW2OnoqQrpFW7nWlwmLJ2dUhIRkySTyhJpq\\\\r\\\\n2026-04-26 12:36:01 K0hnrLThhA1tu8q3dTXOCDs+8csKnI9vVSqAFm6ax3lI6ilBFVIgyZi7dBI1TCKp\\\\r\\\\n2026-04-26 12:36:01 rDbvCzcWY6dxEUzHqTELG5sd955LQgoei2/86QDquRIgB2PGqblBYylUOA9tBTAv\\\\r\\\\n2026-04-26 12:36:01 wSVKoZuonI4ijDZz5yec2C9DiCZva6MbxASOLBl05qfeeDbzkhOWsas2ZpMRmaS8\\\\r\\\\n2026-04-26 12:36:01 dI0Tmp732GkddM2R879ULHp0x4CI4Vh42mN/m22OInwW4mlPaUAy4MQUOWvuWb6/\\\\r\\\\n2026-04-26 12:36:01 o2/HcXJCoj9JsULCKXchFrawJHTgCTpi9BicMpmnPHpnpxlYRw77p4qWcmGqs2Yi\\\\r\\\\n2026-04-26 12:36:01 gQLAAQhZxzpT8MPgsomgC2nySQthEHsvF4XVbL60ImBv9Qig2hd7Jh4cI0D/+TdC\\\\r\\\\n2026-04-26 12:36:01 tky6B1MyPAxYCTN2QXXCo6CbdzMoVBhXuAI7prv2DA5zUwNCpxBKs2BgSIZ9677J\\\\r\\\\n2026-04-26 12:36:01 RlxpsqbbVLVJl6BdbJcMRjIWEW0flKwbSb/PdEuEGheu5UuRZ4/MxrzrciW35CxX\\\\r\\\\n2026-04-26 12:36:01 +XYlHBLCOQ6MCCSYtAy9olSBxQ1iMkiP0V20Crzm6JapZWxTC1EEFgMXAJERMXin\\\\r\\\\n2026-04-26 12:36:01 NiY0wK8f8JFABRBxMZeHyBtT6EobR2Q1Ozcjmhb98rK6wUVhorCGV0mbZ4jzVFtH\\\\r\\\\n2026-04-26 12:36:01 YD9UoTAQrI22NGLy+BupkM7OmaQ82SWZlZ8eiSqv5z7aBI8AAWOORHCYW07i9kCy\\\\r\\\\n2026-04-26 12:36:01 OJ4nB3/Ko4OTiUeGYamtlj9/k7alhM5BE2fkEoygYFvL1cfFXMHH+wOEonSMi5qo\\\\r\\\\n2026-04-26 12:36:01 smQrWalr8aPEPGkXWYDjMsBZ4rHQ00z+cE3YiXJXMj2Y8JMY9LJrR1asaEY3IoBx\\\\r\\\\n2026-04-26 12:36:01 ose+UxmIsZr1OD/Jy1euBJo0IQX3gnrvdGl9u8zQeCes+g5xl68gAU8n1J/Z4DoB\\\\r\\\\n2026-04-26 12:36:01 Y0mUMEgOuMu6aAvmQc/lqqP7lwrCKCfVe6SS6w2w3I9GrL2/3GkQkXJSc4rmZb7u\\\\r\\\\n2026-04-26 12:36:01 JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": \"mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12\",\n \"variable_start\": 113,\n \"variable_end\": 150,\n \"value\": \"36:01\",\n \"value_start\": 151,\n \"value_end\": 156,\n \"entropy\": 2.32193\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 gx1/q1EgS5w2ciAuC8u5gitd1ie43B5lsysO0MY31Qy1eGO1Sj0g4pxM2szbpwso\\\\r\\\\n2026-04-26 12:36:01 0RZL8aKk645hElitcXDx8wUVc0Zm/Av4FsSiZkhFeKaHSAXJtTtlAkLMMTZaNwBA\\\\r\\\\n2026-04-26 12:36:01 hqmHqqtalptZmwGz2F0dmXF9cy+gOxzaBhQbVcH8SDdchpgTl14B93qh2iY2RjxY\\\\r\\\\n2026-04-26 12:36:01 Eb3kpsPG0cdLTAAahEALuMu26YFpglJXAkwSwSLPYsGRPHjJFiXfWBR05x5y5wdB\\\\r\\\\n2026-04-26 12:36:01 1jhhqlV6ZHO/osEJKb6tSHH0mYf0uMNu2speu2DgsjCjHHJwtSJMayfO1WZcSF+G\\\\r\\\\n2026-04-26 12:36:01 wFXOY77MgB3VwMRcCoTMNwoBswcJeZRyNL+cHLZZcK0kpEJbBY60W5pHUceKrDDJ\\\\r\\\\n2026-04-26 12:36:01 sr63qzPaUVNj0Vu2zFG8sEEMES55/JIKCoj6O66j821/qJ97RLPP5pKUpp2gCS7F\\\\r\\\\n2026-04-26 12:36:01 GyCzMBiTsF4zNCr+FA1rQUCZqa50S3Gu90KANsv7VX1krJXXaSXQFaiDAyB+zL0f\\\\r\\\\n2026-04-26 12:36:01 SQR7WrimYwMQaGX8c75+8L7NK2zdxMQH0chtdqv79WmoOn+fWGupCq7NlA32s7rb\\\\r\\\\n2026-04-26 12:36:01 Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 Kqmr2XMicIWCxQoiW4YT5UYfNsfwmRUWkJwmCahUFSzo5swUpBbeCo6bsEdkyxMM\\\\r\\\\n2026-04-26 12:36:01 I5bNV1cjSII5liHOyxnvZ77+giZAKglsiI3ZmmVh+l8fvDBDaLVmmMRfcwRHOxu1\\\\r\\\\n2026-04-26 12:36:01 UMRr047T8ggKgEnyhQLK/FJh+Yp8ubo6wsTUwyyVcRULUVWeJbka6EDkMbPucHHb\\\\r\\\\n2026-04-26 12:36:01 vDdO61eP2yB+uQlwbBr1UquiQD1XrBHXFVwDw6rJoJxTkGQggaofpsUPa3F561LV\\\\r\\\\n2026-04-26 12:36:01 aQAFxU9BAgmdYb4uJxtlt46DCbx2tFW2OnoqQrpFW7nWlwmLJ2dUhIRkySTyhJpq\\\\r\\\\n2026-04-26 12:36:01 K0hnrLThhA1tu8q3dTXOCDs+8csKnI9vVSqAFm6ax3lI6ilBFVIgyZi7dBI1TCKp\\\\r\\\\n2026-04-26 12:36:01 rDbvCzcWY6dxEUzHqTELG5sd955LQgoei2/86QDquRIgB2PGqblBYylUOA9tBTAv\\\\r\\\\n2026-04-26 12:36:01 wSVKoZuonI4ijDZz5yec2C9DiCZva6MbxASOLBl05qfeeDbzkhOWsas2ZpMRmaS8\\\\r\\\\n2026-04-26 12:36:01 dI0Tmp732GkddM2R879ULHp0x4CI4Vh42mN/m22OInwW4mlPaUAy4MQUOWvuWb6/\\\\r\\\\n2026-04-26 12:36:01 o2/HcXJCoj9JsULCKXchFrawJHTgCTpi9BicMpmnPHpnpxlYRw77p4qWcmGqs2Yi\\\\r\\\\n2026-04-26 12:36:01 gQLAAQhZxzpT8MPgsomgC2nySQthEHsvF4XVbL60ImBv9Qig2hd7Jh4cI0D/+TdC\\\\r\\\\n2026-04-26 12:36:01 tky6B1MyPAxYCTN2QXXCo6CbdzMoVBhXuAI7prv2DA5zUwNCpxBKs2BgSIZ9677J\\\\r\\\\n2026-04-26 12:36:01 RlxpsqbbVLVJl6BdbJcMRjIWEW0flKwbSb/PdEuEGheu5UuRZ4/MxrzrciW35CxX\\\\r\\\\n2026-04-26 12:36:01 +XYlHBLCOQ6MCCSYtAy9olSBxQ1iMkiP0V20Crzm6JapZWxTC1EEFgMXAJERMXin\\\\r\\\\n2026-04-26 12:36:01 NiY0wK8f8JFABRBxMZeHyBtT6EobR2Q1Ozcjmhb98rK6wUVhorCGV0mbZ4jzVFtH\\\\r\\\\n2026-04-26 12:36:01 YD9UoTAQrI22NGLy+BupkM7OmaQ82SWZlZ8eiSqv5z7aBI8AAWOORHCYW07i9kCy\\\\r\\\\n2026-04-26 12:36:01 OJ4nB3/Ko4OTiUeGYamtlj9/k7alhM5BE2fkEoygYFvL1cfFXMHH+wOEonSMi5qo\\\\r\\\\n2026-04-26 12:36:01 smQrWalr8aPEPGkXWYDjMsBZ4rHQ00z+cE3YiXJXMj2Y8JMY9LJrR1asaEY3IoBx\\\\r\\\\n2026-04-26 12:36:01 ose+UxmIsZr1OD/Jy1euBJo0IQX3gnrvdGl9u8zQeCes+g5xl68gAU8n1J/Z4DoB\\\\r\\\\n2026-04-26 12:36:01 Y0mUMEgOuMu6aAvmQc/lqqP7lwrCKCfVe6SS6w2w3I9GrL2/3GkQkXJSc4rmZb7u\\\\r\\\\n2026-04-26 12:36:01 JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": \"KEY-----\\\\r\\\\n2026-04-26 12\",\n \"variable_start\": 176,\n \"variable_end\": 201,\n \"value\": \"36:01\",\n \"value_start\": 202,\n \"value_end\": 207,\n \"entropy\": 2.32193\n }\n ]\n },\n {\n \"rule\": \"BASE64 Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 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]\n },\n {\n \"rule\": \"Auth\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AUTH_SECRET_NONCE = \\\\\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sample.py\",\n \"info\": \"\",\n \"variable\": \"AUTH_SECRET_NONCE\",\n \"variable_start\": 0,\n \"variable_end\": 17,\n \"value\": \"\",\n \"value_start\": 20,\n \"value_end\": 20,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AUTH_SECRET_NONCE = \\\\\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sample.py\",\n \"info\": \"\",\n \"variable\": \"AUTH_SECRET_NONCE\",\n \"variable_start\": 0,\n \"variable_end\": 17,\n \"value\": \"\",\n \"value_start\": 20,\n \"value_end\": 20,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"PASSWORD = \\\\\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/sample.py\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"\",\n \"value_start\": 11,\n \"value_end\": 11,\n \"entropy\": 0.0\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SECRET = os.getenv( #\",\n \"line_num\": 29,\n \"path\": \"./tests/samples/sample.py\",\n \"info\": \"\",\n \"variable\": \"SECRET\",\n \"variable_start\": 0,\n \"variable_end\": 6,\n \"value\": \"os.getenv(\",\n \"value_start\": 9,\n \"value_end\": 19,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"X_Auth_Tokens = [\",\n \"line_num\": 33,\n \"path\": 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\"ALTER ROLE postgres PASSWORD 'SqLpa5sW0rD'; SELECT pg_reload_conf()\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER ROLE postgres PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 28,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 30,\n \"value_end\": 41,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE LOGIN username WITH PASSWORD =\",\n \"variable_start\": 0,\n \"variable_end\": 37,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER chuck WITH PASSWORD 'SqLpa5sW0rD' SUPERUSER;\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER chuck WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 31,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 33,\n \"value_end\": 44,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD 'SqLpa5sW0rD' NOSUPERUSER;\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 45,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 47,\n \"value_end\": 58,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER myuser WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER myuser WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 32,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER username WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 36,\n \"value_end\": 47,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 17,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 47,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'super_user'@'10.10.10.%' identified by 'SqLpa5sW0rD';\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'super_user'@'10.10.10.%' identified by\",\n \"variable_start\": 0,\n \"variable_end\": 50,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 52,\n \"value_end\": 63,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 48,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 50,\n \"value_end\": 61,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"mysql -u root -pdbadmin -e \\\"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\\\"\\u2013 \",\n \"line_num\": 22,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 28,\n \"variable_end\": 77,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 79,\n \"value_end\": 90,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"-c \\\"CREATE ROLE scram_test login password 'SqLpa5sW0rD'\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE ROLE scram_test login password\",\n \"variable_start\": 4,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 43,\n \"value_end\": 54,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE ROLE app_admin WITH LOGIN PASSWORD SqLpa5sW0rD;\",\n \"line_num\": 24,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE ROLE app_admin WITH LOGIN PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 42,\n \"value_end\": 53,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 42,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 44,\n \"value_end\": 55,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"create role forum_example_graph_demo login password 'SqLpa5sW0rD';\",\n \"line_num\": 26,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"create role forum_example_graph_demo login password\",\n \"variable_start\": 0,\n \"variable_end\": 51,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 53,\n \"value_end\": 64,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"create role forum_example_graph login password 'SqLpa5sW0rD';\",\n \"line_num\": 27,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"create role forum_example_graph login password\",\n \"variable_start\": 0,\n \"variable_end\": 46,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 48,\n \"value_end\": 59,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SET PASSWORD FOR 'username'@'localhost' = PASSWORD('SqLpa5sW0rD');\",\n \"line_num\": 28,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"SET PASSWORD FOR 'username'@'localhost' = PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 50,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 52,\n \"value_end\": 63,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SET PASSWORD FOR 'username'@'localhost' = PASSWORD('SqLpa5sW0rD');\",\n \"line_num\": 28,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"PASSWORD FOR\",\n \"variable_start\": 4,\n \"variable_end\": 16,\n \"value\": \"username\",\n \"value_start\": 18,\n \"value_end\": 26,\n \"entropy\": 2.75\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"insert into mysql.user values(PASSWORD('SqLpa5sW0rD') );\",\n \"line_num\": 29,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"insert into mysql.user values(PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 38,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 40,\n \"value_end\": 51,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Auth\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"UPDATE mysql.user SET authentication_string = PASSWORD ('SqLpa5sW0rD') WHERE User = 'username';\",\n \"line_num\": 30,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"authentication_string\",\n \"variable_start\": 22,\n \"variable_end\": 43,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 57,\n \"value_end\": 68,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"UPDATE mysql.user SET authentication_string = PASSWORD ('SqLpa5sW0rD') WHERE User = 'username';\",\n \"line_num\": 30,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"UPDATE mysql.user SET authentication_string = PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 54,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 57,\n \"value_end\": 68,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'test'@'1.1.1.1' IDENTIFIED WITH 'mysql_native_password' AS '*92FD05ADCA2EC9D1E10C096DEB1618BC2470E409' REQUIRE NONE PASSWORD EXPIRE DEFAULT ACCOUNT UNLOCK; -- old MySQL hash scheme with sha1\",\n \"line_num\": 31,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'test'@'1.1.1.1' IDENTIFIED WITH 'mysql_native_password' AS\",\n \"variable_start\": 0,\n \"variable_end\": 70,\n \"value\": \"*92FD05ADCA2EC9D1E10C096DEB1618BC2470E409\",\n \"value_start\": 72,\n \"value_end\": 113,\n \"entropy\": 3.78769\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sh -c 'echo CREATE USER typeorm_mg IDENTIFIED BY SqLpa5sW0rD\\\\; >>tmp.sql;'\",\n \"line_num\": 32,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER typeorm_mg IDENTIFIED BY\",\n \"variable_start\": 12,\n \"variable_end\": 48,\n \"value\": \"SqLpa5sW0rD\\\\;\",\n \"value_start\": 49,\n \"value_end\": 62,\n \"entropy\": 3.70044\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'super_user'@'10.10.%' PASSWORD EXPIRE INTERVAL 90 DAY;\",\n \"line_num\": 34,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'super_user'@'10.10.%' PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 42,\n \"value\": \"EXPIRE\",\n \"value_start\": 43,\n \"value_end\": 49,\n \"entropy\": 2.25163\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'super_user'@'10.1.%' PASSWORD HISTORY 1;\",\n \"line_num\": 35,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'super_user'@'10.1.%' PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 41,\n \"value\": \"HISTORY\",\n \"value_start\": 42,\n \"value_end\": 49,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'username'@'%' PASSWORD EXPIRE INTERVAL 90 DAY;\",\n \"line_num\": 36,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'username'@'%' PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"EXPIRE\",\n \"value_start\": 35,\n \"value_end\": 41,\n \"entropy\": 2.25163\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"alter user \\\"bob\\\"@\\\"localhost\\\" identified with sha256_password by '';\",\n \"line_num\": 38,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"alter user \\\"bob\\\"@\\\"localhost\\\" identified with sha256_password by\",\n \"variable_start\": 0,\n \"variable_end\": 63,\n \"value\": \"\",\n \"value_start\": 65,\n \"value_end\": 81,\n \"entropy\": 3.625\n }\n ]\n },\n {\n \"rule\": \"Square Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \\\"SQT\\\": \\\"EAAAEEPtuW9FnP_CuCV-3DFPB54M7YWBUVEFOWKPRVMWEJYMODIDAEX4FASS64NF\\\",\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/square_access_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"EAAAEEPtuW9FnP_CuCV-3DFPB54M7YWBUVEFOWKPRVMWEJYMODIDAEX4FASS64NF\",\n \"value_start\": 12,\n \"value_end\": 76,\n \"entropy\": 4.66018\n }\n ]\n },\n {\n \"rule\": \"Square Credentials\",\n \"severity\": \"medium\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sq0atp-GIREOGICR0CKLE12W45A78\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/square_client_id\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": 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null,\n \"line_data_list\": [\n {\n \"line\": \"tgp_v1_LRvIfXDN2VjuqCi5zcGzrMx3oIwIOhhIZxxxxxxxxxx\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/together\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"tgp_v1_LRvIfXDN2VjuqCi5zcGzrMx3oIwIOhhIZxxxxxxxxxx\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 4.56278\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_token = \\\"G1Re06G1BdgNseiJDN21Z094M\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/token.toml\",\n \"info\": \"\",\n \"variable\": \"gi_reo_gi_token\",\n \"variable_start\": 0,\n \"variable_end\": 15,\n \"value\": \"G1Re06G1BdgNseiJDN21Z094M\",\n \"value_start\": 19,\n \"value_end\": 44,\n \"entropy\": 4.13366\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"Token-> DemoToken: Nxs094M3ed2s1Re0F4M3ed2GZ8M= <- for User : demo\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/token.toml\",\n \"info\": \"\",\n \"variable\": \"DemoToken\",\n \"variable_start\": 8,\n \"variable_end\": 17,\n \"value\": \"Nxs094M3ed2s1Re0F4M3ed2GZ8M=\",\n \"value_start\": 19,\n \"value_end\": 47,\n \"entropy\": 4.03915\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"tp_token_value=\\\"b035d48j9X2dfjF0hb9sd8Guf5hWu2ia\\\"\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/token.toml\",\n \"info\": \"\",\n \"variable\": \"tp_token_value\",\n \"variable_start\": 0,\n \"variable_end\": 14,\n \"value\": \"b035d48j9X2dfjF0hb9sd8Guf5hWu2ia\",\n \"value_start\": 16,\n \"value_end\": 48,\n \"entropy\": 4.22641\n }\n ]\n },\n {\n \"rule\": \"Tavily API Key\",\n \"severity\": \"high\",\n 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\"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AC123456E2A108CD72F648B1984C3B5A13\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/twilio_credentials_n\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AC123456E2A108CD72F648B1984C3B5A13\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 3.8366\n }\n ]\n },\n {\n \"rule\": \"Twilio Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SK4D2F64E2A108CD72F648B1984C3B5A13\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/twilio_credentials_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SK4D2F64E2A108CD72F648B1984C3B5A13\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 4.02086\n }\n ]\n },\n {\n \"rule\": \"Twilio Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AC4d2f64e2a108cd72f648b1984c3b5a13\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/twilio_credentials_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AC4d2f64e2a108cd72f648b1984c3b5a13\",\n \"value_start\": 0,\n \"value_end\": 34,\n \"entropy\": 4.02086\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"const connection_url = require('dbconnection://ad%6Din:5WdF4f2jE76a@db-host-local');\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"dbconnection://\",\n \"variable_start\": 32,\n \"variable_end\": 47,\n \"value\": \"5WdF4f2jE76a\",\n \"value_start\": 55,\n \"value_end\": 67,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"Credential\",\n 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16,\n \"value\": \"546DFS64N90P3AW7DX\",\n \"value_start\": 17,\n \"value_end\": 35,\n \"entropy\": 3.83659\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"email_as_login = \\\"smtps://example@gmail.com:FnD83JZs@smtp.gmail.com:465\\\";\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"smtps://\",\n \"variable_start\": 18,\n \"variable_end\": 26,\n \"value\": \"FnD83JZs\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Auth\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"@\\\"otpauth://host/port?set=VNMXQKAZFVOYOJCDNBIYXYIWX2&info=should_not_be_found_even_in_ml_threshold\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": 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\"value_end\": 51,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.966,\n \"line_data_list\": [\n {\n \"line\": \"ID:master,PW:dipPr10Gg!\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr10Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.971,\n \"line_data_list\": [\n {\n \"line\": \"ID:master PW:dipPr11Gg!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr11Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": 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\"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:master,password:dipPr14Gg!\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"dipPr14Gg!\",\n \"value_start\": 19,\n \"value_end\": 29,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.977,\n \"line_data_list\": [\n {\n \"line\": \"ID:master/PW:dipPr15Gg!\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr15Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:master password:dipPr16Gg!\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"dipPr16Gg!\",\n \"value_start\": 19,\n \"value_end\": 29,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user:master password:dipPr17Gg!\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 12,\n \"variable_end\": 20,\n \"value\": \"dipPr17Gg!\",\n \"value_start\": 21,\n \"value_end\": 31,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"username:master,password:dipPr19Gg!\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 16,\n \"variable_end\": 24,\n \"value\": \"dipPr19Gg!\",\n \"value_start\": 25,\n \"value_end\": 35,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.986,\n \"line_data_list\": [\n {\n \"line\": \"username:master pwd:dipPr110Gg!\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"pwd\",\n \"variable_start\": 16,\n \"variable_end\": 19,\n \"value\": \"dipPr110Gg!\",\n \"value_start\": 20,\n \"value_end\": 31,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.987,\n \"line_data_list\": [\n {\n \"line\": \"ANYid:master,password:dipPr111Gg!\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 13,\n \"variable_end\": 21,\n \"value\": \"dipPr111Gg!\",\n \"value_start\": 22,\n \"value_end\": 33,\n \"entropy\": 3.02717\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.965,\n \"line_data_list\": [\n {\n \"line\": \"ID:master PWD:dipPr112Gg!\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PWD\",\n \"variable_start\": 10,\n \"variable_end\": 13,\n \"value\": \"dipPr112Gg!\",\n \"value_start\": 14,\n \"value_end\": 25,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user id:master password:dipPr113Gg!\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 15,\n \"variable_end\": 23,\n \"value\": \"dipPr113Gg!\",\n \"value_start\": 24,\n \"value_end\": 35,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user:master,password:dipPr114Gg!\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 12,\n \"variable_end\": 20,\n \"value\": \"dipPr114Gg!\",\n \"value_start\": 21,\n \"value_end\": 32,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user=master,password=dipPr115Gg!\",\n \"line_num\": 16,\n \"path\": 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]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.05602\n }\n ]\n },\n {\n \"rule\": \"MailChimp API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"mailchimp = \\\"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailchimp_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\",\n \"value_start\": 13,\n \"value_end\": 50,\n \"entropy\": 4.75662\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.91661\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 3.85669\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Netlify Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/netlify\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"value_start\": 0,\n \"value_end\": 40,\n \"entropy\": 4.61531\n }\n ]\n },\n {\n \"rule\": \"NKEY Seed\",\n \"severity\": \"high\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"// SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/nkey_seed\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"value_start\": 3,\n \"value_end\": 61,\n \"entropy\": 4.55826\n }\n ]\n },\n {\n \"rule\": \"Nonce\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"nonce = 'bsfcvir57nt40rydvtbhs8lzbgljmet5'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"nonce\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"bsfcvir57nt40rydvtbhs8lzbgljmet5\",\n \"value_start\": 9,\n \"value_end\": 41,\n \"entropy\": 4.39032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password: F1lT3ReDw17hQoT3s\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"F1lT3ReDw17hQoT3s\",\n \"value_start\": 10,\n \"value_end\": 27,\n \"entropy\": 3.73452\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_wrap = 'KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\\\\\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"key_wrap\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\",\n \"value_start\": 12,\n \"value_end\": 44,\n \"entropy\": 4.11673\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_multi = '''KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"key_multi\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"value_start\": 15,\n \"value_end\": 45,\n \"entropy\": 4.12323\n }\n ]\n },\n {\n \"rule\": \"Notion Integration Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/notion\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 5.06876\n }\n ]\n },\n {\n \"rule\": \"NPM Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"positive: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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/npm\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 9,\n \"value_end\": 49,\n \"entropy\": 4.80306\n }\n ]\n },\n {\n \"rule\": \"NTLM Token\",\n \"severity\": \"medium\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"Positive: TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/ntlm\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=\",\n \"value_start\": 10,\n \"value_end\": 190,\n \"entropy\": 3.79713\n }\n ]\n },\n {\n \"rule\": \"NuGet API key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"k = 'oy2mlf2v7jl2firuegfqwzc4zxyebz3ethzd14g4hw4iam'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nuget_api_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"oy2mlf2v7jl2firuegfqwzc4zxyebz3ethzd14g4hw4iam\",\n \"value_start\": 5,\n \"value_end\": 51,\n \"entropy\": 4.56129\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 51,\n \"entropy\": 5.22625\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 5.25816\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 4.12555\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"WXFES7QNTET5DQYC\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"WXFES7QNTET5DQYC\",\n \"value_start\": 0,\n \"value_end\": 16,\n \"entropy\": 3.625\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.14032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.0,\n \"line_data_list\": [\n {\n \"line\": \"password_id = 2938479\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/pass_filtered\",\n \"info\": \"\",\n \"variable\": \"password_id\",\n \"variable_start\": 0,\n \"variable_end\": 11,\n \"value\": \"2938479\",\n \"value_start\": 14,\n \"value_end\": 21,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.99,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"gi_reo_gi_passwd\",\n \"variable_start\": 0,\n \"variable_end\": 16,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 20,\n \"value_end\": 30,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"password_confirmation\",\n \"variable_start\": 33,\n \"variable_end\": 54,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 58,\n \"value_end\": 68,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"cackle!\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.gradle\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"MYPSWRD!@#$%^&*\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.tfvars\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"MYPSWRD!@#$%^&*\",\n \"value_start\": 12,\n \"value_end\": 27,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.996,\n \"line_data_list\": [\n {\n \"line\": \"MYSQLPASS: Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQLPASS\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"value_start\": 11,\n \"value_end\": 37,\n \"entropy\": 3.8693\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"my_pw: nCzx8A8#!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"my_pw\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 7,\n \"value_end\": 16,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"val password: String = \\\"exord13Paw64\\\", // scala\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"exord13Paw64\",\n \"value_start\": 24,\n \"value_end\": 36,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"def connect(passwd: str = \\\"cq2tPr1a2\\\"): # python default arg\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passwd\",\n \"variable_start\": 12,\n \"variable_end\": 18,\n \"value\": \"cq2tPr1a2\",\n \"value_start\": 27,\n \"value_end\": 36,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd == \\\"q4c1a2oPd\\\": # __eq__ separator\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"q4c1a2oPd\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd != \\\"x6s7djtEa\\\": # __ne__ separator\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"x6s7djtEa\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password=2bkJgtJDiLcq1t\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"2bkJgtJDiLcq1t\",\n \"value_start\": 9,\n \"value_end\": 23,\n \"entropy\": 3.52164\n }\n ]\n },\n {\n \"rule\": \"CMD Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passin\",\n \"variable_start\": 33,\n \"variable_end\": 39,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 41,\n \"variable_end\": 45,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"MYSQL_DATABASE_USER=CRED;MYSQL_DATABASE_PASSWORD=2IWJD88FH4Y;\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQL_DATABASE_PASSWORD\",\n \"variable_start\": 25,\n \"variable_end\": 48,\n \"value\": \"2IWJD88FH4Y\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"#define password \\\"n84ASM54y4\\\"\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.065,\n \"line_data_list\": [\n {\n \"line\": \"#define password {0x48, 0x65, 0x6C, 0x6C, 0x30}\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"0x48, 0x65, 0x6C, 0x6C, 0x30\",\n \"value_start\": 18,\n \"value_end\": 46,\n \"entropy\": 3.02613\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"%define PASSWORD \\\"n84ASM54y4\\\"\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"%global PASSWORD \\\"n84RPM54y4\\\"\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84RPM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"SET password \\\"n83.bat47Fy4\\\"\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"n83.bat47Fy4\",\n \"value_start\": 14,\n \"value_end\": 26,\n \"entropy\": 3.4183\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"\\\"#define\\\\tpassword\\\\t\\\\\\\"n84ASM54y4\\\\\\\"\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 22,\n \"value_end\": 32,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.991,\n \"line_data_list\": [\n {\n \"line\": \"WPA2_PASSWORD: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"WPA2_PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 13,\n \"value\": \"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"value_start\": 15,\n \"value_end\": 79,\n \"entropy\": 3.67082\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/password_utf16.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.914,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajc\\u00f61\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password_western.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajc\\u00f61\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"PayPal Braintree Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"access_token$production$gireogi121451781$abcaeaabadef01134517891121451781\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/paypal_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"access_token$production$gireogi121451781$abcaeaabadef01134517891121451781\",\n \"value_start\": 0,\n \"value_end\": 73,\n \"entropy\": 4.39985\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"str value = \\\"-----BEGIN RSA PRIVATE KEY-----\\\\n\\\" +\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN RSA PRIVATE KEY-----\",\n \"value_start\": 13,\n \"value_end\": 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\"ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\",\n \"value_start\": 20,\n \"value_end\": 84,\n \"entropy\": 4.99173\n },\n {\n \"line\": \"2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\",\n \"line_num\": 69,\n \"path\": \"./tests/samples/pem_key.p.log\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\",\n \"value_start\": 20,\n \"value_end\": 84,\n \"entropy\": 5.24586\n },\n {\n \"line\": \"2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\",\n \"line_num\": 70,\n \"path\": \"./tests/samples/pem_key.p.log\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\",\n \"value_start\": 20,\n \"value_end\": 84,\n \"entropy\": 5.21048\n },\n {\n \"line\": \"2026-04-26 12:36:01 qwI=\",\n \"line_num\": 71,\n \"path\": \"./tests/samples/pem_key.p.log\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"qwI=\",\n \"value_start\": 20,\n \"value_end\": 24,\n \"entropy\": 2.0\n },\n {\n \"line\": \"2026-04-26 12:36:01 -----END PRIVATE KEY-----\",\n \"line_num\": 72,\n \"path\": \"./tests/samples/pem_key.p.log\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----END PRIVATE KEY-----\",\n \"value_start\": 20,\n \"value_end\": 45,\n \"entropy\": 3.04489\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 t51bOzjJlLIlUEQicJcXMCrBJ8pL1bHJGkT7t7gxnC72Qz7D2Czh20oJIgFTs1yJ\\\\r\\\\n2026-04-26 12:36:01 kQSTxDFcMsakyRRZAAcDyGMGUnrMxIVSyrQDhIQrORaeiTDHcaS6pDuz5kkJsT+Y\\\\r\\\\n2026-04-26 12:36:01 ki/ZkkAldBpX4sDD1zvC6LyWU1IlZcx9F5V7I0P/BrpSwrvjNQEIeW4tNR1+fEYW\\\\r\\\\n2026-04-26 12:36:01 fE7gewlJZbTCVqTcQ7wQ+kA7JEQkU6I8YaIXuiwiG55EuSsO2MzpApgFtmAcWlT4\\\\r\\\\n2026-04-26 12:36:01 ybWzhp7kqwRFolOi6hb9y8y4aDRkRltYcTPswcjh40k1spoCRlwCcgahgTnuWJ8O\\\\r\\\\n2026-04-26 12:36:01 qq4uxkY8xkFvJ4VqZjcl7AbhdJg3R5gqlbhPZmEXBn3teYbihzMCBRI3RTI5/Hy2\\\\r\\\\n2026-04-26 12:36:01 Yh4VhW+MqaukgRTPk50aKFjEs0vj6D1RpLRUmq/EI2GKZbtZc4MDR8kZWXsP5yqO\\\\r\\\\n2026-04-26 12:36:01 o2OcG66cSXR5KrzmNRNdci1GNafm5qHiqj5NsnDax1B8t1hkpV+VMkZKGxGXt2YP\\\\r\\\\n2026-04-26 12:36:01 gx1/q1EgS5w2ciAuC8u5gitd1ie43B5lsysO0MY31Qy1eGO1Sj0g4pxM2szbpwso\\\\r\\\\n2026-04-26 12:36:01 0RZL8aKk645hElitcXDx8wUVc0Zm/Av4FsSiZkhFeKaHSAXJtTtlAkLMMTZaNwBA\\\\r\\\\n2026-04-26 12:36:01 hqmHqqtalptZmwGz2F0dmXF9cy+gOxzaBhQbVcH8SDdchpgTl14B93qh2iY2RjxY\\\\r\\\\n2026-04-26 12:36:01 Eb3kpsPG0cdLTAAahEALuMu26YFpglJXAkwSwSLPYsGRPHjJFiXfWBR05x5y5wdB\\\\r\\\\n2026-04-26 12:36:01 1jhhqlV6ZHO/osEJKb6tSHH0mYf0uMNu2speu2DgsjCjHHJwtSJMayfO1WZcSF+G\\\\r\\\\n2026-04-26 12:36:01 wFXOY77MgB3VwMRcCoTMNwoBswcJeZRyNL+cHLZZcK0kpEJbBY60W5pHUceKrDDJ\\\\r\\\\n2026-04-26 12:36:01 sr63qzPaUVNj0Vu2zFG8sEEMES55/JIKCoj6O66j821/qJ97RLPP5pKUpp2gCS7F\\\\r\\\\n2026-04-26 12:36:01 GyCzMBiTsF4zNCr+FA1rQUCZqa50S3Gu90KANsv7VX1krJXXaSXQFaiDAyB+zL0f\\\\r\\\\n2026-04-26 12:36:01 SQR7WrimYwMQaGX8c75+8L7NK2zdxMQH0chtdqv79WmoOn+fWGupCq7NlA32s7rb\\\\r\\\\n2026-04-26 12:36:01 Cq4auSoIF5ovQqw2F2wgi2nBpHwfF5ka6qSaQA4wiACrxkC255lCaAzy9jky4Ldt\\\\r\\\\n2026-04-26 12:36:01 1iSmA7q2JSu8HEN8NG9AQqP+l44HRXFzJsF3cXTaOzKZKYlhlx5btb8F+M9aCgXi\\\\r\\\\n2026-04-26 12:36:01 pICqo0FqkQ03ULwswnF8yXsjpYkx63lc0pLStKn7dxI+cSOYYCu0cbxcBoZyqmH1\\\\r\\\\n2026-04-26 12:36:01 Kqmr2XMicIWCxQoiW4YT5UYfNsfwmRUWkJwmCahUFSzo5swUpBbeCo6bsEdkyxMM\\\\r\\\\n2026-04-26 12:36:01 I5bNV1cjSII5liHOyxnvZ77+giZAKglsiI3ZmmVh+l8fvDBDaLVmmMRfcwRHOxu1\\\\r\\\\n2026-04-26 12:36:01 UMRr047T8ggKgEnyhQLK/FJh+Yp8ubo6wsTUwyyVcRULUVWeJbka6EDkMbPucHHb\\\\r\\\\n2026-04-26 12:36:01 vDdO61eP2yB+uQlwbBr1UquiQD1XrBHXFVwDw6rJoJxTkGQggaofpsUPa3F561LV\\\\r\\\\n2026-04-26 12:36:01 aQAFxU9BAgmdYb4uJxtlt46DCbx2tFW2OnoqQrpFW7nWlwmLJ2dUhIRkySTyhJpq\\\\r\\\\n2026-04-26 12:36:01 K0hnrLThhA1tu8q3dTXOCDs+8csKnI9vVSqAFm6ax3lI6ilBFVIgyZi7dBI1TCKp\\\\r\\\\n2026-04-26 12:36:01 rDbvCzcWY6dxEUzHqTELG5sd955LQgoei2/86QDquRIgB2PGqblBYylUOA9tBTAv\\\\r\\\\n2026-04-26 12:36:01 wSVKoZuonI4ijDZz5yec2C9DiCZva6MbxASOLBl05qfeeDbzkhOWsas2ZpMRmaS8\\\\r\\\\n2026-04-26 12:36:01 dI0Tmp732GkddM2R879ULHp0x4CI4Vh42mN/m22OInwW4mlPaUAy4MQUOWvuWb6/\\\\r\\\\n2026-04-26 12:36:01 o2/HcXJCoj9JsULCKXchFrawJHTgCTpi9BicMpmnPHpnpxlYRw77p4qWcmGqs2Yi\\\\r\\\\n2026-04-26 12:36:01 gQLAAQhZxzpT8MPgsomgC2nySQthEHsvF4XVbL60ImBv9Qig2hd7Jh4cI0D/+TdC\\\\r\\\\n2026-04-26 12:36:01 tky6B1MyPAxYCTN2QXXCo6CbdzMoVBhXuAI7prv2DA5zUwNCpxBKs2BgSIZ9677J\\\\r\\\\n2026-04-26 12:36:01 RlxpsqbbVLVJl6BdbJcMRjIWEW0flKwbSb/PdEuEGheu5UuRZ4/MxrzrciW35CxX\\\\r\\\\n2026-04-26 12:36:01 +XYlHBLCOQ6MCCSYtAy9olSBxQ1iMkiP0V20Crzm6JapZWxTC1EEFgMXAJERMXin\\\\r\\\\n2026-04-26 12:36:01 NiY0wK8f8JFABRBxMZeHyBtT6EobR2Q1Ozcjmhb98rK6wUVhorCGV0mbZ4jzVFtH\\\\r\\\\n2026-04-26 12:36:01 YD9UoTAQrI22NGLy+BupkM7OmaQ82SWZlZ8eiSqv5z7aBI8AAWOORHCYW07i9kCy\\\\r\\\\n2026-04-26 12:36:01 OJ4nB3/Ko4OTiUeGYamtlj9/k7alhM5BE2fkEoygYFvL1cfFXMHH+wOEonSMi5qo\\\\r\\\\n2026-04-26 12:36:01 smQrWalr8aPEPGkXWYDjMsBZ4rHQ00z+cE3YiXJXMj2Y8JMY9LJrR1asaEY3IoBx\\\\r\\\\n2026-04-26 12:36:01 ose+UxmIsZr1OD/Jy1euBJo0IQX3gnrvdGl9u8zQeCes+g5xl68gAU8n1J/Z4DoB\\\\r\\\\n2026-04-26 12:36:01 Y0mUMEgOuMu6aAvmQc/lqqP7lwrCKCfVe6SS6w2w3I9GrL2/3GkQkXJSc4rmZb7u\\\\r\\\\n2026-04-26 12:36:01 JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 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yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\",\n \"value_start\": 157,\n \"value_end\": 6245,\n \"entropy\": 5.8771\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.0,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 OYyA41Ls/ESNS1UGWwfCuZ89CBzjjBQZhxp4ELW+ZLa+1w3iUhJZEYoc9GQm7E+v\\\\r\\\\n2026-04-26 12:36:01 VIQvl4RxKF8WZAc4uTaisTwcNAhYK5m5gpX5ZHLgBndWRjE32kOvask2BLdgjJig\\\\r\\\\n2026-04-26 12:36:01 Fs9mKlRU+ZqIQxukBDO6xkHjSr1JxIP2HJNyiiZxgCUKSi/I5h4UObW1yjNv0Ymw\\\\r\\\\n2026-04-26 12:36:01 FE/csKq4gcWvPD/QuFeW4XFQcZaoqkQVILnjVG10NqOTlDJaywMhcgjQq2QQlVXH\\\\r\\\\n2026-04-26 12:36:01 zMBgJI3W9qLDYFY69rN/xnL68wg5B1xv62ChNo4eTLlppGmNlLfX6YleXLYK2pTj\\\\r\\\\n2026-04-26 12:36:01 cmIbK3nvQ7BGLAXVMMYFOkkht0mHVC4sS3mwdUtS2l5KECOq1R+g4mrrAUyGpI1B\\\\r\\\\n2026-04-26 12:36:01 68+Eg5DkM86BUYI9N86V4cUtNGDbsmaJgCurGJHHupeJQhWj+Q2CNlXmSaP+mCau\\\\r\\\\n2026-04-26 12:36:01 GUEMVn/PVmqhSJIj+yEsojeZykecYXo7LMxiJkuX8HZ9R3ynOHdedcfV4DdAJc1E\\\\r\\\\n2026-04-26 12:36:01 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JoAFyHleVFAnDFXlhLKFl0h3x7TD26LK2LApnLI344MvE6ZG9RFA6w2Q6JtRIEWU\\\\r\\\\n2026-04-26 12:36:01 lheqsm3z9sfcOiHW/GWw0nTkC8btOFZ0uBTThDnHg0BvuXzmBDcle1GpXJdyzLyl\\\\r\\\\n2026-04-26 12:36:01 cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": \"mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12\",\n \"variable_start\": 113,\n \"variable_end\": 150,\n \"value\": \"36:01\",\n \"value_start\": 151,\n \"value_end\": 156,\n \"entropy\": 2.32193\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.0,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"ML-KEM-1024.log\\\":\\\"\\\\r\\\\n\\\\r\\\\n#7 [4/4] RUN openssl genpkey -algorithm ML-KEM-1024 -out mlkem-privatekey.pem && cat mlkem-privatekey.pem\\\\r\\\\n2026-04-26 12:36:01 -----BEGIN PRIVATE KEY-----\\\\r\\\\n2026-04-26 12:36:01 MIIMvgIBADALBglghkgBZQMEBAMEggyqMIIMpgRATqJGETTwhb2gxXF41z3G5ztP\\\\r\\\\n2026-04-26 12:36:01 I+dcZ5zCOnpcALAIw+OAqVHjisQypIBH6K/pqnrVYzZkwV6M4bLhesOMuserAgSC\\\\r\\\\n2026-04-26 12:36:01 DGAygxLkWHaG9AEmQJsg1MeFxsNyehNphDUdaKHxVmXPYUNVm3J4c5+xBZigd8pa\\\\r\\\\n2026-04-26 12:36:01 LEIX4H6JKVWAwKs5UkCLw3uB434w+6mWMJlUjDwWZSGgEiRjS21nx6eKyLqlLE16\\\\r\\\\n2026-04-26 12:36:01 XAZ5Rg2oJAL5CVj8uAe7pUdweySS4EBgdMPJ9o0cEZDP5aD9yTSIeXzi1bgGJQ/s\\\\r\\\\n2026-04-26 12:36:01 aJ5DxXUVXDWTZgA05CHuojS/R1WlO2o30rxV4azc+Yr7IcR89i4wNGHUNQFmhhBF\\\\r\\\\n2026-04-26 12:36:01 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cW4qlLb15J1zMb/hVBNGagquATVVclvcVKYGYkNsxGpWBC8/8iJTEUKEMwqti7PR\\\\r\\\\n2026-04-26 12:36:01 yh+r058rdhlVML+0F5aDJwjslkCppGpJF5nGQn4pwBzViz752YFUgRRz2jrhFYHE\\\\r\\\\n2026-04-26 12:36:01 KaVCtcczpnZhtqNMY49aRMaTphHu4YpgglMjbDuZ5wiK27Fq5RM+lF6sIG6SGycb\\\\r\\\\n2026-04-26 12:36:01 4whptwXeepJbATEQ55FWWckLVJ5lVWuZ0pCOMguparXRwXECzGnIHLxehCexiZqA\\\\r\\\\n2026-04-26 12:36:01 QLJZNAFOyB3IhHZo5TrJY5sNIMXU94yraZLmQQ3cRMntNiW8kp6Pqj3I40bqlL3F\\\\r\\\\n2026-04-26 12:36:01 ahwNl8qwsjl44hMmWMfQk1c5OpCtkGJcIpIF08ILxDknAyBTQ35BJXMJ9XtI0nt2\\\\r\\\\n2026-04-26 12:36:01 OiGGA6YUqbb68bmXbEhzKQhulHs8GWh/sgXiN3NoI5ns6nU0a3e6Oz2BkXY708iM\\\\r\\\\n2026-04-26 12:36:01 oxrQxsZ4uoM/pjlHG5xeOM62B3tpeghU5iFfOgr+hH9mGcOx4cSoNjn3a5gvMJqc\\\\r\\\\n2026-04-26 12:36:01 Ycc60cOGalwlpLruUy4rdDwhInvsGAmaapDq8IxRpS/AIpij4Y/SmMl9uisvqBr9\\\\r\\\\n2026-04-26 12:36:01 ypg1olTOJ8rk08AXY0Kl2D9lS5GK11g2VWtCgKiMdS/RvAXJnJGkdStVTGYiCnHJ\\\\r\\\\n2026-04-26 12:36:01 OjgyHTrR2a+N2ZiYTldYtmF6H9pm/lfv6FNtw2cNQzqGoSSsrAHEugO0d94keir2\\\\r\\\\n2026-04-26 12:36:01 62w9ymkZWDurfZDVT8OIVWXhgKlR44rEMqSAR+iv6ap61WM2ZMFejOGy4XrDjLrH\\\\r\\\\n2026-04-26 12:36:01 qwI=\\\\r\\\\n2026-04-26 12:36:01 -----END PRIVATE KEY-----\\\\r\\\\n#7 DONE 0.3s\\\\r\\\\n\\\\r\\\\n#8 exporting to image\\\\r\\\\n#8 exporting layers 0.1s done\\\\r\\\\n#8 writing image sha256:3ed48eb4eb0c17e6baaf691a361afd8c75572517e5b729849da4e5344bf7f244 done\\\\r\\\\n#8 DONE 0.2s\\\"}\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.log.json\",\n \"info\": \"\",\n \"variable\": \"KEY-----\\\\r\\\\n2026-04-26 12\",\n \"variable_start\": 176,\n \"variable_end\": 201,\n \"value\": \"36:01\",\n \"value_start\": 202,\n \"value_end\": 207,\n \"entropy\": 2.32193\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"-----BEGIN PRIVATE KEY-----\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/pem_key.p.rsa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN PRIVATE KEY-----\",\n \"value_start\": 0,\n \"value_end\": 27,\n \"entropy\": 3.20029\n },\n {\n \"line\": \"MIIBVQIBADANBgkqhkiG9w0BAQEFAASCAT8wggE7AgEAAkEA12FhURMjPmqRNZZl\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/pem_key.p.rsa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"MIIBVQIBADANBgkqhkiG9w0BAQEFAASCAT8wggE7AgEAAkEA12FhURMjPmqRNZZl\",\n \"value_start\": 0,\n \"value_end\": 64,\n \"entropy\": 4.67611\n },\n {\n \"line\": \"teTEEoNqzPBXPBgBSqihi1qWbk3NthnycOSinUz7prfasLMlEDqcS68FFh1t5rrX\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/pem_key.p.rsa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"teTEEoNqzPBXPBgBSqihi1qWbk3NthnycOSinUz7prfasLMlEDqcS68FFh1t5rrX\",\n \"value_start\": 0,\n 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033, 043, 000, \\\\\",\n \"value_start\": 16,\n \"value_end\": 83,\n \"entropy\": 3.24263\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"TokenRequest\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/sample.html\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 28,\n \"variable_end\": 33,\n \"value\": \"g1re0g1T0keN3zWx\",\n \"value_start\": 40,\n \"value_end\": 56,\n \"entropy\": 3.5\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \" placeholder=\\\"Your password: "g1re0g1Pa5$w0Rd"\\\"\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/sample.html\",\n \"info\": \"\",\n \"variable\": \"Your password\",\n \"variable_start\": 17,\n \"variable_end\": 30,\n \"value\": \"g1re0g1Pa5$w0Rd\",\n \"value_start\": 38,\n \"value_end\": 53,\n \"entropy\": 3.50689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \" \",\n \"line_num\": 21,\n \"path\": \"./tests/samples/sample.html\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 30,\n \"variable_end\": 38,\n \"value\": \"g1re0g2Pa5$w0Rd\",\n \"value_start\": 39,\n \"value_end\": 54,\n \"entropy\": 3.64022\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"81f50f8d-4c1a-de4d-8e3f-c1bc8b429a36}{\\\\loch\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/sample.rtf\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"81f50f8d-4c1a-de4d-8e3f-c1bc8b429a36\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.84286\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.193,\n \"line_data_list\": [\n {\n \"line\": \"%define bld %(if [[ \\\"%{password}\\\" =~ \\\"himmelsrand\\\" ]]; then echo \\\"y\\\"; else echo \\\"n\\\"; fi)\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/sample.spec\",\n \"info\": \"\",\n \"variable\": \"%{password}\",\n \"variable_start\": 21,\n \"variable_end\": 32,\n \"value\": \"himmelsrand\",\n \"value_start\": 38,\n \"value_end\": 49,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"%define token 4b9a6d8b4bc56fbfa1c638eb0c6cab3746bf32ac7bfa89a6d8b638eb0c619ff2\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/sample.spec\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 8,\n \"variable_end\": 13,\n \"value\": 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\"17205d79-dead-beef-a311-26312ad6ea36\",\n \"value_start\": 9,\n \"value_end\": 45,\n \"entropy\": 3.60702\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \" May password:6Ew1ThY0u\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/sample.tm7\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 15,\n \"variable_end\": 23,\n \"value\": \"6Ew1ThY0u\",\n \"value_start\": 24,\n \"value_end\": 33,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Nonce\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \" __NONCE: AQ+n0Tth3F1Lt3ReDe+BrQwTzNcs7y+OFND0M/+ipSM+5xE91lsQWW0j1dxGh4PEJtVN0U1oVAL+ZVEIw0IpBDaQQYqkxkkp/+Aj1lp3UgUtGUyX+/CxXFnoK04XZzdpWxcwYeBUikykI5YUUQVldaoTql4BugUy733PXFK91q4UpPK0Dne5yCRKvpqSLWVgigXbUogfRugfYgTgkiGEPsv3izNgRWycIDUInfvpzVvODk1gz6/1nW7xISgLCdcewkRgO6l0WGuOn2dWcndURMOooj4ljD9Aw7g4eIu5hf/B5sCOYh7fB33QxOlAmiMZoliEo6WWGP7P8hneYli7YnRfvvqx7Yh30E3qokRKQXsT+OuSZgK1kKK5yzroO\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/sealed_secrets.yaml\",\n \"info\": \"\",\n \"variable\": \"__NONCE\",\n \"variable_start\": 4,\n \"variable_end\": 11,\n \"value\": \"AQ+n0Tth3F1Lt3ReDe+BrQwTzNcs7y+OFND0M/+ipSM+5xE91lsQWW0j1dxGh4PEJtVN0U1oVAL+ZVEIw0IpBDaQQYqkxkkp/+Aj1lp3UgUtGUyX+/CxXFnoK04XZzdpWxcwYeBUikykI5YUUQVldaoTql4BugUy733PXFK91q4UpPK0Dne5yCRKvpqSLWVgigXbUogfRugfYgTgkiGEPsv3izNgRWycIDUInfvpzVvODk1gz6/1nW7xISgLCdcewkRgO6l0WGuOn2dWcndURMOooj4ljD9Aw7g4eIu5hf/B5sCOYh7fB33QxOlAmiMZoliEo6WWGP7P8hneYli7YnRfvvqx7Yh30E3qokRKQXsT+OuSZgK1kKK5yzroO\",\n \"value_start\": 13,\n \"value_end\": 394,\n \"entropy\": 5.81513\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.265,\n \"line_data_list\": [\n {\n \"line\": \"if string(secret) == \\\"cackle!\\\" {\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"secret)\",\n \"variable_start\": 10,\n \"variable_end\": 17,\n \"value\": \"cackle!\",\n \"value_start\": 22,\n \"value_end\": 29,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \" Secret: []byte{333, 9, 100, 114, 245, 164, 134, 217,225,26,0, 172, 39, 248, 203, 201},\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"Secret\",\n \"variable_start\": 8,\n \"variable_end\": 14,\n \"value\": \"333, 9, 100, 114, 245, 164, 134, 217,225,26,0, 172, 39, 248, 203, 201\",\n \"value_start\": 23,\n \"value_end\": 99,\n \"entropy\": 3.10882\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var SECRET = `-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 14,\n \"value_end\": 49,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.18903\n },\n {\n \"line\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OQAAABWHkoN5N0V0OCSXOHWSOHAxRYMJSGc4clgVA0gJgFlIBAAAAJimRM7VpkTO1QAAAAtzc2gt\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.74471\n },\n {\n \"line\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ZWQyNTUxOQAAACBqIPMG94HL7zedFzsvi45mHS8ZuyLQXqvHpHobcdNCJAAAAFRoZXJlXzE1LU4w\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 5.24555\n },\n {\n \"line\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"dF9UaGVLZXlZb3VBcmVMb29raW5nRm9S8wb3Mj0tZT1hc3A7ZHprejsuZm5tbmRmbmVuZm5pAAAA\",\n \"value_start\": 0,\n \"value_end\": 76,\n \"entropy\": 4.94996\n },\n {\n \"line\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"EXRpemVuQGNyZWRzd2VlcGVyAQIDBA==\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.47641\n },\n {\n \"line\": \"-----END OPENSSH PRIVATE KEY-----\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----END OPENSSH PRIVATE KEY-----\",\n \"value_start\": 0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"var secret_looks_like_linux_path_1=\\\"/VnpmUGWxhQW9KQAwrL2ZYdDJPNG1PQjYxMXNPaF\\\"\",\n \"line_num\": 17,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"secret_looks_like_linux_path_1\",\n \"variable_start\": 4,\n \"variable_end\": 34,\n \"value\": \"/VnpmUGWxhQW9KQAwrL2ZYdDJPNG1PQjYxMXNPaF\",\n \"value_start\": 36,\n \"value_end\": 76,\n \"entropy\": 4.83418\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"var secret_looks_like_linux_path_2=\\\"VnpmUGWxhQW/9KQAwrL2ZYd/DJPNG1PQjYxMXNPF\\\"\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"secret_looks_like_linux_path_2\",\n \"variable_start\": 4,\n \"variable_end\": 34,\n \"value\": \"VnpmUGWxhQW/9KQAwrL2ZYd/DJPNG1PQjYxMXNPF\",\n \"value_start\": 36,\n \"value_end\": 76,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"var secret_looks_like_linux_path_3=\\\"VnpmUGWxhQW/9KQAwrL2ZYdDJPNG1PQjYxMXNPF=\\\"\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"secret_looks_like_linux_path_3\",\n \"variable_start\": 4,\n \"variable_end\": 34,\n \"value\": \"VnpmUGWxhQW/9KQAwrL2ZYdDJPNG1PQjYxMXNPF=\",\n \"value_start\": 36,\n \"value_end\": 76,\n \"entropy\": 4.83418\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"var secret_looks_like_linux_path__=\\\"VnpmUGWxhQW/9KQAwrL2ZYd/DJPNG1PQjEXAMbLE\\\"\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/secret.go\",\n \"info\": \"\",\n \"variable\": \"secret_looks_like_linux_path__\",\n \"variable_start\": 4,\n \"variable_end\": 34,\n \"value\": \"VnpmUGWxhQW/9KQAwrL2ZYd/DJPNG1PQjEXAMbLE\",\n \"value_start\": 36,\n \"value_end\": 76,\n \"entropy\": 4.85306\n }\n ]\n },\n {\n \"rule\": \"Secret\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"LEGACY_GITHUB_SECRET = \\\"fa87409ad3a4589fd279c501b3d2e174855ee9f4\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/secret.groovy\",\n \"info\": \"\",\n \"variable\": \"LEGACY_GITHUB_SECRET\",\n \"variable_start\": 0,\n \"variable_end\": 20,\n \"value\": \"fa87409ad3a4589fd279c501b3d2e174855ee9f4\",\n \"value_start\": 24,\n \"value_end\": 64,\n \"entropy\": 3.80869\n }\n ]\n },\n {\n \"rule\": \"SendGrid API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"SG.gireogigireogigi.gireogigireogigi\",\n \"line_num\": 1,\n \"path\": 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\"value_end\": 179,\n \"entropy\": 5.53873\n }\n ]\n },\n {\n \"rule\": \"Sentry User Auth Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/sentry\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 71,\n \"entropy\": 4.14384\n }\n ]\n },\n {\n \"rule\": \"Shopify Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \\\"shopyfy_k\\\": \\\"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\\\",\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/shopify_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n 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\"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER ExposedTest ACCOUNT UNLOCK IDENTIFIED BY\",\n \"variable_start\": 6,\n \"variable_end\": 58,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 59,\n \"value_end\": 70,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.041,\n \"line_data_list\": [\n {\n \"line\": \"expected_statement = \\\"\\\"\\\"CREATE USER foo WITH ENCRYPTED PASSWORD 'SqLpa5sW0rD' CREATEDB;\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER foo WITH ENCRYPTED PASSWORD\",\n \"variable_start\": 24,\n \"variable_end\": 63,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 65,\n \"value_end\": 76,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.914,\n \"line_data_list\": [\n {\n 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\"confidence\": \"weak\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE LOGIN username WITH PASSWORD =\",\n \"variable_start\": 0,\n \"variable_end\": 37,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER chuck WITH PASSWORD 'SqLpa5sW0rD' SUPERUSER;\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER chuck WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 31,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 33,\n \"value_end\": 44,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD 'SqLpa5sW0rD' NOSUPERUSER;\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 45,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 47,\n \"value_end\": 58,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER myuser WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER myuser WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 32,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n 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\"SqLpa5sW0rD\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.553,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'super_user'@'10.10.10.%' identified by 'SqLpa5sW0rD';\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'super_user'@'10.10.10.%' identified by\",\n \"variable_start\": 0,\n \"variable_end\": 50,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 52,\n \"value_end\": 63,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.899,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.991,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 48,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 50,\n \"value_end\": 61,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"mysql -u root -pdbadmin -e \\\"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\\\"\\u2013 \",\n \"line_num\": 22,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 28,\n \"variable_end\": 77,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 79,\n \"value_end\": 90,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"-c \\\"CREATE ROLE scram_test login 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[\n {\n \"line\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE ROLE flask_admin_geo LOGIN PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 42,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 44,\n \"value_end\": 55,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.702,\n \"line_data_list\": [\n {\n \"line\": \"create role forum_example_graph_demo login password 'SqLpa5sW0rD';\",\n \"line_num\": 26,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"create role forum_example_graph_demo login password\",\n \"variable_start\": 0,\n \"variable_end\": 51,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 53,\n \"value_end\": 64,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n 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\"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"Credential\",\n \"variable_start\": 38,\n \"variable_end\": 48,\n \"value\": \"546DFS64N90P3AW7DX%2Fkeep%26cut\",\n \"value_start\": 49,\n \"value_end\": 80,\n \"entropy\": 4.41372\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.006,\n \"line_data_list\": [\n {\n \"line\": \"// \\\"fp://no.host.real/any/path/to/nowhere/\\\",\\\"key\\\":\\\"f45VgF8jX79o@anydata.com\\\"\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"key\",\n \"variable_start\": 45,\n \"variable_end\": 48,\n \"value\": \"f45VgF8jX79o@anydata.com\",\n \"value_start\": 51,\n \"value_end\": 75,\n \"entropy\": 4.30351\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"39084?Credential=546DFS64N90P3AW7DX&key=3487263-2384579834-234732875-345&hasToBefound=2\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"key\",\n \"variable_start\": 36,\n \"variable_end\": 39,\n \"value\": \"3487263-2384579834-234732875-345\",\n \"value_start\": 40,\n \"value_end\": 72,\n \"entropy\": 2.97591\n }\n ]\n },\n {\n \"rule\": \"Credential\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"39084?Credential=546DFS64N90P3AW7DX&key=3487263-2384579834-234732875-345&hasToBefound=2\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"Credential\",\n \"variable_start\": 6,\n \"variable_end\": 16,\n \"value\": \"546DFS64N90P3AW7DX\",\n \"value_start\": 17,\n \"value_end\": 35,\n \"entropy\": 3.83659\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"email_as_login = \\\"smtps://example@gmail.com:FnD83JZs@smtp.gmail.com:465\\\";\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"smtps://\",\n \"variable_start\": 18,\n \"variable_end\": 26,\n \"value\": \"FnD83JZs\",\n \"value_start\": 44,\n \"value_end\": 52,\n \"entropy\": 3.0\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"url3d = \\\"https://localhost.com/013948?26timestamp%3D1395782596%26token%3Dh1d3Me4ch534d801sl3jdk%26version%3D3.14%26si\\\";\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 65,\n \"variable_end\": 70,\n \"value\": \"h1d3Me4ch534d801sl3jdk\",\n \"value_start\": 73,\n \"value_end\": 95,\n \"entropy\": 3.75444\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if (password !== \\\"PaS5w0rD2#\\\"){\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"PaS5w0rD2#\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"URL Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.933,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"line\\\": \\\"url: mongodb://jrfdeg42:p4Dsr8b@127.0.0.1:32768/architecture\\\"}\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"mongodb://\",\n \"variable_start\": 15,\n \"variable_end\": 25,\n \"value\": \"p4Dsr8b\",\n \"value_start\": 34,\n \"value_end\": 41,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"bace4d19-fa7e-beef-cafe-9129474bcd81 # tp\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/uuid\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"bace4d19-fa7e-beef-cafe-9129474bcd81\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.58954\n }\n ]\n },\n {\n \"rule\": \"Vercel Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/vercel\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"value_start\": 0,\n \"value_end\": 60,\n \"entropy\": 5.23581\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wxe191bc54fc7d529a\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wxe191bc54fc7d529a\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.72548\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wx2274a335e18222d6\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wx2274a335e18222d6\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.41383\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": 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\"value_end\": 51,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.966,\n \"line_data_list\": [\n {\n \"line\": \"ID:master,PW:dipPr10Gg!\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr10Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.971,\n \"line_data_list\": [\n {\n \"line\": \"ID:master PW:dipPr11Gg!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr11Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": 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\"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:master,password:dipPr14Gg!\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"dipPr14Gg!\",\n \"value_start\": 19,\n \"value_end\": 29,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.977,\n \"line_data_list\": [\n {\n \"line\": \"ID:master/PW:dipPr15Gg!\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PW\",\n \"variable_start\": 10,\n \"variable_end\": 12,\n \"value\": \"dipPr15Gg!\",\n \"value_start\": 13,\n \"value_end\": 23,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"id:master password:dipPr16Gg!\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"dipPr16Gg!\",\n \"value_start\": 19,\n \"value_end\": 29,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user:master password:dipPr17Gg!\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 12,\n \"variable_end\": 20,\n \"value\": \"dipPr17Gg!\",\n \"value_start\": 21,\n \"value_end\": 31,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"username:master,password:dipPr19Gg!\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 16,\n \"variable_end\": 24,\n \"value\": \"dipPr19Gg!\",\n \"value_start\": 25,\n \"value_end\": 35,\n \"entropy\": 3.32193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.986,\n \"line_data_list\": [\n {\n \"line\": \"username:master pwd:dipPr110Gg!\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"pwd\",\n \"variable_start\": 16,\n \"variable_end\": 19,\n \"value\": \"dipPr110Gg!\",\n \"value_start\": 20,\n \"value_end\": 31,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.987,\n \"line_data_list\": [\n {\n \"line\": \"ANYid:master,password:dipPr111Gg!\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 13,\n \"variable_end\": 21,\n \"value\": \"dipPr111Gg!\",\n \"value_start\": 22,\n \"value_end\": 33,\n \"entropy\": 3.02717\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.965,\n \"line_data_list\": [\n {\n \"line\": \"ID:master PWD:dipPr112Gg!\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"PWD\",\n \"variable_start\": 10,\n \"variable_end\": 13,\n \"value\": \"dipPr112Gg!\",\n \"value_start\": 14,\n \"value_end\": 25,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user id:master password:dipPr113Gg!\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 15,\n \"variable_end\": 23,\n \"value\": \"dipPr113Gg!\",\n \"value_start\": 24,\n \"value_end\": 35,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user:master,password:dipPr114Gg!\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/doc_id_pair_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 12,\n \"variable_end\": 20,\n \"value\": \"dipPr114Gg!\",\n \"value_start\": 21,\n \"value_end\": 32,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"user=master,password=dipPr115Gg!\",\n \"line_num\": 16,\n \"path\": 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0.999,\n \"line_data_list\": [\n {\n \"line\": \"ANY-password=Prl23Db#@\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/doc_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"ANY-password\",\n \"variable_start\": 0,\n \"variable_end\": 12,\n \"value\": \"Prl23Db#@\",\n \"value_start\": 13,\n \"value_end\": 22,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"master@98.76.54.32 password:Prl23Db#@\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/doc_passwd_pair\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 19,\n \"variable_end\": 27,\n \"value\": \"Prl23Db#@\",\n \"value_start\": 28,\n \"value_end\": 37,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"CMD Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"--Password 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\"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"hvs.atlasv1-Z28P3STmkBQi1Y-YE7RBqu6VVyQIOq9a1eC3YFU5Elt7ToIr6OwzKAWlCTQ7N4gElXaWou6aPpOIwGCoc0\",\n \"value_start\": 0,\n \"value_end\": 94,\n \"entropy\": 5.53423\n }\n ]\n },\n {\n \"rule\": \"Heroku Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"HRKU-RAjCYR7Mai1JAIhHASD6ITENvdVydAPCnNcAlrMrTLozPkj9_BGqh1J5P4Wf\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/heroku\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"HRKU-RAjCYR7Mai1JAIhHASD6ITENvdVydAPCnNcAlrMrTLozPkj9_BGqh1J5P4Wf\",\n \"value_start\": 0,\n \"value_end\": 65,\n \"entropy\": 5.32822\n }\n ]\n },\n {\n \"rule\": \"Heroku Credentials\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"HRKU-f1274537-88fb-deaf-beda-453bd9a496ef\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/heroku\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"HRKU-f1274537-88fb-deaf-beda-453bd9a496ef\",\n \"value_start\": 0,\n \"value_end\": 41,\n \"entropy\": 4.0555\n }\n ]\n },\n {\n \"rule\": \"Hugging Face User Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"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\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/huggingface\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 37,\n \"entropy\": 4.70256\n }\n ]\n },\n {\n \"rule\": \"Hugging Face User Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"url/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/part\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/huggingface\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 4,\n \"value_end\": 41,\n \"entropy\": 4.77702\n }\n ]\n },\n {\n \"rule\": \"Hugging Face User Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"hf_UdYjVqYvybBLEhIrwwEUYjOgkeyexample\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/huggingface\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"hf_UdYjVqYvybBLEhIrwwEUYjOgkeyexample\",\n \"value_start\": 0,\n \"value_end\": 37,\n \"entropy\": 4.62811\n }\n ]\n },\n {\n \"rule\": \"Instagram Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"IGQVJWS3pUNmZA2MUJDVlRwLW9ac1lrU05nZAmpzWHQtWHFJSEFRMF9tWVpRdEd70HQ5Wk8wSnY0R0VEQnVQdUU0MnpxNWxocUYyNmZAXSTUtVVNrMmh1ZAHZAQQno2ZA0VHR0lLWkk1N1R5RDFvM0dmVEpIYQZGZX\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/instagram_access_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"IGQVJWS3pUNmZA2MUJDVlRwLW9ac1lrU05nZAmpzWHQtWHFJSEFRMF9tWVpRdEd70HQ5Wk8wSnY0R0VEQnVQdUU0MnpxNWxocUYyNmZAXSTUtVVNrMmh1ZAHZAQQno2ZA0VHR0lLWkk1N1R5RDFvM0dmVEpIYQZGZX\",\n \"value_start\": 0,\n \"value_end\": 162,\n \"entropy\": 5.23164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/iso_ir_111.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Jfrog Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"cmVmdGtuOjAxOjAxMjM0NTY3ODk6QWJjZGVmR2hpamtsbW5vUHFyc3R1dnd4eXow\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/jfrog_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"cmVmdGtuOjAxOjAxMjM0NTY3ODk6QWJjZGVmR2hpamtsbW5vUHFyc3R1dnd4eXow\",\n \"value_start\": 0,\n \"value_end\": 64,\n \"entropy\": 5.28891\n }\n ]\n },\n {\n \"rule\": \"Jfrog Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"AKCp2UNCd8uK7hQoxZnFE4PGtRHnAcBHr43HgLcj7nJmWb4JhVUqBwa2iwXszftnogpo2EVFa\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/jfrog_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKCp2UNCd8uK7hQoxZnFE4PGtRHnAcBHr43HgLcj7nJmWb4JhVUqBwa2iwXszftnogpo2EVFa\",\n \"value_start\": 0,\n \"value_end\": 73,\n \"entropy\": 5.35394\n }\n ]\n },\n {\n \"rule\": \"Jira / Confluence PAT token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"TP: https://www.example.com/api/verification/version2322/token/OTI2NjA3NjU1NTI2Oh2DOnASdOHoIhEGyqIuYrdkYaQZ\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/jira_confluence_pat\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OTI2NjA3NjU1NTI2Oh2DOnASdOHoIhEGyqIuYrdkYaQZ\",\n \"value_start\": 63,\n \"value_end\": 107,\n \"entropy\": 4.60694\n }\n ]\n },\n {\n \"rule\": \"Jira / Confluence PAT token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"TP: \\\"image/png\\\": \\\"iVBORx09VIskhxhCe7sh03R1dnENPiB66xQSIZjEYN13vafX/OTI2NjA3NjU1NTI2Oh2DOnASdOHoIhEGyqIuYrdkYaQZ/hZwUteHsmN+z+aoEAAAAvL+Q5FSQGyqIuYrdkYaQZuW1TvI=\\\\n\\\",\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/jira_confluence_pat\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"OTI2NjA3NjU1NTI2Oh2DOnASdOHoIhEGyqIuYrdkYaQZ\",\n \"value_start\": 67,\n \"value_end\": 111,\n \"entropy\": 4.60694\n }\n ]\n },\n {\n \"rule\": \"JSON Web Key\",\n \"severity\": \"medium\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": 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\"value_start\": 0,\n \"value_end\": 407,\n \"entropy\": 5.27189\n }\n ]\n },\n {\n \"rule\": \"JSON Web Token\",\n \"severity\": \"medium\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"detected: eyJhbGciOiJSUzI1NiJ9Cg.eyJleHAiOjY1NTM2fQo.Ce7sh0ENPiBlE_dose0cBA\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/json_web_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"eyJhbGciOiJSUzI1NiJ9Cg.eyJleHAiOjY1NTM2fQo.Ce7sh0ENPiBlE_dose0cBA\",\n \"value_start\": 10,\n \"value_end\": 75,\n \"entropy\": 5.03815\n }\n ]\n },\n {\n \"rule\": \"JWK\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \\\"kty\\\": \\\"[EC]\\\",\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"kty\",\n \"variable_start\": 9,\n \"variable_end\": 12,\n \"value\": \"\\\"kty\\\": \\\"[EC\",\n \"value_start\": 8,\n \"value_end\": 19,\n \"entropy\": 3.02717\n },\n {\n \"line\": \" \\\"d\\\": \\\"slaQqyHQPudOpq2mbDskum8rOu9IMkLGjINAFWwfqr-\\\"\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"d\",\n \"variable_start\": 9,\n \"variable_end\": 10,\n \"value\": \"slaQqyHQPudOpq2mbDskum8rOu9IMkLGjINAFWwfqr-\",\n \"value_start\": 14,\n \"value_end\": 57,\n \"entropy\": 4.87953\n }\n ]\n },\n {\n \"rule\": \"JWK\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \\\"kty\\\": \\\"RSA\\\",\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"kty\",\n \"variable_start\": 9,\n \"variable_end\": 12,\n \"value\": \"\\\"kty\\\": \\\"RSA\\\"\",\n \"value_start\": 8,\n \"value_end\": 20,\n \"entropy\": 2.9183\n },\n {\n \"line\": \" \\\"d\\\": \\\"-phZ8N4GuwZchy7FCMB14IA35dBU3sWy2ORxwWN8PbKqKOkZb8mh4v_gQgwg7j16uSd91COBNPGH0hNzaH2jOY\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"d\",\n \"variable_start\": 9,\n \"variable_end\": 10,\n \"value\": \"-phZ8N4GuwZchy7FCMB14IA35dBU3sWy2ORxwWN8PbKqKOkZb8mh4v_gQgwg7j16uSd91COBNPGH0hNzaH2jOY\",\n \"value_start\": 14,\n \"value_end\": 100,\n \"entropy\": 5.43459\n }\n ]\n },\n {\n \"rule\": \"JWK\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \" \\\"kty\\\": \\\"oct\\\",\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"kty\",\n \"variable_start\": 9,\n \"variable_end\": 12,\n \"value\": \"\\\"kty\\\": \\\"oct\\\"\",\n \"value_start\": 8,\n \"value_end\": 20,\n \"entropy\": 2.75163\n },\n {\n \"line\": \" \\\"k\\\": \\\"WrMwQfoNaHTgXU5fZvRGAD\\\"\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/jwk.json\",\n \"info\": \"\",\n \"variable\": \"k\",\n \"variable_start\": 9,\n \"variable_end\": 10,\n \"value\": \"WrMwQfoNaHTgXU5fZvRGAD\",\n \"value_start\": 14,\n \"value_end\": 36,\n \"entropy\": 4.36852\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"var PKEY = `-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 12,\n \"value_end\": 47,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/key.go\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": 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0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"$key = 'gmUGWxhQW9KQWdhd0lCQVFRZ0ViVnpwrLzZYdDJPNG1PQjYxMXNPaFJ1\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.php\",\n \"info\": \"\",\n \"variable\": \"$key\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": \"gmUGWxhQW9KQWdhd0lCQVFRZ0ViVnpwrLzZYdDJPNG1PQjYxMXNPaFJ1\",\n \"value_start\": 8,\n \"value_end\": 64,\n \"entropy\": 4.96772\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"define( 'PASSWORD' , '2Arh5dA1Sn0ywiVYdnpwr3aLzZDJPNG' );\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/key.php\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 9,\n \"variable_end\": 17,\n \"value\": \"2Arh5dA1Sn0ywiVYdnpwr3aLzZDJPNG\",\n \"value_start\": 22,\n \"value_end\": 53,\n \"entropy\": 4.63162\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"pkey = (\\\"LS0tLS1CRUdJTiBQUklWQVRFIENDcUdTTTQ5QXdFSEJHMHdhd0lCQVFRZ0ViVn\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"\",\n \"variable\": \"pkey\",\n \"variable_start\": 0,\n \"variable_end\": 4,\n \"value\": \"LS0tLS1CRUdJTiBQUklWQVRFIENDcUdTTTQ5QXdFSEJHMHdhd0lCQVFRZ0ViVn\",\n \"value_start\": 9,\n \"value_end\": 71,\n \"entropy\": 4.71236\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"print(\\\"https://example.com/api/js?key=dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB&bug=true\\\")\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"\",\n \"variable\": \"key\",\n \"variable_start\": 34,\n \"variable_end\": 37,\n \"value\": \"dhd0lCQVFRZ0ViVnpmUGWxhQW9KQWwrLzZYdDJPNG1PQjYxMXNPaFJB\",\n \"value_start\": 38,\n \"value_end\": 93,\n \"entropy\": 4.96282\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"PKEY = \\\"\\\"\\\"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN OPENSSH PRIVATE KEY-----\",\n \"value_start\": 10,\n \"value_end\": 45,\n \"entropy\": 3.58716\n },\n {\n \"line\": \"b3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZWQyNTUx\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/key.py\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": 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\"value_start\": 0,\n \"value_end\": 33,\n \"entropy\": 3.46942\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-gOpoyW2vlgfBcYEYlSu8x3Tk3lrtW1AWJU8nXQ6XOCZah4h1\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.03958\n }\n ]\n },\n {\n \"rule\": \"LLAMA API Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/llama\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"llx-vYx_tfO1AgW73_hwAET-u7p7YVDTBERNn4ij4a8wrDrGM6RT\",\n \"value_start\": 0,\n \"value_end\": 52,\n \"entropy\": 5.05602\n }\n ]\n },\n {\n \"rule\": \"MailChimp API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"mailchimp = \\\"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailchimp_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"LRINSm5Vdi9BMCzCWSJ8M3TMysUHwDzB-us36\",\n \"value_start\": 13,\n \"value_end\": 50,\n \"entropy\": 4.75662\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"key-a25a4ac62a074cd52c668c6b9937cf40\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.91661\n }\n ]\n },\n {\n \"rule\": \"MailGun API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/mailgun\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"a25a4ac62a074cd52c668c6b9937cf40-432f2836-db15b420\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 3.85669\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 45,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 46,\n \"path\": \"./tests/samples/multifile.patch\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"AWS Client ID\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n }\n ]\n },\n {\n \"rule\": \"AWS Multi\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"+ clid = \\\"AKIAQWADE5R42RDZ4JEM\\\"\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"AKIAQWADE5R42RDZ4JEM\",\n \"value_start\": 11,\n \"value_end\": 31,\n \"entropy\": 3.68418\n },\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ token = \\\"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/multiline.patch\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 3,\n \"variable_end\": 8,\n \"value\": \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\",\n \"value_start\": 12,\n \"value_end\": 52,\n \"entropy\": 4.78418\n }\n ]\n },\n {\n \"rule\": \"Netlify Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/netlify\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"nfp_0i5OM4MV7L02wV3E6rrwiTwhvEkkkPJ9C3EP\",\n \"value_start\": 0,\n \"value_end\": 40,\n \"entropy\": 4.61531\n }\n ]\n },\n {\n \"rule\": \"NKEY Seed\",\n \"severity\": \"high\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"// SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/nkey_seed\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\",\n \"value_start\": 3,\n \"value_end\": 61,\n \"entropy\": 4.55826\n }\n ]\n },\n {\n \"rule\": \"Nonce\",\n \"severity\": \"low\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"nonce = 'bsfcvir57nt40rydvtbhs8lzbgljmet5'\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"nonce\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"bsfcvir57nt40rydvtbhs8lzbgljmet5\",\n \"value_start\": 9,\n \"value_end\": 41,\n \"entropy\": 4.39032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password: F1lT3ReDw17hQoT3s\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"F1lT3ReDw17hQoT3s\",\n \"value_start\": 10,\n \"value_end\": 27,\n \"entropy\": 3.73452\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_wrap = 'KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\\\\\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"key_wrap\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"KJHhJKhKU7yguyuyfrtsdESffhjgkhYT\",\n \"value_start\": 12,\n \"value_end\": 44,\n \"entropy\": 4.11673\n }\n ]\n },\n {\n \"rule\": \"Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"key_multi = '''KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/nonce.py\",\n \"info\": \"\",\n \"variable\": \"key_multi\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"KJHfdjs8767gr54534wsFHGf5hJKhK\",\n \"value_start\": 15,\n \"value_end\": 45,\n \"entropy\": 4.12323\n }\n ]\n },\n {\n \"rule\": \"Notion Integration Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/notion\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"ntn_123465789l62YMNJKXLKpjiCVEXbx4CBxkfprOA96Y15wZ\",\n \"value_start\": 0,\n \"value_end\": 50,\n \"entropy\": 5.06876\n }\n ]\n },\n {\n \"rule\": \"NPM Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n 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\"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\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"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\",\n \"value_start\": 0,\n \"value_end\": 51,\n \"entropy\": 5.22625\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-qa25MV9c7Qu0EjDIEWdcT3BlbkFJ83uCF0K4yw7RzpY39bio\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 5.25816\n }\n ]\n },\n {\n \"rule\": \"OpenAI Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/open_ai_token\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"sk-proj-asdfgasdfasdfdcQbzdcT3BlbkFJ83uCasdfgasdfgasdfjk\",\n \"value_start\": 0,\n \"value_end\": 56,\n \"entropy\": 4.12555\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"WXFES7QNTET5DQYC\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"WXFES7QNTET5DQYC\",\n \"value_start\": 0,\n \"value_end\": 16,\n \"entropy\": 3.625\n }\n ]\n },\n {\n \"rule\": \"OTP / 2FA Secret\",\n \"severity\": \"info\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/otp_2fa\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"JERZOR2XLQYTUQG7YBZYHLK3KSLRYTWB\",\n \"value_start\": 0,\n \"value_end\": 32,\n \"entropy\": 4.14032\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.99,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"gi_reo_gi_passwd\",\n \"variable_start\": 0,\n \"variable_end\": 16,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 20,\n \"value_end\": 30,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"gi_reo_gi_passwd = \\\"cAc48k1Zd7\\\"; password_confirmation = \\\"cAc48k1Zd7\\\";\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/passwd.groovy\",\n \"info\": \"\",\n \"variable\": \"password_confirmation\",\n \"variable_start\": 33,\n \"variable_end\": 54,\n \"value\": \"cAc48k1Zd7\",\n \"value_start\": 58,\n \"value_end\": 68,\n \"entropy\": 3.12193\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"cackle!\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.gradle\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 12,\n \"value_end\": 19,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password = \\\"MYPSWRD!@#$%^&*\\\"\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password.tfvars\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"MYPSWRD!@#$%^&*\",\n \"value_start\": 12,\n \"value_end\": 27,\n \"entropy\": 3.90689\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.996,\n \"line_data_list\": [\n {\n \"line\": \"MYSQLPASS: Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQLPASS\",\n \"variable_start\": 0,\n \"variable_end\": 9,\n \"value\": \"Ce7shE0ENPiBlE_EdEose0cBAA\",\n \"value_start\": 11,\n \"value_end\": 37,\n \"entropy\": 3.8693\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"my_pw: nCzx8A8#!\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"my_pw\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 7,\n \"value_end\": 16,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"val password: String = \\\"exord13Paw64\\\", // scala\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"exord13Paw64\",\n \"value_start\": 24,\n \"value_end\": 36,\n \"entropy\": 3.58496\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"def connect(passwd: str = \\\"cq2tPr1a2\\\"): # python default arg\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passwd\",\n \"variable_start\": 12,\n \"variable_end\": 18,\n \"value\": \"cq2tPr1a2\",\n \"value_start\": 27,\n \"value_end\": 36,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd == \\\"q4c1a2oPd\\\": # __eq__ separator\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"q4c1a2oPd\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"if passworsd != \\\"x6s7djtEa\\\": # __ne__ separator\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passworsd\",\n \"variable_start\": 3,\n \"variable_end\": 12,\n \"value\": \"x6s7djtEa\",\n \"value_start\": 17,\n \"value_end\": 26,\n \"entropy\": 3.16993\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"password=2bkJgtJDiLcq1t\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"2bkJgtJDiLcq1t\",\n \"value_start\": 9,\n \"value_end\": 23,\n \"entropy\": 3.52164\n }\n ]\n },\n {\n \"rule\": \"CMD Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"passin\",\n \"variable_start\": 33,\n \"variable_end\": 39,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"RUN openssl x509 -req -days 365 -passin \\\"pass:nCzx8A8#!\\\" -sha256 -in server.csr -CA ca.pem -CAkey ca-key\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"pass\",\n \"variable_start\": 41,\n \"variable_end\": 45,\n \"value\": \"nCzx8A8#!\",\n \"value_start\": 46,\n \"value_end\": 55,\n \"entropy\": 2.9477\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"MYSQL_DATABASE_USER=CRED;MYSQL_DATABASE_PASSWORD=2IWJD88FH4Y;\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"MYSQL_DATABASE_PASSWORD\",\n \"variable_start\": 25,\n \"variable_end\": 48,\n \"value\": \"2IWJD88FH4Y\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.27761\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"#define password \\\"n84ASM54y4\\\"\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"%define PASSWORD \\\"n84ASM54y4\\\"\",\n \"line_num\": 18,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"%global PASSWORD \\\"n84RPM54y4\\\"\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 8,\n \"variable_end\": 16,\n \"value\": \"n84RPM54y4\",\n \"value_start\": 18,\n \"value_end\": 28,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"SET password \\\"n83.bat47Fy4\\\"\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"n83.bat47Fy4\",\n \"value_start\": 14,\n \"value_end\": 26,\n \"entropy\": 3.4183\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"\\\"#define\\\\tpassword\\\\t\\\\\\\"n84ASM54y4\\\\\\\"\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 10,\n \"variable_end\": 18,\n \"value\": \"n84ASM54y4\",\n \"value_start\": 22,\n \"value_end\": 32,\n \"entropy\": 2.84644\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.991,\n \"line_data_list\": [\n {\n \"line\": \"WPA2_PASSWORD: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/password_TRUE\",\n \"info\": \"\",\n \"variable\": \"WPA2_PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 13,\n \"value\": \"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855\",\n \"value_start\": 15,\n \"value_end\": 79,\n \"entropy\": 3.67082\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajco1\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/password_utf16.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajco1\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.914,\n \"line_data_list\": [\n {\n \"line\": \"+ \\\"password\\\": \\\"dkajc\\u00f61\\\"\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/password_western.patch\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 4,\n \"variable_end\": 12,\n \"value\": \"dkajc\\u00f61\",\n \"value_start\": 16,\n \"value_end\": 23,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"PayPal Braintree Access Token\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"access_token$production$gireogi121451781$abcaeaabadef01134517891121451781\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/paypal_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"access_token$production$gireogi121451781$abcaeaabadef01134517891121451781\",\n \"value_start\": 0,\n \"value_end\": 73,\n \"entropy\": 4.39985\n }\n ]\n },\n {\n \"rule\": \"PEM Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"str value = \\\"-----BEGIN RSA PRIVATE KEY-----\\\\n\\\" +\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"-----BEGIN RSA PRIVATE KEY-----\",\n \"value_start\": 13,\n \"value_end\": 44,\n \"entropy\": 3.38229\n },\n {\n \"line\": \"\\\"MIICXQIBAAKBgQDwcEN7vZygGg6DvPpsw17hRD6S5N8+huaqs1JGXQfPhbvLTUsHdzGLVNQ/Z0wQVGdPiaJDflqhcT1IH8BLD4SHn+ \\\\n\\\"\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"\\\"MIICXQIBAAKBgQDwcEN7vZygGg6DvPpsw17hRD6S5N8+huaqs1JGXQfPhbvLTUsHdzGLVNQ/Z0wQVGdPiaJDflqhcT1IH8BLD4SHn+ \\\\n\\\"\",\n \"value_start\": 0,\n \"value_end\": 108,\n \"entropy\": 5.52555\n },\n {\n \"line\": \"\\t+ \\\"WuRIzX77P7oVKM2CoTA6VzT6s/bvr7HxFLl4NhohfyDsV0YCDc4I6EHGWMCUHZb0IWxzEGRWD3jbG8KAZUsQIDAQABAoGAOD7a2o\\\\r \\\\n\\\"\",\n \"line_num\": 4,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"\\t+ \\\"WuRIzX77P7oVKM2CoTA6VzT6s/bvr7HxFLl4NhohfyDsV0YCDc4I6EHGWMCUHZb0IWxzEGRWD3jbG8KAZUsQIDAQABAoGAOD7a2o\\\\r \\\\n\\\"\",\n \"value_start\": 0,\n \"value_end\": 110,\n \"entropy\": 5.49388\n },\n {\n \"line\": \"\\\" CRujY+PP0hS/4sHOBdDvnxa2wdW8NVNNagdCBhvP5Y1edBNMnkWOyuM4e7HzUgO0+8ndWis1OSJTz9EFTyHJm6GOn+/JR62NWNr \\\"\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"\\\" CRujY+PP0hS/4sHOBdDvnxa2wdW8NVNNagdCBhvP5Y1edBNMnkWOyuM4e7HzUgO0+8ndWis1OSJTz9EFTyHJm6GOn+/JR62NWNr \\\"\",\n \"value_start\": 0,\n \"value_end\": 106,\n \"entropy\": 5.44383\n },\n {\n \"line\": \"\\t\\t\\\"9lfCb8cWq0eoOk3UUO9P+1nZNHjE/iDhuTi3x/5naW4SzdkZfxHo/NMI6i5w1ZnQ60CQQD9d0G9gBy6lPhC \\\\\\\\\",\n \"line_num\": 6,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"\\t\\t\\\"9lfCb8cWq0eoOk3UUO9P+1nZNHjE/iDhuTi3x/5naW4SzdkZfxHo/NMI6i5w1ZnQ60CQQD9d0G9gBy6lPhC \\\\\\\\\",\n \"value_start\": 0,\n \"value_end\": 90,\n \"entropy\": 5.53586\n },\n {\n \"line\": \"\\\"\\\"\\\" mbHzYovVjSnyfzUtyWPNSrXNiUCR5vu2f6eCgSVzFZ0oHAv8nLaYnXrhyT25lwzNK5OhR/oPAkEA8tep3NmfxV \\\"\\\"\\\" +\",\n \"line_num\": 7,\n \"path\": \"./tests/samples/pem_key\",\n \"info\": \"\",\n 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\"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'haproxy'@'%' IDENTIFIED BY\",\n \"variable_start\": 2,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 43,\n \"value_end\": 54,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.996,\n \"line_data_list\": [\n {\n \"line\": \"exec(\\\"CREATE USER ExposedTest ACCOUNT UNLOCK IDENTIFIED BY SqLpa5sW0rD\\\");\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER ExposedTest ACCOUNT UNLOCK IDENTIFIED BY\",\n \"variable_start\": 6,\n \"variable_end\": 58,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 59,\n \"value_end\": 70,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.914,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER foo WITH ENCRYPTED PASSWORD 'SqLpa5sW0rD' CREATEDB;\",\n \"line_num\": 8,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER foo WITH ENCRYPTED PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 39,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 41,\n \"value_end\": 52,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"ALTER LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 26,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 38,\n \"value_end\": 49,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"ALTER LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 9,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER LOGIN username WITH PASSWORD =\",\n \"variable_start\": 0,\n \"variable_end\": 36,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 38,\n \"value_end\": 49,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.992,\n \"line_data_list\": [\n {\n \"line\": \"ALTER ROLE postgres PASSWORD 'SqLpa5sW0rD'; SELECT pg_reload_conf()\\\"\",\n \"line_num\": 10,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER ROLE postgres PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 28,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 30,\n \"value_end\": 41,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"PASSWORD\",\n \"variable_start\": 27,\n \"variable_end\": 35,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE LOGIN username WITH PASSWORD = 'SqLpa5sW0rD';\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE LOGIN username WITH PASSWORD =\",\n \"variable_start\": 0,\n \"variable_end\": 37,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 39,\n \"value_end\": 50,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER chuck WITH PASSWORD 'SqLpa5sW0rD' SUPERUSER;\",\n \"line_num\": 13,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER chuck WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 31,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 33,\n \"value_end\": 44,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD 'SqLpa5sW0rD' NOSUPERUSER;\",\n \"line_num\": 14,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER IF NOT EXISTS sandy WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 45,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 47,\n \"value_end\": 58,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER myuser WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 15,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER myuser WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 32,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username WITH PASSWORD 'SqLpa5sW0rD';\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER username WITH PASSWORD\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 36,\n \"value_end\": 47,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.964,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 17,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 47,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 49,\n \"value_end\": 60,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.899,\n \"line_data_list\": [\n {\n \"line\": \"ALTER USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 19,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"ALTER USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 33,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 34,\n \"value_end\": 45,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.991,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER username IDENTIFIED BY SqLpa5sW0rD;\",\n \"line_num\": 20,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER username IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 34,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 35,\n \"value_end\": 46,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.997,\n \"line_data_list\": [\n {\n \"line\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\",\n \"line_num\": 21,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'username'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 0,\n \"variable_end\": 48,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 50,\n \"value_end\": 61,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.998,\n \"line_data_list\": [\n {\n \"line\": \"mysql -u root -pdbadmin -e \\\"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY 'SqLpa5sW0rD';\\\"\\u2013 \",\n \"line_num\": 22,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE USER 'cactiuser'@'localhost' IDENTIFIED BY\",\n \"variable_start\": 28,\n \"variable_end\": 77,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 79,\n \"value_end\": 90,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.999,\n \"line_data_list\": [\n {\n \"line\": \"-c \\\"CREATE ROLE scram_test login password 'SqLpa5sW0rD'\\\"\",\n \"line_num\": 23,\n \"path\": \"./tests/samples/sql_password\",\n \"info\": \"\",\n \"variable\": \"CREATE ROLE scram_test login password\",\n \"variable_start\": 4,\n \"variable_end\": 41,\n \"value\": \"SqLpa5sW0rD\",\n \"value_start\": 43,\n \"value_end\": 54,\n \"entropy\": 3.45943\n }\n ]\n },\n {\n \"rule\": \"SQL Password\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": 0.995,\n \"line_data_list\": [\n {\n \"line\": \"CREATE ROLE app_admin WITH LOGIN PASSWORD SqLpa5sW0rD;\",\n \"line_num\": 24,\n \"path\": 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\"moderate\",\n \"ml_probability\": 0.933,\n \"line_data_list\": [\n {\n \"line\": \"{\\\"line\\\": \\\"url: mongodb://jrfdeg42:p4Dsr8b@127.0.0.1:32768/architecture\\\"}\",\n \"line_num\": 25,\n \"path\": \"./tests/samples/url_cred.js\",\n \"info\": \"\",\n \"variable\": \"mongodb://\",\n \"variable_start\": 15,\n \"variable_end\": 25,\n \"value\": \"p4Dsr8b\",\n \"value_start\": 34,\n \"value_end\": 41,\n \"entropy\": 2.80735\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"bace4d19-fa7e-beef-cafe-9129474bcd81 # tp\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/uuid\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"bace4d19-fa7e-beef-cafe-9129474bcd81\",\n \"value_start\": 0,\n \"value_end\": 36,\n \"entropy\": 3.58954\n }\n ]\n },\n {\n \"rule\": \"Vercel Token\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/vercel\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"vcp_5G8LQP7fmw80eG7W8y0sWO1QFPuhsYUuLEqyd1ialdvz9r6pL4vzxkC3\",\n \"value_start\": 0,\n \"value_end\": 60,\n \"entropy\": 5.23581\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wxe191bc54fc7d529a\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wxe191bc54fc7d529a\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.72548\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wx2274a335e18222d6\",\n \"line_num\": 2,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wx2274a335e18222d6\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.41383\n }\n ]\n },\n {\n \"rule\": \"Tencent WeChat API App ID\",\n \"severity\": \"medium\",\n \"confidence\": \"weak\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"wx4d82d07e3eb5ba84\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/wechat_p\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"wx4d82d07e3eb5ba84\",\n \"value_start\": 0,\n \"value_end\": 18,\n \"entropy\": 3.61437\n }\n ]\n },\n {\n \"rule\": \"X AI API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"xai-wjluCw1zixzDiYOxeeGtIwuHjIyax8SukK2lFWtBRn1yfEPMQzv63sMCd1nzqylpuDXQjEGd19OJi3cL\",\n \"line_num\": 1,\n \"path\": \"./tests/samples/xai\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"xai-wjluCw1zixzDiYOxeeGtIwuHjIyax8SukK2lFWtBRn1yfEPMQzv63sMCd1nzqylpuDXQjEGd19OJi3cL\",\n \"value_start\": 0,\n \"value_end\": 84,\n \"entropy\": 5.35637\n }\n ]\n },\n {\n \"rule\": \"BASE64 Private Key\",\n \"severity\": \"high\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"data : MIIBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsnhRFakQFbAuI/\\n DaJSTVnp3ObjJPZhJs/P/XPWIKRNIglRqkkCAwEAAQJAbErPFMWah3EPxtfeVO1l\\n 5R0yAZwrFKmLDO29/FoXyL2XbxthJlJmdMQgIYayZYn4W2PSq6C56AI201SlW7Ts\\n AQIhAMwBYS+NST98g0nytTRD1Y94n+yrhTlyWNR/uC4tT8SpAiEAwthlcs9UDPh5\\n BnaO8Y7A+im+Aw5ANIhJwSVBxB3QnKECIQCJm9ihic1B7MxmojgGxEcXGwfNTjl0\\n caRn2qszQs9O2QIgdaBFvkXDrADkry4rpVBU17ETcKzNvej4/Y0MYuTM54ECIGtT\\n EBUWuiacAxz/WKHb9WVp0F/zkRwucJ0Hr2W4P9cP\",\n \"line_num\": 3,\n \"path\": \"./tests/samples/xml_data.xml\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"MIIBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsnhRFakQFbAuI/\\n DaJSTVnp3ObjJPZhJs/P/XPWIKRNIglRqkkCAwEAAQJAbErPFMWah3EPxtfeVO1l\\n 5R0yAZwrFKmLDO29/FoXyL2XbxthJlJmdMQgIYayZYn4W2PSq6C56AI201SlW7Ts\\n AQIhAMwBYS+NST98g0nytTRD1Y94n+yrhTlyWNR/uC4tT8SpAiEAwthlcs9UDPh5\\n BnaO8Y7A+im+Aw5ANIhJwSVBxB3QnKECIQCJm9ihic1B7MxmojgGxEcXGwfNTjl0\\n caRn2qszQs9O2QIgdaBFvkXDrADkry4rpVBU17ETcKzNvej4/Y0MYuTM54ECIGtT\\n EBUWuiacAxz/WKHb9WVp0F/zkRwucJ0Hr2W4P9cP\",\n \"value_start\": 7,\n \"value_end\": 485,\n \"entropy\": 5.75738\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.993,\n \"line_data_list\": [\n {\n \"line\": \"token : \\\"IBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsn\\n hRFakQFbAuI769fdsbkjerfkjrekjnkerjnfkrejnfrejn==\\\"\",\n \"line_num\": 12,\n \"path\": \"./tests/samples/xml_data.xml\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"IBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsn\\n hRFakQFbAuI769fdsbkjerfkjrekjnkerjnfkrejnfrejn==\",\n \"value_start\": 9,\n \"value_end\": 116,\n \"entropy\": 5.12458\n }\n ]\n },\n {\n \"rule\": \"Token\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 1.0,\n \"line_data_list\": [\n {\n \"line\": \"token : IBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsn\\n hRFakQFbAuI769fdsbkjerfkjrekjnkerjnfkrejnfrejn==\",\n \"line_num\": 16,\n \"path\": \"./tests/samples/xml_data.xml\",\n \"info\": \"\",\n \"variable\": \"token\",\n \"variable_start\": 0,\n \"variable_end\": 5,\n \"value\": \"IBOgIBAAJBAJtFfagSXdo0JmX6EdwWGvFMaXeOFY5xOTs3PWsn\",\n \"value_start\": 8,\n \"value_end\": 58,\n \"entropy\": 4.83327\n }\n ]\n },\n {\n \"rule\": \"Password\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"ml_probability\": 0.857,\n \"line_data_list\": [\n {\n \"line\": \"password : cackle!\",\n \"line_num\": 5,\n \"path\": \"./tests/samples/xml_password.xml\",\n \"info\": \"\",\n \"variable\": \"password\",\n \"variable_start\": 0,\n \"variable_end\": 8,\n \"value\": \"cackle!\",\n \"value_start\": 11,\n \"value_end\": 18,\n \"entropy\": 2.52164\n }\n ]\n },\n {\n \"rule\": \"UUID\",\n \"severity\": \"info\",\n \"confidence\": \"strong\",\n \"ml_probability\": null,\n \"line_data_list\": [\n {\n \"line\": \"password : Password for authorization\\n BAIT: bace4d59-fa7e-beef-cafe-9129474bcd81\",\n \"line_num\": 11,\n \"path\": \"./tests/samples/xml_password.xml\",\n \"info\": \"\",\n \"variable\": null,\n \"variable_start\": -2,\n \"variable_end\": -2,\n \"value\": \"bace4d59-fa7e-beef-cafe-9129474bcd81\",\n \"value_start\": 52,\n \"value_end\": 88,\n \"entropy\": 3.66606\n }\n ]\n }\n]" }, { "path": "tests/deep_scanner/__init__.py", "content": "" }, { "path": "tests/deep_scanner/test_abstract_scanner.py", "content": "import random\nimport unittest\n\nfrom credsweeper.deep_scanner.abstract_scanner import AbstractScanner\nfrom tests import AZ_STRING, AZ_DATA\n\n\nclass TestAbstractScanner(unittest.TestCase):\n\n def test_structure_processing_n(self):\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=None)))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=42)))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=3.14)))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=AZ_STRING)))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=AZ_DATA)))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=())))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure=[])))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure={})))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure={0: [], 1: (), 2: {}})))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure={\"key\": None})))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure={\"key\": 0})))\n self.assertListEqual([], list(AbstractScanner.structure_processing(structure={\"key\": False})))\n\n def test_structure_processing_p(self):\n self.assertListEqual([(0, 1), (1, 2), (2, 3)], list(AbstractScanner.structure_processing(structure=(1, 2, 3))))\n self.assertListEqual([(0, 1), (1, 2), (2, 3)], list(AbstractScanner.structure_processing(structure=[1, 2, 3])))\n self.assertListEqual([(0, 1), (1, 2), (2, 3)],\n list(AbstractScanner.structure_processing(structure={\n 0: 1,\n 1: 2,\n 2: 3\n })))\n self.assertListEqual([(42, 3.14)], list(AbstractScanner.structure_processing(structure={42: 3.14})))\n self.assertListEqual([(\"key\", AZ_STRING), (\"VALUE\", AZ_DATA), (AZ_STRING, AZ_DATA)],\n list(AbstractScanner.structure_processing(structure={\n \"key\": AZ_STRING,\n \"VALUE\": AZ_DATA\n })))\n\n def test_key_value_combination_n(self):\n # bytes in key do not produce augmented pair\n self.assertListEqual([],\n list(AbstractScanner.key_value_combination(structure={\n \"key\": AZ_STRING,\n b\"VALUE\": AZ_DATA\n })))\n # and wrong symbols do not produce the pair\n self.assertListEqual([],\n list(AbstractScanner.key_value_combination(structure={\n \"KEY\": AZ_STRING,\n \"VaLuE\": AZ_DATA\n })))\n # bytes which cannot be decoded do not produce the augmentation\n self.assertListEqual([],\n list(\n AbstractScanner.key_value_combination(structure={\n \"Key\": random.randbytes(16),\n \"VALUE\": AZ_DATA\n })))\n\n def test_key_value_combination_p(self):\n self.assertListEqual([(AZ_STRING, AZ_DATA)],\n list(AbstractScanner.key_value_combination(structure={\n \"Key\": AZ_STRING,\n \"VALUE\": AZ_DATA\n })))\n # bytes in key value may produce the augmentation\n self.assertListEqual([(AZ_STRING, AZ_DATA)],\n list(AbstractScanner.key_value_combination(structure={\n \"Key\": AZ_DATA,\n \"VALUE\": AZ_DATA\n })))\n" }, { "path": "tests/deep_scanner/test_bzip2_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.bzip2_scanner import Bzip2Scanner\n\n\nclass TestBzip2Scanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid bzip2 signature with correct version and block size\n self.assertTrue(Bzip2Scanner.match(b\"\\x42\\x5A\\x68\\x31\\x31\\x41\\x59\\x26\\x53\\x59\"))\n self.assertTrue(Bzip2Scanner.match(b\"\\x42\\x5A\\x68\\x39\\x31\\x41\\x59\\x26\\x53\\x59\"))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n Bzip2Scanner.match(None)\n with self.assertRaises(AttributeError):\n Bzip2Scanner.match(1)\n # Too short\n self.assertFalse(Bzip2Scanner.match(b\"\"))\n self.assertFalse(Bzip2Scanner.match(b\"\\x42\\x5A\\x68\"))\n # Wrong signature\n self.assertFalse(Bzip2Scanner.match(b\"\\x42\\x5A\\x69\"))\n # Wrong version\n self.assertFalse(Bzip2Scanner.match(b\"\\x42\\x5A\\x68\\x30\\x31\\x41\\x59\\x26\\x53\\x59\"))\n # Wrong block size\n self.assertFalse(Bzip2Scanner.match(b\"\\x42\\x5A\\x68\\x31\\x30\\x41\\x59\\x26\\x53\\x59\"))\n" }, { "path": "tests/deep_scanner/test_crx_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.crx_scanner import CrxScanner\nfrom tests import AZ_DATA\n\n\nclass TestCrxScanner(unittest.TestCase):\n\n def test_match_p(self):\n self.assertTrue(CrxScanner.match(b'Cr24\\x02\\x00\\x00\\x00' + b'\\0' * 32))\n self.assertTrue(CrxScanner.match(b'Cr24\\x03\\x00\\x00\\x00' + b'\\0' * 32))\n\n def test_match_n(self):\n # wrong data type\n with self.assertRaises(AttributeError):\n self.assertFalse(CrxScanner.match(None))\n with self.assertRaises(AttributeError):\n self.assertFalse(CrxScanner.match(1))\n # few bytes than required\n self.assertFalse(CrxScanner.match(b'Cr24\\x02\\x00\\x00\\x00' + b'\\0' * 16))\n self.assertFalse(CrxScanner.match(AZ_DATA))\n\n def test_zip_extract_p(self):\n self.assertEqual(b'', CrxScanner.zip_extract(b'\\0' * 16))\n self.assertEqual(AZ_DATA, CrxScanner.zip_extract(b'\\0' * 16 + AZ_DATA))\n\n def test_zip_extract_n(self):\n # wrong data type\n with self.assertRaises(TypeError):\n self.assertFalse(CrxScanner.zip_extract(None))\n" }, { "path": "tests/deep_scanner/test_csv_scanner.py", "content": "import random\nimport unittest\nfrom _csv import Error\n\nfrom credsweeper.deep_scanner.csv_scanner import CsvScanner\nfrom tests import AZ_STRING, SAMPLES_PATH, AZ_DATA\n\n\nclass TestCsvScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def test_match_n(self):\n # even random data may look like a CSV\n random_data = random.randbytes(random.randint(4, 16))\n self.assertFalse(CsvScanner.match(random_data), random_data)\n self.assertFalse(CsvScanner.match(b''))\n self.assertFalse(CsvScanner.match(b'||||'))\n self.assertFalse(CsvScanner.match(AZ_DATA))\n self.assertFalse(CsvScanner.match(AZ_DATA + b'\\r\\n'))\n\n def test_match_p(self):\n self.assertTrue(CsvScanner.match(b'a|b\\r1|2'))\n self.assertTrue(CsvScanner.match(b'a|b\\n1|2'))\n self.assertTrue(CsvScanner.match(b'a|b\\r\\n1|2'))\n\n def test_get_structure_n(self):\n with self.assertRaises(ValueError):\n CsvScanner.get_structure('First line,\"and escaped,coma\"\\nSecond,line,with more comas\\n')\n with self.assertRaises(ValueError):\n CsvScanner.get_structure(\"First,line\\nSecond,line,with,more,comas\")\n with self.assertRaises(Error):\n CsvScanner.get_structure(f\"{AZ_STRING[:19]}\\n{AZ_STRING[20:]}\\n\")\n with self.assertRaises(Error):\n CsvScanner.get_structure(\"'user and password'\\nadmin&tizen\\n\")\n with self.assertRaises(ValueError):\n CsvScanner.get_structure('')\n with self.assertRaises(Error):\n CsvScanner.get_structure(\"user&password\\nadmin&tizen\\n\")\n with self.assertRaises(Error):\n CsvScanner.get_structure('\"user and password\"\\nadmin&tizen\\n')\n with self.assertRaises(ValueError):\n CsvScanner.get_structure(\"user,password\\tadmin,tizen\\t\")\n\n def test_get_structure_from_sample_n(self):\n with self.assertRaises(ValueError):\n with open(SAMPLES_PATH / \"aws_client_id\") as f:\n CsvScanner.get_structure(f.read())\n\n def test_get_structure_p(self):\n structure = CsvScanner.get_structure(\"user,password\\nadmin,tizen\\nempty,\\n\")\n self.assertIsInstance(structure, list)\n self.assertEqual(2, len(structure))\n self.assertDictEqual({'password': 'tizen', 'user': 'admin'}, structure[0])\n self.assertDictEqual({'password': '', 'user': 'empty'}, structure[1])\n #CsvScanner.get_structure(\"Feuer und Wasser\\ncommt nicht zusammen\\n\")\n" }, { "path": "tests/deep_scanner/test_deb_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.deb_scanner import DebScanner\n\n\nclass TestDebScanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid deb archive signature\n self.assertTrue(DebScanner.match(b\"!\\n\"))\n self.assertTrue(DebScanner.match(b\"!\\nmore data here\"))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n DebScanner.match(None)\n with self.assertRaises(AttributeError):\n DebScanner.match(1)\n # Too short\n self.assertFalse(DebScanner.match(b\"\"))\n self.assertFalse(DebScanner.match(b\"!\"))\n # Wrong signature\n self.assertFalse(DebScanner.match(b\"\\n\"))\n self.assertFalse(DebScanner.match(b\"!\"))\n self.assertFalse(DebScanner.match(b\"!\\r\"))\n" }, { "path": "tests/deep_scanner/test_deep_scanner.py", "content": "import unittest\n\nfrom hypothesis import given, strategies\n\nfrom credsweeper.deep_scanner.deep_scanner import DeepScanner\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom tests import AZ_DATA, AZ_STRING\n\n\nclass TestDeepScanner(unittest.TestCase):\n\n def test_get_deep_scanners_n(self):\n self.assertEqual(([], []), DeepScanner.get_deep_scanners(None, Descriptor('', '', ''), 0))\n self.assertEqual(([], []), DeepScanner.get_deep_scanners(b'', Descriptor('', '', ''), 0))\n self.assertEqual(([], []), DeepScanner.get_deep_scanners(b'0xFF', Descriptor('', '', ''), 0))\n\n @given(strategies.binary())\n def test_get_deep_scanners_n(self, data):\n # no exception should be raised\n x, y = DeepScanner.get_deep_scanners(data, Descriptor('', '', ''), 0)\n # no fallback scanners for depth=0\n self.assertListEqual([], y)\n\n def test_is_media_n(self):\n with self.assertRaises(TypeError):\n self.assertFalse(DeepScanner.is_media(None))\n with self.assertRaises(IndexError):\n self.assertFalse(DeepScanner.is_media(b''))\n self.assertFalse(DeepScanner.is_media(AZ_STRING))\n self.assertFalse(DeepScanner.is_media(AZ_DATA))\n self.assertFalse(DeepScanner.is_media(b\"\\0\\0\\0\\0\"))\n self.assertFalse(DeepScanner.is_media(b\"III. Password is Gehe1mnis!\"))\n self.assertFalse(DeepScanner.is_media(b\"\\xFF\\xFEu\\x00t\\x00f\\x001\\x006\\x00\"))\n self.assertFalse(DeepScanner.is_media(b\"GIF89a format cannot store data inside\\n\\tHowever a picture can\\r\\n\"))\n self.assertFalse(DeepScanner.is_media(b\"BMP is a picture\"))\n\n def test_is_media_p(self):\n self.assertTrue(DeepScanner.is_media(b\"\\x89PNG\\x0D\\x0A\\x1A\\x0A...can store text chunks\"))\n self.assertTrue(DeepScanner.is_media(b\"\\xFF\\xD8\\xFF\\xE1+\\x84Exif\\0\\0*\\0\"))\n self.assertTrue(DeepScanner.is_media(b\"GIF89a null terminated string\\0\"))\n self.assertTrue(DeepScanner.is_media(b\"BMP!\\0\\0\\0\\0\"))\n" }, { "path": "tests/deep_scanner/test_eml_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.eml_scanner import EmlScanner\n\n\nclass TestEmlScanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid EML format with all required headers\n eml_data = b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nFrom: sender@example.com\\nTo: recipient@example.com\\nSubject: Test Email\\n\\nEmail body\"\n self.assertTrue(EmlScanner.match(eml_data))\n\n # EML format with headers at the beginning\n eml_data2 = b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nFrom: sender@example.com\\nTo: recipient@example.com\\nSubject: Test Email\"\n self.assertTrue(EmlScanner.match(eml_data2))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(TypeError):\n EmlScanner.match(None)\n with self.assertRaises(TypeError):\n EmlScanner.match(1)\n # Missing required headers\n self.assertFalse(\n EmlScanner.match(b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nFrom: sender@example.com\\nSubject: Test Email\"))\n self.assertFalse(EmlScanner.match(b\"From: sender@example.com\\nTo: recipient@example.com\\nSubject: Test Email\"))\n self.assertFalse(\n EmlScanner.match(b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nTo: recipient@example.com\\nSubject: Test Email\"))\n self.assertFalse(\n EmlScanner.match(\n b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nFrom: sender@example.com\\nTo: recipient@example.com\"))\n # Wrong format\n self.assertFalse(EmlScanner.match(b\"This is not an email\"))\n self.assertFalse(EmlScanner.match(b\"Date: Mon, 1 Jan 2024 12:00:00 +0000\\nFrom: sender@example.com\"))\n" }, { "path": "tests/deep_scanner/test_encoder_scanner.py", "content": "import string\nimport unittest\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.deep_scanner.encoder_scanner import EncoderScanner\nfrom tests import AZ_DATA\n\n\nclass TestEncoderScanner(unittest.TestCase):\n\n def test_match_n(self):\n with self.assertRaises(TypeError):\n EncoderScanner.match(None)\n self.assertFalse(EncoderScanner.match(b\"\"))\n self.assertFalse(EncoderScanner.match(AZ_DATA))\n self.assertFalse(EncoderScanner.match(b\"ba4e4d89-dead-beef-c0fe-913bc57ff132\"))\n self.assertFalse(EncoderScanner.match(b\"/Some/Path.extension\"))\n self.assertFalse(EncoderScanner.match(b\"1-various+SYMBOLS\"))\n self.assertFalse(EncoderScanner.match(string.digits.encode()))\n self.assertFalse(EncoderScanner.match(string.ascii_letters.encode()))\n self.assertFalse(EncoderScanner.match(string.ascii_lowercase.encode()))\n self.assertFalse(EncoderScanner.match(string.ascii_uppercase.encode()))\n self.assertFalse(EncoderScanner.match(string.printable.encode()))\n self.assertFalse(EncoderScanner.match(b'A' * MAX_LINE_LENGTH + b\"E2e4\"))\n self.assertFalse(EncoderScanner.match(b'a' * MAX_LINE_LENGTH + b\"E2e4\"))\n self.assertFalse(EncoderScanner.match(b'0' * MAX_LINE_LENGTH + b\"E2e4\"))\n self.assertFalse(EncoderScanner.match(b\"TooSh0rt\"))\n\n def test_match_p(self):\n self.assertTrue(\n EncoderScanner.match(\n b'\\xFF\\xFE\\x00X\\x00G\\x005\\x00n\\x00a\\x00X\\x00R\\x00f\\x00d\\x00G\\x009\\x00r\\x00Z\\x00W\\x004\\x00g\\x00P'\n b'\\x00S\\x00A\\x00i\\x00Z\\x002\\x00l\\x00y\\x00Z\\x00W\\x009\\x00n\\x00a\\x00W\\x00N\\x00y\\x00Y\\x00W\\x00N'\n b'\\x00r\\x00b\\x00G\\x00V\\x00j\\x00c\\x00m\\x00\\r\\x00\\n\\x00F\\x00j\\x00a\\x002\\x00x\\x00l\\x00M\\x00T\\x00I'\n b'\\x00z\\x00M\\x00T\\x00U\\x002\\x00N\\x00z\\x00E\\x005\\x00M\\x00D\\x00E\\x00x\\x00M\\x00z\\x00Q\\x00x\\x00M\\x00z'\n b'\\x00k\\x004\\x00M\\x00S\\x00J\\x00c\\x00b\\x00l\\x00x\\x00u\\x00C\\x00g\\x00=\\x00=\\x00\\r\\x00\\n\\x00\\r\\x00\\n'))\n self.assertTrue(EncoderScanner.match(b\"E2e4\\n\\tnext line\"))\n self.assertTrue(EncoderScanner.match(b\"E2e4a1++//==\"))\n" }, { "path": "tests/deep_scanner/test_gzip_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.gzip_scanner import GzipScanner\n\n\nclass TestGzipScanner(unittest.TestCase):\n\n def test_match_p(self):\n self.assertTrue(GzipScanner.match(b'\\x1f\\x8b\\x08'))\n self.assertTrue(GzipScanner.match(b'\\x1f\\x8b\\x08xxx'))\n\n def test_match_n(self):\n with self.assertRaises(AttributeError):\n self.assertFalse(GzipScanner.match(None))\n self.assertFalse(GzipScanner.match(b'\\x1f'))\n self.assertFalse(GzipScanner.match(b'\\x1f\\x8bxxx'))\n self.assertFalse(GzipScanner.match(b'\\x1f\\x8b\\x02'))\n" }, { "path": "tests/deep_scanner/test_html_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.html_scanner import HtmlScanner\n\n\nclass TestHtmlScanner(unittest.TestCase):\n\n def test_match_n(self):\n self.assertFalse(HtmlScanner.match(b\"\"))\n with self.assertRaises(AttributeError):\n HtmlScanner.match(None)\n\n def test_match_p(self):\n self.assertTrue(HtmlScanner.match(b\"
    \"))\n" }, { "path": "tests/deep_scanner/test_jclass_scanner.py", "content": "import base64\nimport io\nimport struct\nimport unittest\n\nfrom credsweeper.deep_scanner.jclass_scanner import JclassScanner\nfrom tests import AZ_DATA\n\nSAMPLE_B64 = \"\"\"\nyv66vgAAAEEAaQoAAgADBwAEDAAFAAYBABBqYXZhL2xhbmcvT2JqZWN0AQAGPGluaXQ+AQADKClWEgAAAAgMAAkACgEAA3J1bgEAFigpTGphdmEvbGFuZy9S\ndW5uYWJsZTsLAAwADQcADgwACQAGAQASamF2YS9sYW5nL1J1bm5hYmxlCQAQABEHABIMABMAFAEAEGphdmEvbGFuZy9TeXN0ZW0BAANvdXQBABVMamF2YS9p\nby9QcmludFN0cmVhbTsHABYBAAZTYW1wbGUKABgAGQcAGgwAGwAcAQATamF2YS9pby9QcmludFN0cmVhbQEAB3ByaW50bG4BAAQoWilWCgAYAB4MABsAHwEA\nBChDKVYIACEBACRiYWNlNGQxOS1iZWVmLWNhZmUtY29vMS05MTI5NDc0YmNkODEKABgAIwwAGwAkAQAVKExqYXZhL2xhbmcvU3RyaW5nOylWBQAAAAB3NhXZ\nCgAYACgMABsAKQEABChKKVYGQBdu4XWCSM4KABgALQwAGwAuAQAEKEQpVgoAFQADCgAVAA0IAAkBAAxKQVZBX0JPT0xFQU4BAAFaAQANQ29uc3RhbnRWYWx1\nZQMAAAABAQAJSkFWQV9DSEFSAQABQwMAAABYAQAJSkFWQV9CWVRFAQABQgMAAAB7AQAKSkFXQV9TSE9SVAEAAVMDAAABXgEACEpBVkFfSU5UAQABSQMAAIAA\nAQAJSkFWQV9MT05HAQABSgUAAAAAdzWUAAEACkpBVkFfRkxPQVQBAAFGBEBI9cMBAAtKQVZBX0RPVUJMRQEAAUQGQAW/CosEkZsBAAtKQVZBX1NUUklORwEA\nEkxqYXZhL2xhbmcvU3RyaW5nOwEABENvZGUBAA9MaW5lTnVtYmVyVGFibGUBAANsb2cBAARtYWluAQAWKFtMamF2YS9sYW5nL1N0cmluZzspVgEADGxhbWJk\nYSRydW4kMAEAClNvdXJjZUZpbGUBAAtTYW1wbGUuamF2YQEAEEJvb3RzdHJhcE1ldGhvZHMQAAYPBgBaCgAVAFsMAFQABg8GAF0KAF4AXwcAYAwAYQBiAQAi\namF2YS9sYW5nL2ludm9rZS9MYW1iZGFNZXRhZmFjdG9yeQEAC21ldGFmYWN0b3J5AQDMKExqYXZhL2xhbmcvaW52b2tlL01ldGhvZEhhbmRsZXMkTG9va3Vw\nO0xqYXZhL2xhbmcvU3RyaW5nO0xqYXZhL2xhbmcvaW52b2tlL01ldGhvZFR5cGU7TGphdmEvbGFuZy9pbnZva2UvTWV0aG9kVHlwZTtMamF2YS9sYW5nL2lu\ndm9rZS9NZXRob2RIYW5kbGU7TGphdmEvbGFuZy9pbnZva2UvTWV0aG9kVHlwZTspTGphdmEvbGFuZy9pbnZva2UvQ2FsbFNpdGU7AQAMSW5uZXJDbGFzc2Vz\nBwBlAQAlamF2YS9sYW5nL2ludm9rZS9NZXRob2RIYW5kbGVzJExvb2t1cAcAZwEAHmphdmEvbGFuZy9pbnZva2UvTWV0aG9kSGFuZGxlcwEABkxvb2t1cAAh\nABUAAgABAAwACQAaADIAMwABADQAAAACADUAGgA2ADcAAQA0AAAAAgA4ABoAOQA6AAEANAAAAAIAOwAaADwAPQABADQAAAACAD4AGgA/AEAAAQA0AAAAAgBB\nABoAQgBDAAEANAAAAAIARAAaAEYARwABADQAAAACAEgAGgBJAEoAAQA0AAAAAgBLABoATQBOAAEANAAAAAIAIAAFAAEABQAGAAEATwAAAB0AAQABAAAABSq3\nAAGxAAAAAQBQAAAABgABAAAABAABAAkABgABAE8AAAAtAAEAAgAAAA26AAcAAEwruQALAQCxAAAAAQBQAAAADgADAAAAEgAGABMADAAUAAEAUQAGAAEATwAA\nAFYAAwABAAAAKrIADwS2ABeyAA8QWLYAHbIADxIgtgAisgAPFAAltgAnsgAPFAAqtgAssQAAAAEAUAAAABoABgAAABcABwAYAA8AGQAXABoAIAAbACkAHAAJ\nAFIAUwABAE8AAAAnAAIAAQAAAAu7ABVZtwAvtgAwsQAAAAEAUAAAAAoAAgAAAB8ACgAgEAoAVAAGAAEATwAAACEAAgAAAAAACbIADxIxtgAisQAAAAEAUAAA\nAAYAAQAAABIAAwBVAAAAAgBWAFcAAAAMAAEAXAADAFgAWQBYAGMAAAAKAAEAZABmAGgAGQ==\n\"\"\"\n\n\nclass TestJclassScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def test_get_utf8_constants_n(self):\n with self.assertRaises(AttributeError):\n JclassScanner.get_utf8_constants(None)\n with self.assertRaises(struct.error):\n JclassScanner.get_utf8_constants(io.BytesIO(b''))\n self.assertListEqual([], JclassScanner.get_utf8_constants(io.BytesIO(AZ_DATA)))\n\n def test_get_utf8_constants_p(self):\n data = base64.b64decode(SAMPLE_B64)\n self.assertListEqual([\n 'java/lang/Object', '', '()V', 'run', '()Ljava/lang/Runnable;', 'java/lang/Runnable',\n 'java/lang/System', 'out', 'Ljava/io/PrintStream;', 'Sample', 'java/io/PrintStream', 'println', '(Z)V',\n '(C)V', 'bace4d19-beef-cafe-coo1-9129474bcd81', '(Ljava/lang/String;)V', '(J)V', '(D)V', 'JAVA_BOOLEAN',\n 'Z', 'ConstantValue', 'JAVA_CHAR', 'C', 'JAVA_BYTE', 'B', 'JAWA_SHORT', 'S', 'JAVA_INT', 'I', 'JAVA_LONG',\n 'J', 'JAVA_FLOAT', 'F', 'JAVA_DOUBLE', 'D', 'JAVA_STRING', 'Ljava/lang/String;', 'Code', 'LineNumberTable',\n 'log', 'main', '([Ljava/lang/String;)V', 'lambda$run$0', 'SourceFile', 'Sample.java', 'BootstrapMethods',\n 'java/lang/invoke/LambdaMetafactory', 'metafactory',\n ('(Ljava/lang/invoke/MethodHandles$Lookup;Ljava/lang/String;Ljava/lang/invoke/MethodType;'\n 'Ljava/lang/invoke/MethodType;Ljava/lang/invoke/MethodHandle;Ljava/lang/invoke/MethodType;'\n ')Ljava/lang/invoke/CallSite;'), 'InnerClasses', 'java/lang/invoke/MethodHandles$Lookup',\n 'java/lang/invoke/MethodHandles', 'Lookup'\n ], JclassScanner.get_utf8_constants(io.BytesIO(data[8:])))\n\n def test_match_p(self):\n # Valid Java class file signature (0xCAFEBABE)\n self.assertTrue(JclassScanner.match(b\"\\xCA\\xFE\\xBA\\xBE\"))\n self.assertTrue(JclassScanner.match(b\"\\xCA\\xFE\\xBA\\xBE\\x00\\x00\"))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n JclassScanner.match(None)\n with self.assertRaises(AttributeError):\n JclassScanner.match(1)\n # Too short\n self.assertFalse(JclassScanner.match(b\"\"))\n self.assertFalse(JclassScanner.match(b\"\\xCA\\xFE\\xBA\"))\n # Wrong signature\n self.assertFalse(JclassScanner.match(b\"\\xCA\\xFE\\xBA\\xBF\"))\n self.assertFalse(JclassScanner.match(b\"\\xBE\\xBA\\xFE\\xCA\"))\n" }, { "path": "tests/deep_scanner/test_jks_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.jks_scanner import JksScanner\n\n\nclass TestJksScanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid Java KeyStore signature\n self.assertTrue(JksScanner.match(b\"\\xFE\\xED\\xFE\\xED\"))\n self.assertTrue(JksScanner.match(b\"\\xFE\\xED\\xFE\\xED\\x00\\x00\"))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n JksScanner.match(None)\n with self.assertRaises(AttributeError):\n JksScanner.match(1)\n # Too short\n self.assertFalse(JksScanner.match(b\"\"))\n self.assertFalse(JksScanner.match(b\"\\xFE\\xED\\xFE\"))\n # Wrong signature\n self.assertFalse(JksScanner.match(b\"\\xFE\\xED\\xFE\\xEF\"))\n self.assertFalse(JksScanner.match(b\"\\xED\\xFE\\xED\\xFE\"))\n" }, { "path": "tests/deep_scanner/test_lzma_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.lzma_scanner import LzmaScanner\n\n\nclass TestLzmaScanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid LZMA signature (XZ format)\n self.assertTrue(LzmaScanner.match(b\"\\xFD7zXZ\\x00\"))\n # Valid LZMA signature (legacy format)\n self.assertTrue(LzmaScanner.match(b\"\\x5D\\x00\\x00\"))\n self.assertTrue(LzmaScanner.match(b\"\\xFD7zXZ\\x00\\x00\\x00\\x00\\x00\"))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n LzmaScanner.match(None)\n with self.assertRaises(AttributeError):\n LzmaScanner.match(1)\n # Too short\n self.assertFalse(LzmaScanner.match(b\"\"))\n self.assertFalse(LzmaScanner.match(b\"\\x5D\\x00\"))\n # Wrong signature\n self.assertFalse(LzmaScanner.match(b\"\\xFD7zXY\\x00\"))\n self.assertFalse(LzmaScanner.match(b\"\\x5D\\x00\\x01\"))\n self.assertFalse(LzmaScanner.match(b\"\\xFE7zXZ\\x00\"))\n" }, { "path": "tests/deep_scanner/test_mxfile_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.mxfile_scanner import MxfileScanner\n\n\nclass TestMxfileScanner(unittest.TestCase):\n\n def test_match_n(self):\n self.assertFalse(MxfileScanner.match(b\"\"))\n self.assertFalse(MxfileScanner.match(b\"\"))\n with self.assertRaises(AttributeError):\n MxfileScanner.match(None)\n with self.assertRaises(AttributeError):\n MxfileScanner.match(1)\n\n def test_match_p(self):\n self.assertTrue(MxfileScanner.match(b\"
    \"))\n" }, { "path": "tests/deep_scanner/test_pdf_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.pdf_scanner import PdfScanner\n\n\nclass TestPdfScanner(unittest.TestCase):\n\n def test_match_p(self):\n self.assertTrue(PdfScanner.match(b'\\x25\\x50\\x44\\x46\\x2D'))\n self.assertTrue(PdfScanner.match(b'%PDF-!'))\n\n def test_match_n(self):\n with self.assertRaises(AttributeError):\n self.assertFalse(PdfScanner.match(None))\n self.assertFalse(PdfScanner.match(b''))\n self.assertFalse(PdfScanner.match(b'%PDF+'))\n" }, { "path": "tests/deep_scanner/test_png_scanner.py", "content": "import base64\nimport unittest\n\nfrom credsweeper.deep_scanner.png_scanner import PngScanner\n\nsample_png_b64 = \"\"\"\niVBORw0KGgoAAAANSUhEUgAAAAgAAAAICAAAAADhZOFXAAAABGdBTUEAALGPC/xhBQAAAAFzUkdCAdnJLH8AAAAgY0hSTQAAeiYAAICEAAD6AAAAgOgAAHUw\nAADqYAAAOpgAABdwnLpRPAAAACx0RVh0Q29tbWVudABlN2RiYTljMS1kZWFkLWJlZWYtY2FmZS02MTM5NDc0YmNmODKLJWKsAAAAEElEQVQI12P8zwABTAwU\nMQBJQQEPsgmdYgAAAABJRU5ErkJggg==\n\"\"\"\n\n\nclass TestPngScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def test_match_n(self):\n with self.assertRaises(AttributeError):\n PngScanner.match(None)\n self.assertFalse(PngScanner.match(b''))\n\n def test_match_p(self):\n self.assertTrue(PngScanner.match(b'\\x89PNG\\r\\n\\x1a\\n'))\n self.assertTrue(PngScanner.match(base64.b64decode(sample_png_b64)))\n\n def test_yield_png_chunks_p(self):\n self.assertListEqual([(114, 'PNG_TEXT:Comment', b'e7dba9c1-dead-beef-cafe-6139474bcf82')],\n list(PngScanner.yield_png_chunks(base64.b64decode(sample_png_b64))))\n" }, { "path": "tests/deep_scanner/test_rtf_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.rtf_scanner import RtfScanner\n\nSIMPLE_SAMPLE = rb\"\"\"{\\rtf1\\ansi\\deff3\\adeflang1025\n{\\dbch\n\\u48708\\'3f\\u48128\\'3f\\u48264\\'3f\\u54840\\'3f}{\\loch\n:pR5!Db@}\n\\par }\"\"\"\n\n\nclass TestRtfScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def test_get_lines_n(self):\n self.assertListEqual([''], RtfScanner.get_lines(r\"{\\rtf1}\"))\n\n def test_get_lines_p(self):\n self.assertListEqual(['비밀번호:pR5!Db@', ''], RtfScanner.get_lines(SIMPLE_SAMPLE.decode()))\n" }, { "path": "tests/deep_scanner/test_sqlite3_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.sqlite3_scanner import Sqlite3Scanner\nfrom tests import SAMPLE_SQLITE\n\n\nclass TestSqlite3Scanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def test_walk_n(self):\n with self.assertRaises(TypeError):\n list(Sqlite3Scanner.walk_sqlite(None))\n\n def test_walk_p(self):\n self.assertListEqual([('KEYS', {\n 'ID': -1,\n 'KEY': None\n }),\n ('KEYS', {\n 'ID': 1,\n 'KEY': b'0\\x82\\x01=\\x02\\x01\\x00\\x02A\\x00\\xaf\\xa2\\x08\\xbf\\\\U\\xc2\\xb8`\\xa1'\n b'z~(\\xe5\\x03\\x84\\xbas\\x10\\xf8;]\\xa1\\xb6\\xbd\\xf1\\xda8\\x1d>'\n b'\\xf8\\x9c\\xd6\\x9e\\x9b\\xdf\\x8a.\\x01\\xa25s\\xae\\xb9\\t\\x8d\\xc1\\xc4\\x03O'\n b'{\\xe4))\\xd5\\xb2\\xa9\\xfe\\xcc\\x18\\xaf\\xca\\x87g\\x02\\x03'\n b'\\x01\\x00\\x01\\x02A\\x00\\x90P\\xc9uLN\\xdf\\xe8\\x96\\xe68\\xfb\\xcfh'\n b'\\x96\\xe2\\x8a> \\x94\\x88[`\\x95\\x030\\xe6\\xc9\\xb3&Z+Q\\x14\\x80Y\\xb6L'\n b\"O\\xff%-\\x93\\xca\\xf2\\xb0\\x0f\\xcc\\x9aQJ\\x03,'\\x86\\xca\\xab\\x87\"\n b'\\xf9JY\\xc2\\xcfq\\x02!\\x00\\xd8\\xcd\\x0f\\xdft-0-\\xa9\\xed/_\\xa0\\xbf\\x96'\n b'\\xdd\\xe9=\\x06\\xcb\\x8au\\x7fR\\xfb\\xf7M9\\xfb\\xae\\xe8Y\\x02!\\x00\\xcfcsB'\n b'\\x9fc\\xba\\xf53\\xdd\\x95a\\x81\\xf7\\xab\\xd36\\xd6\\x94\\xbcS\\xe7gR'\n b'\\x00\\\\\\xf0\\x01e\\x9e\\xf5\\xbf\\x02!\\x00\\xcd\\xf3W]\\xcd\\xaeS\\xb3=Vm\\x07i'\n b'\\xdc7\\x04M\\xdaDG=\\x1b\\xcb=X\\xd0\\x9f\\xd32-\\x00\\xd9\\x02!\\x00\\xa9P'\n b'W,\\x806\\x8a\\xcf_}\\xbbTu(@\\x16\\xdb\\x81\\x8a\\xc2\\xcayt\\xc7\\xe4\\xd5'\n b'\\xfbx\\x18\\x80\\x13\\xbf\\x02!\\x00\\xcc\\x88\\xf9P\\xdc\\xdf\\x85ni\\x80\\x9c'\n b'\\x0c\\x1f=F\\xfeq\\xfa\\x11\\xad%1)~\\xaeJ\\xadR\\x8aQ\\xd0\\x89'\n }),\n ('USERS', {\n 'ID': 1,\n 'PASSWORD': 'Dt1Js8m#1s',\n 'TOKEN': 'xoxa-FLYLIKEAGIREOGI-b1da04e31f',\n 'USER': '1d3e45d1-dead-beef-c0de-294622932701'\n }),\n ('USERS', {\n 'ID': 2,\n 'PASSWORD': 'password',\n 'TOKEN': '1d3e45d1deadbeefc0de29beda932701',\n 'USER': 'user'\n })], list(Sqlite3Scanner.walk_sqlite(SAMPLE_SQLITE.read_bytes())))\n" }, { "path": "tests/deep_scanner/test_strings_scanner.py", "content": "import unittest\n\nfrom hypothesis import given, strategies\n\nfrom credsweeper.deep_scanner.strings_scanner import StringsScanner\n\n\nclass TestStringsScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n @given(strategies.binary())\n def test_get_lines_hypothesis_n(self, data):\n self.assertIsNotNone(StringsScanner.get_enumerated_lines(data))\n\n def test_get_lines_n(self):\n self.assertListEqual([], StringsScanner.get_enumerated_lines(b''))\n self.assertListEqual([], StringsScanner.get_enumerated_lines(b'\\x00\\xBE'))\n self.assertListEqual([], StringsScanner.get_enumerated_lines(b'\\x9F\\xBEP\\xE3\\xb4W\\xA5:\\xF1R\\x9C00\\xcf\\x84t!'))\n self.assertListEqual([], StringsScanner.get_enumerated_lines(b'\\x00\\x01\\x02PW:R00t\\x0D\\x00'))\n\n def test_get_lines_p(self):\n self.assertListEqual([(3, \"PW:R00t!\")], StringsScanner.get_enumerated_lines(b'\\x00\\x01\\x02PW:R00t!\\x0D\\x00'))\n self.assertListEqual([(0, \"PW:R00t!\")], StringsScanner.get_enumerated_lines(b'PW:R00t!\\x0D\\x00'))\n self.assertListEqual([(4, \"PW:R00t!\")], StringsScanner.get_enumerated_lines(b'\\x00\\x01\\x02\\x03PW:R00t!'))\n self.assertListEqual(\n [(9, 'Salt:CwXD\\t3dsd'), (24, 'Token:SOMETEST')],\n StringsScanner.get_enumerated_lines(b'\\x9F\\xBEP\\xE3\\xb4W\\xA5:\\xFFSalt:CwXD\\x093dsd\\nToken:SOMETEST\\0'))\n" }, { "path": "tests/deep_scanner/test_struct_scanner.py", "content": "import unittest\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.common.constants import MAX_LINE_LENGTH, Severity\nfrom credsweeper.config.config import Config\nfrom credsweeper.deep_scanner.deep_scanner import DeepScanner\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\nfrom credsweeper.scanner.scanner import Scanner\nfrom credsweeper.utils.util import Util\n\n\nclass TestStructScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n # default config\n config = Util.json_load(APP_PATH / \"secret\" / \"config.json\")\n config[\"pedantic\"] = False\n config[\"depth\"] = 0\n config[\"doc\"] = False\n config[\"use_filters\"] = True\n config[\"find_by_ext\"] = False\n config[\"size_limit\"] = None\n config[\"severity\"] = Severity.LOW\n self.config = Config(config)\n self.scanner = DeepScanner(config=self.config, scanner=Scanner(self.config, None))\n\n def test_scan_n(self):\n provider = StructContentProvider(None)\n self.assertListEqual([], self.scanner.structure_scan(provider, 3, MAX_LINE_LENGTH))\n\n def test_scan_p(self):\n sample = {\n 'API': '\\t\\t\\t !!! \\r\\n', # strip does small value\n 'aUtH': b'\\t\\t\\t !!! \\r\\n', # bytes are not stripped,\n 'dummy': None,\n 'self': self,\n 'Certificate': 3.14,\n 'cReDeNtIaL': 42,\n 'PASSWORD': 'Dt1Js8m#1s',\n 'Nonce': b'9jY*g76f65D4d5rdy',\n 'Key': 'MII5cCI6NiIsInRIkpXV',\n 'salt': b\"\\t'\\xDE\\xAD\\xBE\\xEF,1\\012\\0\",\n 'key': 'Token',\n 'value': '\\t-dead-beef-c0de-\\n',\n }\n provider = StructContentProvider(sample)\n self.assertListEqual(\n [('Auth', 'aUtH', '\\\\t\\\\t\\\\t !!! \\\\r\\\\n', \"aUtH = b'\\\\t\\\\t\\\\t !!! \\\\r\\\\n'\"),\n ('Key', 'Key', 'MII5cCI6NiIsInRIkpXV', \"Key = 'MII5cCI6NiIsInRIkpXV'\"),\n ('Nonce', 'Nonce', \"9jY*g76f65D4d5rdy\", \"Nonce = b'9jY*g76f65D4d5rdy'\"),\n ('Password', 'PASSWORD', 'Dt1Js8m#1s', \"PASSWORD = 'Dt1Js8m#1s'\"),\n ('Salt', 'salt', \"\\\\t\\'\\\\xde\\\\xad\\\\xbe\\\\xef,1\\\\n\\\\x00\", 'salt = b\"\\\\t\\'\\\\xde\\\\xad\\\\xbe\\\\xef,1\\\\n\\\\x00\"'),\n ('Token', 'Token', '-dead-beef-c0de-', \"Token = '-dead-beef-c0de-'\")],\n sorted([(x.rule_name, x.line_data_list[0].variable, x.line_data_list[0].value, x.line_data_list[0].line)\n for x in self.scanner.structure_scan(provider, 3, MAX_LINE_LENGTH)]))\n" }, { "path": "tests/deep_scanner/test_tar_scanner.py", "content": "import base64\nimport unittest\nimport zlib\n\nfrom credsweeper.deep_scanner.tar_scanner import TarScanner\n\n\nclass TestTarScanner(unittest.TestCase):\n\n def test_match_p(self):\n # there is 10240 bytes of simple tar file\n tar_zlib_base64 = (b\"eJztzzEOwjAQBMCreYWfYIfEfk9eEMmY/2NRUoAoIoQ002xxW+yNvcfZ8lTr+szpNac1ylaWVuqWW41c8tKukfLpy6\"\n b\"b7bew9pejHMd71Pt3/1Hz+8usNAAAAAAAAAAAAfO8BVeUSWg==\")\n # there is a tar file with single file and without compression\n data = zlib.decompress(base64.b64decode(tar_zlib_base64))\n self.assertTrue(TarScanner.match(data))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(TypeError):\n TarScanner.match(None)\n with self.assertRaises(TypeError):\n TarScanner.match(1)\n # Too short\n self.assertFalse(TarScanner.match(b\"\"))\n self.assertFalse(TarScanner.match(b\"\\x00\" * 100))\n # Wrong magic\n tar_data = b\"\\x00\" * 512\n tar_data = tar_data[:257] + b\"wrong!\" + tar_data[263:]\n self.assertFalse(TarScanner.match(tar_data))\n" }, { "path": "tests/deep_scanner/test_tmx_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.tmx_scanner import TmxScanner\n\n\nclass TestTmxScanner(unittest.TestCase):\n\n def test_match_p(self):\n # Valid TMX format with ThreatModel tags\n tmx_data = b\"Some content\"\n self.assertTrue(TmxScanner.match(tmx_data))\n\n # Valid TMX format with KnowledgeBase tags\n tmx_data2 = b\"Some content\"\n self.assertTrue(TmxScanner.match(tmx_data2))\n\n # TMX format with additional content\n tmx_data3 = b\"Some prefix content some suffix\"\n self.assertTrue(TmxScanner.match(tmx_data3))\n\n def test_match_n(self):\n # Wrong data type\n with self.assertRaises(AttributeError):\n TmxScanner.match(None)\n with self.assertRaises(AttributeError):\n TmxScanner.match(1)\n # Missing or incomplete tags\n self.assertFalse(TmxScanner.match(b\"\"))\n self.assertFalse(TmxScanner.match(b\"\"))\n self.assertFalse(TmxScanner.match(b\"\"))\n self.assertFalse(TmxScanner.match(b\"\"))\n # Wrong order\n self.assertFalse(TmxScanner.match(b\"\"))\n self.assertFalse(TmxScanner.match(b\"\"))\n # Different tags\n self.assertFalse(TmxScanner.match(b\"content\"))\n self.assertFalse(TmxScanner.match(b\"content\"))\n" }, { "path": "tests/deep_scanner/test_xml_scanner.py", "content": "import unittest\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.deep_scanner.xml_scanner import XmlScanner\n\n\nclass TestXmlScanner(unittest.TestCase):\n\n def test_match_n(self):\n with self.assertRaises(TypeError):\n XmlScanner.match(None)\n self.assertFalse(XmlScanner.match(b''))\n self.assertFalse(XmlScanner.match(b\"!<>\"))\n self.assertFalse(XmlScanner.match(b\"\"))\n self.assertFalse(XmlScanner.match(b\"

    \"))\n self.assertFalse(XmlScanner.match(b\"
    \"))\n self.assertFalse(\n XmlScanner.match(bytearray(b'\\n' * MAX_LINE_LENGTH) + bytearray(b\" far far away\")))\n self.assertFalse(XmlScanner.match(b\" unmatched tags \"))\n self.assertFalse(XmlScanner.match(b\"\"))\n\n def test_match_p(self):\n self.assertTrue(XmlScanner.match(b\" matched tags \"))\n self.assertTrue(XmlScanner.match(b\"
    \"))\n self.assertTrue(\n XmlScanner.match(\n bytearray(b'\\n far far away ') + bytearray(b'\\n' * MAX_LINE_LENGTH) +\n bytearray(b' long long ago ')))\n" }, { "path": "tests/deep_scanner/test_zip_scanner.py", "content": "import unittest\n\nfrom credsweeper.deep_scanner.zip_scanner import ZipScanner\nfrom tests import AZ_DATA\n\n\nclass TestZipScanner(unittest.TestCase):\n\n def test_match_p(self):\n self.assertTrue(ZipScanner.match(b'PK\\003\\004'))\n # empty archive - no files\n self.assertTrue(ZipScanner.match(b'PK\\x05\\x06\\x00\\x00'))\n # not supported spanned archive (multi volume)\n self.assertFalse(ZipScanner.match(b'PK\\x07\\x08'))\n\n def test_match_n(self):\n # wrong data type\n with self.assertRaises(AttributeError):\n self.assertFalse(ZipScanner.match(None))\n with self.assertRaises(AttributeError):\n self.assertFalse(ZipScanner.match(1))\n # few bytes than required\n self.assertFalse(ZipScanner.match(b''))\n self.assertFalse(ZipScanner.match(b'P'))\n self.assertFalse(ZipScanner.match(b'PK'))\n self.assertFalse(ZipScanner.match(b'PK\\003'))\n # wrong signature\n self.assertFalse(ZipScanner.match(b'PK\\003\\003'))\n # plain text data\n self.assertFalse(ZipScanner.match(AZ_DATA))\n" }, { "path": "tests/deep_scanner/test_zlib_scanner.py", "content": "import contextlib\nimport itertools\nimport random\nimport sys\nimport unittest\nimport zlib\n\nimport pytest\nfrom hypothesis import given, strategies\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH, CHUNK_SIZE, CHUNK_STEP_SIZE\nfrom credsweeper.deep_scanner.zlib_scanner import ZlibScanner\nfrom tests import AZ_DATA\n\nZLIB_DATA = zlib.compress(AZ_DATA)\n\n\nclass TestZlibScanner(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n @given(strategies.binary())\n def test_match_hypothesis_n(self, data):\n # too hard to find random data which looks like zlib compressed data\n self.assertFalse(ZlibScanner.match(data))\n\n def test_match_p(self):\n self.assertTrue(ZlibScanner.match(b'(S)Ljava/lang/Short;'))\n self.assertTrue(ZlibScanner.match(ZLIB_DATA))\n self.assertTrue(ZlibScanner.match(b\"XG5FAKE\"))\n\n @given(strategies.binary())\n def test_decompress_hypothesis_n(self, data):\n # any data are over negative test limit\n with self.assertRaises(ValueError):\n ZlibScanner.decompress(-1, data)\n\n def test_decompress_static_n(self):\n with self.assertRaises(zlib.error):\n ZlibScanner.decompress(limit=MAX_LINE_LENGTH, data=AZ_DATA)\n with self.assertRaises(ValueError):\n ZlibScanner.decompress(limit=MAX_LINE_LENGTH, data=ZLIB_DATA + AZ_DATA)\n with self.assertRaises(ValueError):\n ZlibScanner.decompress(limit=10, data=b\"XG5FAKE\")\n with self.assertRaises(ValueError):\n ZlibScanner.decompress(limit=MAX_LINE_LENGTH, data=ZLIB_DATA[:-1])\n with self.assertRaises(ValueError):\n ZlibScanner.decompress(limit=1, data=ZLIB_DATA)\n\n def test_decompress_static_p(self):\n self.assertEqual(AZ_DATA, ZlibScanner.decompress(limit=MAX_LINE_LENGTH, data=ZLIB_DATA))\n\n # todo: fix when python 3.10 support ends\n @pytest.mark.skipif(10 == sys.version_info.minor, reason=\"zlib.compress was changed in 3.11\")\n def test_decompress_n(self):\n self.assertTrue(CHUNK_STEP_SIZE < CHUNK_SIZE < MAX_LINE_LENGTH)\n total_counter = check_counter = 0\n for level, wbits in itertools.product(list(range(10)), list(range(8, 32))):\n total_counter += 1\n data = random.randbytes(random.randint(CHUNK_SIZE, MAX_LINE_LENGTH))\n try:\n # check combinations which are valid\n zlib_data = zlib.compress(data, level=level, wbits=wbits)\n except zlib.error:\n continue\n with self.assertRaises((ValueError, zlib.error)):\n check_counter += 1\n ZlibScanner.decompress(CHUNK_STEP_SIZE, zlib_data)\n self.assertTrue(100 < check_counter < total_counter)\n\n # todo: fix when python 3.10 support ends\n @pytest.mark.skipif(10 == sys.version_info.minor, reason=\"zlib.compress was changed in 3.11\")\n def test_decompress_p(self):\n total_counter = check_counter = 0\n for level, wbits in itertools.product(list(range(10)), list(range(8, 32))):\n total_counter += 1\n data = random.randbytes(random.randint(0, MAX_LINE_LENGTH))\n with contextlib.suppress(zlib.error):\n # check combinations which are valid\n zlib_data = zlib.compress(data, level=level, wbits=wbits)\n self.assertEqual(data, ZlibScanner.decompress(MAX_LINE_LENGTH, zlib_data), str((level, wbits)))\n self.assertTrue(ZlibScanner.match(zlib_data))\n check_counter += 1\n self.assertTrue(10 < check_counter < total_counter)\n" }, { "path": "tests/file_handler/__init__.py", "content": "" }, { "path": "tests/file_handler/test_byte_content_provider.py", "content": "import os\nfrom typing import List\n\nimport pytest\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.utils.util import Util\nfrom tests import SAMPLES_FILES_COUNT, SAMPLES_PATH, AZ_DATA\nfrom tests.filters.conftest import DUMMY_DESCRIPTOR\n\n\nclass TestByteContentProvider:\n\n @pytest.mark.parametrize(\"lines_as_bytes,lines\",\n [(b\"line one\\npassword='in_line_2'\", [\"line one\", \"password='in_line_2'\"])])\n def test_get_analysis_target_p(self, lines_as_bytes: bytes, lines: List[str]) -> None:\n \"\"\"Evaluate that lines data correctly extracted from file\"\"\"\n content_provider = ByteContentProvider(lines_as_bytes)\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n expected_target = AnalysisTarget(0, lines, [x for x in range(len(lines))], DUMMY_DESCRIPTOR)\n\n assert len(analysis_targets) == 2\n\n target = analysis_targets[0]\n assert target.line == expected_target.line\n\n def test_byte_content_provider_p(self) -> None:\n files_counter = 0\n for dir_path, _, filenames in os.walk(SAMPLES_PATH):\n filenames.sort()\n for filename in filenames:\n files_counter += 1\n file_path = os.path.join(dir_path, filename)\n util_text = Util.read_file(file_path)\n with open(file_path, 'rb') as f:\n bin_data = f.read()\n provider = ByteContentProvider(bin_data)\n assert util_text == provider.lines\n assert files_counter == SAMPLES_FILES_COUNT\n\n def test_free_n(self) -> None:\n # free without cached properties invocation\n provider1 = ByteContentProvider(AZ_DATA)\n provider1.free()\n assert provider1.data is None\n assert len(provider1.lines) == 0\n provider1.free()\n # free after the invocation\n provider2 = ByteContentProvider(AZ_DATA)\n assert AZ_DATA == provider2.data\n assert len(provider2.lines) == 1\n provider2.free()\n assert provider2.data is None\n assert len(provider2.lines) == 0\n provider2.free()\n provider2.free()\n assert provider2.data is None\n assert len(provider2.lines) == 0\n" }, { "path": "tests/file_handler/test_data_content_provider.py", "content": "import json\nimport os\nimport tempfile\nimport unittest\nimport zipfile\nfrom typing import List\nfrom unittest.mock import patch\n\nfrom credsweeper.app import CredSweeper\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.file_handler.data_content_provider import DataContentProvider\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom tests import SAMPLES_FILES_COUNT, SAMPLES_PATH, AZ_DATA, SAMPLE_ZIP\nfrom tests.file_handler.zip_bomb_1 import zb1\nfrom tests.file_handler.zip_bomb_2 import zb2\n\n\nclass DataContentProviderTest(unittest.TestCase):\n WRONG_ZIP_FILE = b\"PK\\003\\004_WRONG_ZIP_FILE\"\n\n def test_wrong_xml_n(self) -> None:\n content_provider1 = DataContentProvider(data=b\"\")\n with patch('logging.Logger.debug') as mocked_logger:\n self.assertFalse(content_provider1.represent_as_xml())\n mocked_logger.assert_not_called()\n content_provider2 = DataContentProvider(data=AZ_DATA)\n with patch('logging.Logger.debug') as mocked_logger:\n self.assertFalse(content_provider2.represent_as_xml())\n mocked_logger.assert_called_with(\"Weak data to parse as XML\")\n content_provider3 = DataContentProvider(data=b\"\")\n with patch('logging.Logger.debug') as mocked_logger:\n self.assertFalse(content_provider3.represent_as_xml())\n mocked_logger.assert_called()\n\n def test_scan_wrong_provider_n(self) -> None:\n content_provider = DataContentProvider(b\"dummy\", \"dummy\")\n cs = CredSweeper(json_filename=\"dummy\")\n with self.assertRaises(NotImplementedError):\n cs.file_scan(content_provider)\n\n def test_scan_bottom_reach_n(self) -> None:\n content_provider = DataContentProvider(self.WRONG_ZIP_FILE, \"dummy\")\n cs = CredSweeper(json_filename=\"dummy\")\n self.assertEqual(0, len(cs.deep_scanner.recursive_scan(content_provider, 0, 1 << 16)))\n\n def test_scan_wrong_zip_data_n(self) -> None:\n content_provider = DataContentProvider(self.WRONG_ZIP_FILE, \"dummy\")\n cs = CredSweeper(json_filename=\"dummy\")\n self.assertEqual(0, len(cs.deep_scanner.recursive_scan(content_provider, 1, 1 << 16)))\n\n def test_scan_empty_zip_n(self) -> None:\n content_provider = DataContentProvider(\n b'PK\\x05\\x06\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00', \"dummy\")\n cs = CredSweeper(json_filename=\"dummy\")\n self.assertEqual(0, len(cs.deep_scanner.recursive_scan(content_provider, 1, 1 << 16)))\n\n def test_scan_zipfile_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n report_path = os.path.join(tmp_dir, \"report.json\")\n file_path = os.path.join(tmp_dir, \"test_n.zip\")\n self.assertFalse(os.path.exists(file_path))\n open(file_path, \"wb\").write(self.WRONG_ZIP_FILE)\n\n content_provider = FilesProvider([tmp_dir])\n cs = CredSweeper(json_filename=report_path, depth=1)\n\n file_extractors = content_provider.get_scannable_files(cs.config)\n self.assertEqual(1, len(file_extractors))\n scan_results = cs.file_scan(file_extractors[0])\n self.assertEqual(0, len(scan_results))\n self.assertFalse(os.path.isfile(report_path))\n\n def test_scan_zipfile_p(self) -> None:\n # create new zip archive with all samples\n with tempfile.TemporaryDirectory() as tmp_dir:\n report_path_1 = os.path.join(tmp_dir, \"report_1.json\")\n report_path_2 = os.path.join(tmp_dir, \"report_2.json\")\n\n cs = CredSweeper(json_filename=report_path_1, find_by_ext=True, depth=7)\n\n # calculate samples\n content_provider = FilesProvider([SAMPLES_PATH])\n file_extractors = content_provider.get_scannable_files(cs.config)\n self.assertLess(1, len(file_extractors))\n samples_scan_results: List[Candidate] = []\n for file_extractor in file_extractors:\n samples_scan_results.extend(cs.file_scan(file_extractor))\n len_samples_scan_results = len(samples_scan_results)\n self.assertLess(1, len_samples_scan_results)\n cs.credential_manager.set_credentials(samples_scan_results)\n cs.post_processing()\n cs.export_results()\n\n self.assertTrue(os.path.isfile(report_path_1))\n with open(report_path_1) as f:\n report = json.load(f)\n len_samples_report = len(report)\n self.assertTrue(1 < len_samples_report < len_samples_scan_results)\n\n # change the report file name\n cs.json_filename = report_path_2\n\n # clean credentials to test zip\n cs.credential_manager.candidates.clear()\n self.assertEqual(0, cs.credential_manager.len_credentials())\n\n # use the same approach but with single zip file which is made from the samples\n zip_file_path = os.path.join(tmp_dir, \"test_p.zip\")\n self.assertFalse(os.path.exists(zip_file_path))\n samples_file_count = 0\n with zipfile.ZipFile(zip_file_path, \"a\", zipfile.ZIP_DEFLATED, compresslevel=9) as zip_file:\n for dirpath, dirnames, filenames in os.walk(SAMPLES_PATH):\n for filename in filenames:\n filename_in_zip = f\"{samples_file_count}/{filename}\" if samples_file_count else filename\n with zip_file.open(filename_in_zip, \"w\") as output_file:\n with open(os.path.join(dirpath, filename), \"rb\") as input_file:\n output_file.write(input_file.read())\n samples_file_count += 1\n self.assertEqual(SAMPLES_FILES_COUNT, samples_file_count)\n content_provider = FilesProvider([zip_file_path])\n file_extractors = content_provider.get_scannable_files(cs.config)\n self.assertEqual(1, len(file_extractors))\n # single extractor\n zip_scan_results = cs.file_scan(file_extractors[0])\n # zip scan is used deep scan for source files too\n # so there might be a delta, because samples have tricky cases\n self.assertAlmostEqual(len_samples_scan_results, len(zip_scan_results), delta=3)\n\n cs.credential_manager.set_credentials(zip_scan_results)\n cs.post_processing()\n cs.export_results()\n\n self.assertTrue(os.path.isfile(report_path_1))\n with open(report_path_1) as f:\n report = json.load(f)\n len_samples_report = len(report)\n self.assertTrue(1 < len_samples_report < len_samples_scan_results)\n\n def test_scan_zipfile_size_limit_n(self) -> None:\n cs = CredSweeper()\n content_provider = DataContentProvider(open(SAMPLE_ZIP, \"rb\").read(), SAMPLE_ZIP)\n self.assertEqual(0, len(cs.deep_scanner.recursive_scan(content_provider, 3, 4)))\n\n def test_scan_zipfile_size_limit_p(self) -> None:\n cs = CredSweeper()\n content_provider = DataContentProvider(open(SAMPLE_ZIP, \"rb\").read(), SAMPLE_ZIP)\n self.assertEqual(1, len(cs.deep_scanner.recursive_scan(content_provider, 3, 1024)))\n\n def test_scan_zipfile_bomb_1_n(self) -> None:\n # create with depth to remove *.zip extension\n cs = CredSweeper(depth=2)\n content_provider = DataContentProvider(zb1, \"zip_bomb_1\")\n res_1 = cs.deep_scanner.recursive_scan(content_provider, 2, 1 << 30)\n self.assertEqual(0, len(res_1))\n\n def test_scan_zipfile_bomb_2_n(self) -> None:\n # create with depth to remove *.zip extension\n cs = CredSweeper(depth=4)\n content_provider = DataContentProvider(zb2, \"zip_bomb_2\")\n res_2 = cs.deep_scanner.recursive_scan(content_provider, 16, 1 << 16)\n self.assertEqual(0, len(res_2))\n\n def test_free_n(self) -> None:\n provider = DataContentProvider(AZ_DATA)\n self.assertEqual(AZ_DATA, provider.data)\n provider.free()\n self.assertIsNone(provider.data)\n provider.free()\n provider.free()\n" }, { "path": "tests/file_handler/test_diff_content_provider.py", "content": "import unittest\n\nfrom credsweeper.common.constants import DiffRowType\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom credsweeper.file_handler.diff_content_provider import DiffContentProvider, DiffDict, DiffRowData\n\n\nclass TestDiffContentProvider(unittest.TestCase):\n\n def test_get_analysis_target_p(self) -> None:\n \"\"\"Evaluate that added diff lines data correctly added to change_numbers\"\"\"\n file_path = \"dumy.file\"\n diff = [\n DiffDict({\n \"old\": None,\n \"new\": 2,\n \"line\": \"new line\",\n \"hunk\": 1\n }),\n DiffDict({\n \"old\": 2,\n \"new\": None,\n \"line\": \"moved line\",\n \"hunk\": 1\n })\n ]\n content_provider = DiffContentProvider(file_path, DiffRowType.ADDED, diff)\n\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n all_lines = [\"\", \"new line\", \"moved line\"]\n expected_target = AnalysisTarget(1, all_lines, [x for x in range(len(all_lines))],\n Descriptor(file_path, \".file\", DiffRowType.ADDED.value))\n\n self.assertEqual(1, len(analysis_targets))\n\n target = analysis_targets[0]\n self.assertEqual(expected_target.line, target.line)\n\n def test_get_analysis_target_n(self) -> None:\n \"\"\"Evaluate that deleted diff lines data correctly filtered for added change type\"\"\"\n file_path = \"dumy.file\"\n diff = [\n DiffDict({\n \"old\": 2,\n \"new\": None,\n \"line\": \"new line\",\n \"hunk\": 1\n }),\n DiffDict({\n \"old\": 3,\n \"new\": None,\n \"line\": \"moved line\",\n \"hunk\": 1\n })\n ]\n content_provider = DiffContentProvider(file_path, DiffRowType.ADDED, diff)\n\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n self.assertEqual(0, len(analysis_targets))\n\n def test_parse_lines_data_p(self) -> None:\n \"\"\"Evaluate that added diff lines data correctly added to change_numbers\"\"\"\n lines_data = [DiffRowData(DiffRowType.ADDED, 2, \"new line\")]\n\n change_numbs, _all_lines = DiffContentProvider.parse_lines_data(DiffRowType.ADDED, lines_data)\n\n expected_numbs = [2]\n\n self.assertListEqual(expected_numbs, change_numbs)\n\n def test_parse_lines_data_n(self) -> None:\n \"\"\"Evaluate that deleted diff lines data correctly filtered for added change type\"\"\"\n lines_data = [DiffRowData(DiffRowType.DELETED, 2, \"old line\")]\n\n change_numbs, _all_lines = DiffContentProvider.parse_lines_data(DiffRowType.ADDED, lines_data)\n\n expected_numbs = []\n\n self.assertListEqual(expected_numbs, change_numbs)\n\n def test_free_n(self) -> None:\n diff = [\n DiffDict({\n \"old\": 2,\n \"new\": None,\n \"line\": \"new line\",\n \"hunk\": 1\n }),\n DiffDict({\n \"old\": 3,\n \"new\": None,\n \"line\": \"moved line\",\n \"hunk\": 1\n })\n ]\n provider = DiffContentProvider(\"file_path\", DiffRowType.ADDED, diff)\n self.assertEqual(2, len(provider.diff))\n provider.free()\n self.assertEqual(0, len(provider.diff))\n provider.free()\n provider.free()\n\n def test_data_n(self) -> None:\n with self.assertRaises(NotImplementedError):\n _ = DiffContentProvider(\"file_path\", DiffRowType.ADDED, []).data\n" }, { "path": "tests/file_handler/test_file_path_extractor.py", "content": "import os.path\nimport re\nimport tempfile\nimport unittest\nfrom typing import List\nfrom unittest import mock\n\nimport git\nfrom humanfriendly import parse_size\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.file_path_extractor import FilePathExtractor\nfrom tests import AZ_STRING\n\n\nclass TestFilePathExtractor(unittest.TestCase):\n\n def setUp(self):\n config_dict = {\n \"size_limit\": None,\n \"find_by_ext\": False,\n \"find_by_ext_list\": [],\n \"doc\": False,\n \"pedantic\": False,\n \"depth\": 0,\n \"exclude\": {\n \"path\": [],\n \"pattern\": [],\n \"containers\": [],\n \"documents\": [],\n \"extension\": []\n },\n \"source_ext\": [],\n \"source_quote_ext\": [],\n \"bruteforce_list\": [],\n \"check_for_literals\": [],\n \"use_filters\": False,\n \"line_data_output\": [],\n \"candidate_output\": [],\n \"max_password_value_length\": 0,\n \"max_url_cred_value_length\": 0,\n }\n self.config = Config(config_dict)\n\n # excluded always not_allowed_path_pattern\n self.paths_not = [\"dummy.css\", \"tmp/dummy.css\", \"c:\\\\temp\\\\dummy.css\"]\n # pattern\n self.paths_reg = [\"tmp/Magic/dummy.Number\", \"/tmp/log/MagicNumber.txt\"]\n # \"/.git/\"\n self.paths_git = [\"C:\\\\.git\\\\dummy\", \"./.git/dummy.sample\", \"~/.git\\\\dummy.txt\"]\n # not excluded\n self.paths_src = [\"dummy.py\", \"/tmp/dummy.py\", \"tmp/dummy.py\", \"C:\\\\dummy.py\", \"temp\\\\dummy.py\"]\n # not excluded when --depth are set\n self.paths_pak = [\"dummy.gz\", \"/tmp/dummy.gz\", \"tmp/dummy.gz\", \"C:\\\\dummy.gz\", \"temp\\\\dummy.gz\"]\n # not excluded when --doc or --depth are set\n self.paths_doc = [\"dummy.pdf\", \"/tmp/dummy.pdf\", \"tmp/dummy.pdf\", \"C:\\\\dummy.pdf\", \"temp\\\\dummy.pdf\"]\n # extension to be excluded always\n self.paths_ext = [\"dummy.so\", \"dummy.so\", \"/tmp/dummy.so\", \"tmp/dummy.so\", \"C:\\\\dummy.so\", \"temp\\\\dummy.so\"]\n\n def tearDown(self):\n del self.config\n\n def test_apply_gitignore_p(self) -> None:\n \"\"\"Evaluate that code files would be included after filtering with .gitignore\"\"\"\n files = [\"file.py\", \"src/file.py\", \"src/dir/file.py\"]\n filtered_files = FilePathExtractor.apply_gitignore(files)\n self.assertSetEqual(set(files), set(filtered_files))\n\n def test_apply_gitignore_n(self) -> None:\n \"\"\"Evaluate that .gitignore correctly filters out files from project\"\"\"\n with tempfile.TemporaryDirectory() as tmp_dir:\n git.Repo.init(tmp_dir)\n with open(os.path.join(tmp_dir, \".gitignore\"), \"w\") as f:\n f.write(\".*\\n*.txt\\n*.log\\n*.so\")\n files = [\n os.path.join(tmp_dir, \".idea\"),\n os.path.join(tmp_dir, \".idea\", \"file1.txt\"),\n os.path.join(tmp_dir, \".idea\", \"dir\", \"file1.txt\"),\n os.path.join(tmp_dir, \".cache\"),\n os.path.join(tmp_dir, \"system.log\"),\n os.path.join(tmp_dir, \"src\", \"dir\", \"file.so\"),\n os.path.join(tmp_dir, \"src\", \"dir\", \"file.cpp\")\n ]\n filtered_files = FilePathExtractor.apply_gitignore(files)\n\n self.assertEqual(1, len(filtered_files))\n expected_path = os.path.join(tmp_dir, \"src\", \"dir\", \"file.cpp\")\n self.assertEqual(expected_path, filtered_files[0])\n\n def assert_true_check_exclude_file(self, paths: List[str]):\n for i in paths:\n self.assertTrue(FilePathExtractor.check_exclude_file(self.config, i), i)\n\n def assert_false_check_exclude_file(self, paths: List[str]):\n for i in paths:\n self.assertFalse(FilePathExtractor.check_exclude_file(self.config, i), i)\n\n def test_check_exclude_file_p(self) -> None:\n # matched only not_allowed_path_pattern\n self.config.exclude_containers = [\".gz\"]\n self.config.exclude_documents = [\".pdf\"]\n self.config.exclude_extensions = [\".so\"]\n self.config.exclude_paths = [\"/.git/\"]\n self.config.exclude_patterns = [re.compile(r\".*magic.*number.*\")]\n self.config.depth = 1\n self.config.doc = False\n self.assert_true_check_exclude_file(self.paths_not)\n self.assert_true_check_exclude_file(self.paths_reg)\n self.assert_true_check_exclude_file(self.paths_git)\n self.assert_false_check_exclude_file(self.paths_src)\n self.assert_false_check_exclude_file(self.paths_pak)\n self.assert_false_check_exclude_file(self.paths_doc)\n self.assert_true_check_exclude_file(self.paths_ext)\n\n # pdf should be not filtered\n self.config.depth = 0\n self.config.doc = True\n self.assert_true_check_exclude_file(self.paths_not)\n self.assert_true_check_exclude_file(self.paths_reg)\n self.assert_true_check_exclude_file(self.paths_git)\n self.assert_false_check_exclude_file(self.paths_src)\n self.assert_true_check_exclude_file(self.paths_pak)\n self.assert_false_check_exclude_file(self.paths_doc)\n self.assert_true_check_exclude_file(self.paths_ext)\n\n def test_check_exclude_file_n(self) -> None:\n # none of extension are in config, only not_allowed_path_pattern matches\n self.assert_true_check_exclude_file(self.paths_not)\n self.assert_false_check_exclude_file(self.paths_reg)\n self.assert_false_check_exclude_file(self.paths_git)\n self.assert_false_check_exclude_file(self.paths_src)\n self.assert_false_check_exclude_file(self.paths_pak)\n self.assert_false_check_exclude_file(self.paths_doc)\n self.assert_false_check_exclude_file(self.paths_ext)\n\n # matched only exclude_extensions\n self.config.exclude_containers = [\".gz\"]\n self.config.exclude_documents = [\".pdf\"]\n self.config.exclude_extensions = [\".so\"]\n self.assert_true_check_exclude_file(self.paths_not)\n self.assert_false_check_exclude_file(self.paths_reg)\n self.assert_false_check_exclude_file(self.paths_git)\n self.assert_false_check_exclude_file(self.paths_src)\n self.assert_true_check_exclude_file(self.paths_pak)\n self.assert_true_check_exclude_file(self.paths_doc)\n self.assert_true_check_exclude_file(self.paths_ext)\n\n def test_find_by_ext_file_p(self) -> None:\n self.config.find_by_ext = True\n self.config.find_by_ext_list = [\".p12\", \".jpg\"]\n self.assertTrue(FilePathExtractor.is_find_by_ext_file(self.config, \".p12\"))\n self.assertTrue(FilePathExtractor.is_find_by_ext_file(self.config, \".jpg\"))\n self.assertFalse(FilePathExtractor.is_find_by_ext_file(self.config, \".bmp\"))\n\n def test_find_by_ext_file_n(self) -> None:\n self.config.find_by_ext = False\n self.config.find_by_ext_list = [\".p12\", \".bmp\"]\n self.assertFalse(FilePathExtractor.is_find_by_ext_file(self.config, \".p12\"))\n self.assertFalse(FilePathExtractor.is_find_by_ext_file(self.config, \".bmp\"))\n self.assertFalse(FilePathExtractor.is_find_by_ext_file(self.config, \".jpg\"))\n\n @mock.patch(\"os.path.getsize\")\n def test_check_file_size_p(self, mock_getsize) -> None:\n mock_getsize.return_value = parse_size(\"11MiB\")\n self.config.size_limit = parse_size(\"10MiB\")\n self.assertTrue(FilePathExtractor.check_file_size(self.config, \"\"))\n\n @mock.patch(\"os.path.getsize\")\n def test_check_file_size_n(self, mock_getsize) -> None:\n mock_getsize.return_value = parse_size(\"11MiB\")\n self.config.size_limit = None\n self.assertFalse(FilePathExtractor.check_file_size(self.config, \"\"))\n self.config.size_limit = parse_size(\"11MiB\")\n self.assertFalse(FilePathExtractor.check_file_size(self.config, \"\"))\n\n def test_skip_symlink_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n sub_dir = os.path.join(tmp_dir, \"sub_dir\")\n os.mkdir(sub_dir)\n target_path = os.path.join(sub_dir, \"target\")\n with open(target_path, \"w\") as f:\n f.write(AZ_STRING)\n s_link_path = os.path.join(tmp_dir, \"s_link\")\n os.symlink(target_path, s_link_path)\n s_dir_path = os.path.join(tmp_dir, \"s_dir_link\")\n os.symlink(sub_dir, s_dir_path)\n\n dirs_walked = set()\n files_walked = set()\n for root, dirs, files in os.walk(tmp_dir):\n files_walked.update(files)\n dirs_walked.update(dirs)\n self.assertEqual({\"sub_dir\", \"s_dir_link\"}, dirs_walked)\n self.assertEqual({\"target\", \"s_link\"}, files_walked)\n\n paths = FilePathExtractor.get_file_paths(self.config, tmp_dir)\n self.assertEqual(1, len(paths))\n self.assertEqual(target_path, paths[0])\n" }, { "path": "tests/file_handler/test_files_provider.py", "content": "import io\nimport os\nimport tempfile\nimport unittest\nfrom pathlib import Path\nfrom unittest.mock import MagicMock, patch\n\nfrom credsweeper.common.constants import UTF_8, UTF_16_LE\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom tests import AZ_DATA, AZ_STRING\n\n\nclass TestFilesProvider(unittest.TestCase):\n\n def test_get_scannable_files_io_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n sample_path = os.path.join(tmp_dir, \"sample\")\n with open(sample_path, \"wb\") as f:\n az_data_utf16 = AZ_STRING.encode(UTF_16_LE)\n self.assertNotEqual(az_data_utf16, AZ_DATA)\n f.write(az_data_utf16)\n io_data = io.BytesIO(AZ_DATA)\n\n config = MagicMock()\n config.not_allowed_path_pattern.match.return_value = False\n config.exclude_patterns.return_value = []\n config.exclude_paths.return_value = []\n config.exclude_extensions.return_value = []\n config.depth.return_value = True\n\n file_providers_str = FilesProvider([str(sample_path)])\n file_text_providers_str = file_providers_str.get_scannable_files(config)\n self.assertEqual(1, len(file_text_providers_str))\n file_text_targets_str = [x for x in file_text_providers_str[0].yield_analysis_target(0)]\n self.assertEqual(1, len(file_text_targets_str))\n self.assertEqual(AZ_STRING, file_text_targets_str[0].line)\n\n file_providers_pathlib = FilesProvider([Path(sample_path)])\n file_text_providers_pathlib = file_providers_pathlib.get_scannable_files(config)\n self.assertEqual(1, len(file_text_providers_pathlib))\n file_text_targets_pathlib = [x for x in file_text_providers_pathlib[0].yield_analysis_target(0)]\n self.assertEqual(1, len(file_text_targets_pathlib))\n self.assertEqual(AZ_STRING, file_text_targets_pathlib[0].line)\n\n with patch(\"builtins.open\") as open_mock_str:\n text_provider_str_io = FilesProvider([(str(sample_path), io_data)])\n io_text_providers_str_io = text_provider_str_io.get_scannable_files(config)\n self.assertEqual(1, len(io_text_providers_str_io))\n io_text_targets_str_io = [x for x in io_text_providers_str_io[0].yield_analysis_target(0)]\n self.assertEqual(1, len(io_text_targets_str_io))\n self.assertEqual(AZ_STRING, io_text_targets_str_io[0].line)\n open_mock_str.assert_not_called()\n\n # return the cursor to begin\n io_data.seek(0, io.SEEK_SET)\n\n with patch(\"builtins.open\") as open_mock_io:\n text_provider_pathlib_io = FilesProvider([(Path(sample_path), io_data)])\n io_text_providers_pathlib_io = text_provider_pathlib_io.get_scannable_files(config)\n self.assertEqual(1, len(io_text_providers_pathlib_io))\n io_text_targets_pathlib_io = [x for x in io_text_providers_pathlib_io[0].yield_analysis_target(0)]\n self.assertEqual(1, len(io_text_targets_pathlib_io))\n self.assertEqual(AZ_STRING, io_text_targets_pathlib_io[0].line)\n open_mock_io.assert_not_called()\n\n # return the cursor again\n io_data.seek(0, io.SEEK_SET)\n\n with patch(\"builtins.open\") as open_mock_io:\n text_provider_io = FilesProvider([io_data])\n io_text_providers_io = text_provider_io.get_scannable_files(config)\n self.assertEqual(1, len(io_text_providers_io))\n io_text_targets_io = [x for x in io_text_providers_io[0].yield_analysis_target(0)]\n self.assertEqual(1, len(io_text_targets_io))\n self.assertEqual(AZ_STRING, io_text_targets_io[0].line)\n open_mock_io.assert_not_called()\n\n def test_get_scannable_files_io_n(self) -> None:\n io_data = io.BytesIO(AZ_DATA)\n config = MagicMock()\n provider = FilesProvider([io_data])\n self.assertEqual(1, len(provider.get_scannable_files(config)))\n config.assert_not_called()\n" }, { "path": "tests/file_handler/test_patches_provider.py", "content": "import io\nimport os\nimport tempfile\nfrom unittest.mock import patch\n\nfrom credsweeper.common.constants import DiffRowType, UTF_8\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.patches_provider import PatchesProvider\nfrom credsweeper.utils.util import Util\nfrom tests import SAMPLES_PATH\n\n\nclass TestPatchesProvider:\n\n def test_load_patch_data_p(self, config: Config) -> None:\n \"\"\"Evaluate base load diff file\"\"\"\n patch_file = SAMPLES_PATH / \"password.patch\"\n patch_provider = PatchesProvider([patch_file], DiffRowType.ADDED)\n\n raw_patches = patch_provider.load_patch_data(config)\n\n expected = [[\n 'diff --git a/.changes/1.16.98.json b/.changes/1.16.98.json', #\n 'new file mode 100644', #\n 'index 00000000..7ebf3947', #\n '--- /dev/null', #\n '+++ b/.changes/1.16.98.json', #\n '@@ -0,0 +1,4 @@', #\n '+{', #\n '+ \"category\": \"``cloudformation``\",', #\n '+ \"password\": \"dkajco1\"', #\n '+}', #\n '', #\n '' #\n ]]\n\n assert raw_patches == expected\n\n def test_load_patch_data_io_p(self, config: Config) -> None:\n \"\"\"Evaluate base load diff file with io.BytesIO\"\"\"\n patch_file = SAMPLES_PATH / \"password.patch\"\n data = Util.read_data(str(patch_file))\n io_data = io.BytesIO(data)\n patch_provider = PatchesProvider([io_data], DiffRowType.ADDED)\n\n raw_patches = patch_provider.load_patch_data(config)\n\n expected = [[\n 'diff --git a/.changes/1.16.98.json b/.changes/1.16.98.json', #\n 'new file mode 100644', #\n 'index 00000000..7ebf3947', #\n '--- /dev/null', #\n '+++ b/.changes/1.16.98.json', #\n '@@ -0,0 +1,4 @@', #\n '+{', #\n '+ \"category\": \"``cloudformation``\",', #\n '+ \"password\": \"dkajco1\"', #\n '+}', #\n '', #\n '' #\n ]]\n assert raw_patches == expected\n\n def test_load_patch_data_utf16_p(self, config: Config) -> None:\n \"\"\"Evaluate load diff file with UTF-16 encoding\"\"\"\n patch_file = SAMPLES_PATH / \"password_utf16.patch\"\n patch_provider = PatchesProvider([str(patch_file)], DiffRowType.ADDED)\n raw_patches = patch_provider.load_patch_data(config)\n expected = [[\n 'diff --git a/.changes/1.16.98.json b/.changes/1.16.98.json', #\n 'new file mode 100644', #\n 'index 00000000..7ebf3947', #\n '--- /dev/null', #\n '+++ b/.changes/1.16.98.json', #\n '@@ -0,0 +1,4 @@', #\n '+{', #\n '+ \"info\": \"난 차를 마십니다\"', #\n '+ \"category\": \"``cloudformation``\",', #\n '+ \"password\": \"dkajco1\"', #\n '+}', #\n '', #\n '' #\n ]]\n assert raw_patches == expected\n\n def test_load_patch_data_western_n(self, config: Config) -> None:\n \"\"\"Evaluate load diff file with Western encoding\"\"\"\n patch_file = SAMPLES_PATH / \"password_western.patch\"\n patch_provider = PatchesProvider([patch_file], DiffRowType.ADDED)\n\n with patch('logging.Logger.debug') as mocked_logger:\n raw_patches = patch_provider.load_patch_data(config)\n mocked_logger.assert_called_with(\"UnicodeError: Can't decode content as %s.\", UTF_8)\n\n expected = [[\n 'diff --git a/.changes/1.16.98.json b/.changes/1.16.98.json', #\n 'new file mode 100644', #\n 'index 00000000..7ebf3947', #\n '--- /dev/null', #\n '+++ b/.changes/1.16.98.json', #\n '@@ -0,0 +1,4 @@', #\n '+{', #\n '+ \"category\": \"``cloudformation``\",', #\n '+ \"password\": \"dkajcö1\"', #\n '+}', #\n '', #\n '' #\n ]]\n assert raw_patches == expected\n\n def test_load_patch_data_n(self, config: Config) -> None:\n \"\"\"Evaluate warning occurrence while load diff file with ISO-IR-111 encoding\"\"\"\n patch_file = SAMPLES_PATH / \"iso_ir_111.patch\"\n patch_provider = PatchesProvider([str(patch_file)], DiffRowType.ADDED)\n\n with patch('logging.Logger.debug') as mocked_logger:\n raw_patches = patch_provider.load_patch_data(config)\n mocked_logger.assert_called_with(\"UnicodeError: Can't decode content as %s.\", UTF_8)\n\n expected = [[\n 'ëÉÒÉÌÌÉÃÁ', #\n 'diff --git a/.changes/1.16.98.json b/.changes/1.16.98.json', #\n 'new file mode 100644', #\n 'index 00000000..7ebf3947', #\n '--- /dev/null', #\n '+++ b/.changes/1.16.98.json', #\n '@@ -0,0 +1,4 @@', #\n '+{', #\n '+ \"category\": \"``cloudformation``\",', #\n '+ \"password\": \"dkajco1\"', #\n '+}', #\n '', #\n '' #\n ]]\n assert raw_patches == expected\n\n def test_oversize_n(self, config: Config) -> None:\n \"\"\"Evaluate warning occurrence while load oversize diff file\"\"\"\n # use UTF-16 encoding to prevent any Windows style transformation\n patch_file = SAMPLES_PATH / \"password_utf16.patch\"\n patch_provider = PatchesProvider([str(patch_file)], DiffRowType.ADDED)\n\n config.size_limit = 0\n with patch('logging.Logger.warning') as mocked_logger:\n raw_patches = patch_provider.load_patch_data(config)\n mocked_logger.assert_called_with(\"Size (%s) of the file '%s' is over limit (%s)\", 512, str(patch_file), 0)\n\n assert isinstance(raw_patches, list)\n assert len(raw_patches) == 0\n\n def test_memory_error_n(self, config: Config) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n patch_file = os.path.join(tmp_dir, \"test.patch\")\n assert not os.path.exists(patch_file)\n with open(patch_file, \"w\") as f:\n f.write(\"\"\"diff --git a/creds.py\n@@ -00000000000000000000000000000000000000000000000000000000000000000000000000000000000000002985304056119834851 +1,4 @@\n+{\n+ \"wrong diff\",\n+ \"sword\": \"FISH\"\n+ t............................................. li.k re...o0i:api........///:..N&.@........00000000..7ebf3947\n--- /dev/null\n+++ b/.changes.........json\n@@ -0,0 +1,4 @@\n+{\n+ correct\n+ lines\n\n\"\"\")\n patch_provider = PatchesProvider([str(patch_file)], DiffRowType.ADDED)\n with patch('logging.Logger.error') as mocked_logger:\n test_files = patch_provider.get_scannable_files(config)\n assert len(test_files) == 1\n targets = [x for x in test_files[0].yield_analysis_target(0)]\n assert len(targets) == 7\n mocked_logger.assert_not_called()\n\n def test_overflow_error_n(self, config: Config) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n patch_file = os.path.join(tmp_dir, \"test.patch\")\n assert not os.path.exists(patch_file)\n with open(patch_file, \"w\") as f:\n f.write(\"\"\"OverflowError\ndiff --git a/.changes/1.16.98.json b/.changes/1.16.98.json\nnew file mode 100644\nindex 00000000..7ebf3947\n--- /dev/null\n+++ b/.changes/1.16.98.json\n@@ -0,0 +12345678901234567890,12345678901234567894 @@\n+{\n+ \"category\": \"``cloudformation``\",\n+ \"password\": \"dkajco1\"\n+}\n\n\n\"\"\")\n patch_provider = PatchesProvider([str(patch_file)], DiffRowType.ADDED)\n with patch('logging.Logger.error') as mocked_logger:\n test_files = patch_provider.get_scannable_files(config)\n assert len(test_files) == 1\n targets = [x for x in test_files[0].yield_analysis_target(0)]\n assert len(targets) == 4\n mocked_logger.assert_not_called()\n" }, { "path": "tests/file_handler/test_string_content_provider.py", "content": "import unittest\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom tests import AZ_STRING\nfrom tests.filters.conftest import DUMMY_DESCRIPTOR\n\n\nclass TestStringContentProvider(unittest.TestCase):\n\n def test_get_analysis_target_p(self) -> None:\n \"\"\"Evaluate that lines data correctly extracted from file\"\"\"\n lines = [\"line one\", \"password='in_line_2'\"]\n content_provider = StringContentProvider(lines)\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n self.assertEqual(len(lines), len(analysis_targets))\n\n expected_target = AnalysisTarget(0, lines, [1, 2], DUMMY_DESCRIPTOR)\n self.assertEqual(expected_target.line, analysis_targets[0].line)\n # check second target and line numeration\n expected_target = AnalysisTarget(1, lines, [1, 2], DUMMY_DESCRIPTOR)\n self.assertEqual(expected_target.line, analysis_targets[1].line)\n\n # specific line numeration\n content_provider = StringContentProvider(lines, [42, -1])\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n self.assertEqual(42, analysis_targets[0].line_num)\n self.assertEqual(-1, analysis_targets[1].line_num)\n\n def test_get_analysis_target_n(self) -> None:\n \"\"\"Negative cases check\"\"\"\n # empty list\n content_provider = StringContentProvider([])\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n self.assertEqual(0, len(analysis_targets))\n\n # mismatched amount of lists\n content_provider = StringContentProvider([\"a\", \"b\", \"c\"], [2, 3])\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n self.assertEqual(3, len(analysis_targets))\n self.assertEqual(1, analysis_targets[0].line_num)\n self.assertEqual(2, analysis_targets[1].line_num)\n self.assertEqual(3, analysis_targets[2].line_num)\n\n content_provider = StringContentProvider([\"a\", \"b\", \"c\"], [5, 3, 4, 5])\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n self.assertEqual(3, len(analysis_targets))\n self.assertEqual(1, analysis_targets[0].line_num)\n self.assertEqual(2, analysis_targets[1].line_num)\n self.assertEqual(3, analysis_targets[2].line_num)\n\n def test_free_n(self) -> None:\n provider = StringContentProvider([AZ_STRING])\n provider.free()\n self.assertListEqual([], provider.lines)\n provider.free()\n provider.free()\n\n def test_data_n(self) -> None:\n with self.assertRaises(NotImplementedError):\n _ = StringContentProvider([AZ_STRING]).data\n" }, { "path": "tests/file_handler/test_struct_content_provider.py", "content": "import unittest\n\nfrom credsweeper.file_handler.struct_content_provider import StructContentProvider\n\n\nclass TestStructContentProvider(unittest.TestCase):\n\n def test_free_n(self) -> None:\n provider = StructContentProvider({})\n provider.free()\n self.assertIsNone(provider.struct)\n provider.free()\n provider.free()\n\n def test_data_n(self) -> None:\n with self.assertRaises(NotImplementedError):\n _ = StructContentProvider({}).data\n" }, { "path": "tests/file_handler/test_text_content_provider.py", "content": "import os\nimport tempfile\nimport unittest\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.descriptor import Descriptor\nfrom credsweeper.file_handler.text_content_provider import TextContentProvider\nfrom tests import SAMPLES_PATH\n\n\nclass TestTextContentProvider(unittest.TestCase):\n\n def test_get_analysis_target_p(self) -> None:\n \"\"\"Evaluate that lines data correctly extracted from file\"\"\"\n target_path = SAMPLES_PATH / \"password.gradle\"\n content_provider = TextContentProvider(target_path)\n\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n all_lines = ['password = \"cackle!\"', '']\n expected_target = AnalysisTarget(0, all_lines, [x for x in range(len(all_lines))],\n Descriptor(str(target_path), target_path.suffix, \"\"))\n\n self.assertEqual(6, len(analysis_targets))\n\n target = analysis_targets[0]\n self.assertEqual(expected_target.line, target.line)\n\n target_path = SAMPLES_PATH / \"xml_password.xml\"\n content_provider = TextContentProvider(target_path)\n\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n all_lines = [\n \"Countries : \",\n \"Country : \",\n \"City : Seoul\",\n \"password : cackle!\",\n \"Country : \",\n \"City : Kyiv\",\n \"password : peace_for_ukraine\",\n \"password : Password for authorization\\n BAIT: bace4d59-fa7e-beef-cafe-9129474bcd81\",\n ]\n expected_target = AnalysisTarget(3, all_lines, [x for x in range(len(all_lines))],\n Descriptor(str(target_path), \".xml\", \"\"))\n\n self.assertEqual(8, len(analysis_targets))\n\n target = analysis_targets[3]\n self.assertEqual(expected_target.line, target.line)\n\n def test_get_analysis_target_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n target_path = os.path.join(tmp_dir, \"test_get_analysis_target_n.xml\")\n\n with open(target_path, \"w\") as f:\n f.write(\"crackle!\")\n\n content_provider = TextContentProvider(target_path)\n\n analysis_targets = [x for x in content_provider.yield_analysis_target(0)]\n\n all_lines = [\"crackle!\"]\n expected_target = AnalysisTarget(0, all_lines, [x for x in range(len(all_lines))],\n Descriptor(target_path, \".xml\", \"\"))\n\n self.assertEqual(1, len(analysis_targets))\n\n target = analysis_targets[0]\n self.assertEqual(expected_target.line, target.line)\n\n def test_free_n(self) -> None:\n provider = TextContentProvider(\"dummy\")\n provider.free()\n self.assertListEqual([], provider.lines)\n provider.free()\n provider.free()\n" }, { "path": "tests/file_handler/zip_bomb_1.py", "content": "zb1 = b'PK\\x03\\x04\\x14\\x00\\x02\\x00\\x08\\x00\\x1b\\xad|(\\x93u\\xdc\\xc8\\xf9\\t\\x00\\x00V\\x88\\x00\\x00\\t\\x00\\x00\\x00lib ' \\\n b'3.zip\\xed\\xddWPS\\xdb\\x1a\\x07\\xf0H\\x118t\\x95C\\x00\\xb1Q\"H\\x95\\x1a\\xc4\\xa0\\xdc#\\xbd\\tH\\x95b(' \\\n b'Q\\x8a\\xe8\\r-\\x14+G\\xe9\\x10\\x01)F\\x94\\x8e(QDz\\xb3%\\xa0 \\x08\\xa2 ' \\\n b'RT\\x04\\xa4\\xb7C\\t\\x88\\x1c\\xbd\\x8e\\xf7\\xc6\\x87373y\\xfd\\xf6~X{\\xcd\\xda\\xff\\xf9^\\x7f\\xb3\\xf7*\\x16\\xc6\\xacl[\\x10,' \\\n b'\\x08ND\\xdb\\x9d\\xb0\\xddT\\xd7\\xf1\\r\\x92\\x9c\\x08\\xc4F<\\x02\\xf1\\x1b\\x02\\x81\\xc0\\xfa\\xf9y\\xefPQ\\x089qj\\xb2\\xcf[' \\\n b'\\xd3zu\\x1b\\xc7\\x8c\\x14%j+\\x97\\x90D\\xaa\\xb4\\x04:9\\xd4=\\xb7\\xe3O\\xc1@\\xa4\\xe0\\xae\\n\\x11\\x93)\\xa1\\xac\\xba\\xed' \\\n b'\\x96\\x81\\xe4Fy\\xd3\\x08I\\xc7M\\xff\\xe6\\xefK.q\\xa2J%y?\\xae\\xf4I\\x15\\xac\\xba4Jj%\\x9cnun\\xc3g\\xe2\\x9co\\xd0\\x8a\\x17' \\\n b'\\xb0\\xfb\\x1bF\\xd6\\xd7\\xc9\\x0bs\\xa5\\x99\\x01\\xb4\\xb5\\x17\\\\\\xb5\\xd7(' \\\n b'\\x89\\xa6M.\\x89\\xdd\\x17\\x12\\xd7\\x90Oz:\\xf40l\\x86\\\\\\x87\\x04v\\xb2\\x1d$\\x19\\x9aa6\\x90\\xcf\\xdc\\x17\\x95}\\xe4' \\\n b'~#}\\x83y\\\\\\xee\\x8e[\\xb6\\xf8\\xfd\\x81\\x8a&\\xf9\")&\\xd9\\xbe\\xc2\\xad\\x96Ra\\x05\\xb8\\x0bu\\x1f\\xf79Jd\\xe7\\x16\\x1a' \\\n b'\\x04Kxh\\x1cNO[{0t\\xcb\\x8b\\x1cU\\xdb\\x94w[' \\\n b'\\x10]\\xbfh\\xa4\\x97#\\xd3hgZ\\x93\\x13T\\xa0E\\xc8\\xbb\\\\\\x14\\xaah\\x8a\\x9a\\xaa\\xc6,' \\\n b'\\xb6\\x86N\\xd4\\xd7\\\\\\xec\\xb7\\xd5\\xde\\xef\\x9bB\\x9e?\\xa0\\x7f\\xfd\\xebB\\r\\xcf\\x99\\xedd\\xb3\\xecXsL~.\\xcd,' \\\n b'(\\x95\\xb5\\x9c\\xd3;\\xd9c[\\xb8\\xad\\xca]\\x9f\\x86\\xee\\xe9\\x0f:KG\\x1c\\xadX\\x91\\xfcZ8r\\xc5\\xca&\\xf3\\x10\\x13\\x87[' \\\n b'\\xb1\\xca!\\xb6\\x1e\\n\\x16\\x9e\\x1a{\\xde\\x18kW=5\\xb86\\xe9\\xaa\\xf4q\\x96O\\x8c\\xf5\\xd3\\xb5\\x82\\xd4\\xc0\\xd4\\x1a\\x0b' \\\n b'\\xaf\\x89/\\x89\\xc2\\xd5AM\\x9b\\xfb\\x1f\\xf9\\n\\x0ft\\x14\\xb0\\xb4\\xf1\\xbd,kF\\x9a\\x97\\xe1t\\xecr7R\\x85\\r\\x0b)\\xe1{' \\\n b'\\xf9\\x9a\\xbd\\xaeo\\x9eS\\xb0\\xf5\\xe8q\\xf4\\x1fw\\x19B\\xc5~\\xde\\xb2\\xc2\\x96L\\xb2\\xa9)\\xb87&\\x17\\xe8\\x85\\xcd\\xc29' \\\n b'\\xa0\\x8aK\\xd1\\xaer\\xfb\\xd1\\xca\\xc1\\xb4\\xfb.\\x1f\\xfb\\x89\\xe7\\xc3\\x83\\xf6\\x98\\xa9(x\\x1d\\xcf\\xbf4,' \\\n b'\\x9d\\xa1\\x10\\xb9\\xb5\\\\m\\xe7\\xf5\\xe6\\xfa0k\\xa2\\x83\\x92\\xda\\xe2W\\xe7\\xd1Uwc\\xab?W\\xa4\\xbdK\\xe4m&3\\xd8YJ\\x9c' \\\n b'\\x1dep\\xb9\\x17\\xf66\\xbd\\xb3_\\x9b\\x1d\\xa7MQndO\\xf0\\xd5m\\xb1\\xeaq\\xd1\\xdf\\xdd\\x90v\\xa8j\\xa6J\\xd1\\x8f\\xbax7k0~5' \\\n b'\\x1e\\x93\\x1b~:\\xf6\\xcb\\x97\\xfc\\xf6+}\\x7f\\xa5\\xa1\\xd0\\xa3\\xd8M}<.\\xc7%\\x17\\x8c:\\x94dvk\\xce\\x18{' \\\n b'K5\\x9c\\xe8+Ogu\\x8bM\\t\\x89k\\xa0\\xf9\\xbdO\\xc1\\x8b\\xa9\\xdfi\\xe3\\x92\\xa3V-\\x9a\\xd5K\\xf4\\x1d\\r\\x93\\x1c\\xb6\\xd5' \\\n b'\\xd0Q\\xc58\\xd3\\xdc\\x8b\\x0cxP\\xaac\\x96\\x96\\xc7G\\xdb\\xed\\xfc\\xafS\\xad\\x89\\x8f\\x15_wFy\\x06\\xf7\\xfaZ&-4_\\x97(' \\\n b'\\x0f\\xc9\\xd3\\xba\\xc5\\xafo\\xc8\\x83\\x9b4\\xbe\\x8aS\\xac\\xcfx\\xc9\\xb3b\\xfe\\xf6\\xed\\xc5Y\\x94\\xee\\x96\\xa9\\xc2\\x85' \\\n b'\\xbb\\xc5H?\\xaa\\xc9\\xd5\\x97\\xb63|j\\xe2\\xa9\\xb8\\xd2\\x8b\\\\\\x998[' \\\n b'q}v\\xb2d\\x89\\x9dsh\\xad>\\xafl/vk\\xf3\\n\\xeb\\xcc\\xa3]\\x8a\\xf8\\xb0 ' \\\n b'\\x92A\\xeat\\x81>\\x17\\'o\\x8c\\xb5r\\x03\\xe9\\xd9R\\x9fP@\\xc4\\x159{' \\\n b'!\\xd4H$\\xfe\\x84\\x0bw\\x85\\x98=9\\xdb\\xa4\\xedYoh\\x95\\x05\\xb2\\xfc\\xd3\\xe3\\xa6$\\x8ac\\xd0\\xbd\\x1e\\xf9>\\x99n\\xeaE' \\\n b'\\x8e\\x14\\xa3\\x93\\xbe\\x15xr>A\\xe4\\xb6\\x1a\\xba\\xb7\\xbf\\xa7\\xcbm\\x80\\xb6c*a\\x7f\\xfb;\\x1bgTD\\x0c\\xf6\\xd9\\x97\\x96' \\\n b'*n\\xe2|w\\xdd\\xb57\\xbb\\x1aB%\\xdd\\x9dc\\xf0\\xaa\\x1ej\\xc9\\xcb\\xfb\\xf6\\x99W\\xc6\\x91D\\xd7\\x9e}\\xaa\\xe0\\xb7W\\xd7' \\\n b'\\x8f{\\x15_6\\xf4<\\xa5\\xab\\xdb\\xaf]\\xcbr\\xc7\\x88\\x03\\xa9\\xe7\\xa6\\xa5\\xcd\\x81\\xc6\\xda\\'\\x0f\\x8c\\x1dKO]\\xcax\\xbc3' \\\n b'\\xbao\\xb2\\xd2\\xbc\\xf3\\x18v\\xfd\\xbd\\x93\\xd8\\xad\\x161\\xde\\xfcp\\xc15qB\\xe6\\xe9,U\\x93,' \\\n b'\\xe5\\xbccE\\x85\\x01\\x89\\xcf\\n\\xdd\\xba\\xcf\\x1a:\\xfaXS\\xe5s?\\xd3\\\\9\\xd9\\xbb\\xe2\\xef\\xea\\xe8\\xe4e\\\\J\\xc1s\\xc7' \\\n b'/\\x97\\x9dL\\xcdG\\x13\\xdaQ6\\xad:#\\x94n\\xaf%j\\x01u\\xeb\\x99\\xd5\\x9d\\xaf\\xf6>/}X\\xc1Ril\\xd31D$\\x94\\xccEa\\x1a\\x91u' \\\n b'\\xe3G\\x84r\\xc3\\xea*i(\\x8ai\\xe7\\x91Wnyc\\xd5\\xb2\\xbe\\xda\\xc8\\x1b\\xf5\\xb8zI\\x87\\xd7\\xd1Y\\xf6w\\x88\\x92\\xe9.\\x15' \\\n b'\\x16\\xea\\x9egx\\twz3N\\x1b\\x0c\\x1c\\xf1]v\\xf3P\\rh\\t\\xacZ%y\\xc9\\x1dT\\x92Y\\xf3\\x14\\xd6\\xd3\\x14\\xdd\\xe7\\xfa\\xf9\\xbd' \\\n b'\\x0b\\xb5Z\\xcev\\xbd\\x10]\\x91\\x94\"\\x97i\\xb7\\xa7/\\xbd\\xbf\\xbdF\\x13\\x15\\x97g\\xdey\\x99b$\\x1b\\xd7\\x1d\\xde\\xac\\x86e' \\\n 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b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1a!\\x00\\x005EPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05' \\\n b'\\xb7\\xf4;\\xc8UU\\x00\\x00\\xa1GM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00?!\\x00\\x005FPK\\x01' \\\n b'\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xeaN\\xedc0U\\x00\\x00\\x81GM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00d!\\x00\\x005GPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xb7\\xd9\\x99?\\x0bU' \\\n b'\\x00\\x00aGM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x89!\\x00\\x005HPK\\x01\\x02\\x14\\x00\\x14' \\\n b'\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\x9a\\xec\\x13\\xef\\xe6T\\x00\\x00AGM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\xae!\\x00\\x005IPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05~\\x94\\x0e\\xf1\\xc1T\\x00\\x00' \\\n b'!GM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xd3!\\x00\\x005JPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00' \\\n b'\\x00\\x08\\x00\\xa0lH\\x05\\x08\\x99\\xd0\\xf7\\x9cT\\x00\\x00\\x01GM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\xf8!\\x00\\x005KPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\x8e\\x14\\xb2bwT\\x00\\x00\\xe1FM\\x01' \\\n b'\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1d\"\\x00\\x005LPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08' \\\n b'\\x00\\xa0lH\\x05\\xa11\\x03\\xa6RT\\x00\\x00\\xc1FM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00B\"\\x00' \\\n b'\\x005MPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\x8aS\\xa4\\xcd-T\\x00\\x00\\xa1FM\\x01\\x02\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00g\"\\x00\\x005NPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\x9d' \\\n b'\\x0e\\xe9\\xdf\\x08T\\x00\\x00\\x81FM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8c\"\\x00\\x005OPK' \\\n b'\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\x1b\\rI\\xaa\\xe3S\\x00\\x00aFM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xb1\"\\x00\\x005PPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05k\\x03Gz\\xbeS' \\\n b'\\x00\\x00AFM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xd6\"\\x00\\x005QPK\\x01\\x02\\x14\\x00\\x14' \\\n b'\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xca0\\xb4\\xa5\\x99S\\x00\\x00!FM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\xfb\"\\x00\\x005RPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05,' \\\n b'^\\xb9JtS\\x00\\x00\\x01FM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00 ' \\\n b'#\\x00\\x005SPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xf3\\x1e\\x07\\xfcOS\\x00\\x00\\xe1EM\\x01\\x02\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00E#\\x00\\x005TPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH' \\\n b'\\x05Oo\\x8c\\x8a*S\\x00\\x00\\xc1EM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00j#\\x00\\x005UPK\\x01' \\\n b'\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xcb?~\\x93\\x05S\\x00\\x00\\xa1EM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8f#\\x00\\x005VPK\\x01\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05\\xf4,' \\\n b'\\x82\\xf1\\xe0R\\x00\\x00\\x81EM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xb4#\\x00\\x005WPK\\x01' \\\n b'\\x02\\x14\\x00\\x14\\x00\\x00\\x00\\x08\\x00\\xa0lH\\x05Q\\xbaZ\\x17\\xbbR\\x00\\x00aEM\\x01\\x02\\x00\\x00\\x00\\x00\\x00\\x00\\x00' \\\n b'\\x00\\x00\\x00\\x00\\x00\\x00\\xd9#\\x00\\x005XPK\\x05\\x06\\x00\\x00\\x00\\x00\\xfa\\x00\\xfa\\x00\\xbc.\\x00\\x00\\xb4v\\x00\\x00' \\\n b'\\x00\\x00 '\n" }, { "path": "tests/filters/__init__.py", "content": "" }, { "path": "tests/filters/conftest.py", "content": "import re\n\nimport pytest\n\nfrom credsweeper.common.keyword_pattern import KeywordPattern\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.file_handler.descriptor import Descriptor\n\nsuccess_line_list = [ #\n \"\\\"passwd\\\": \\\"Crackle4421\\\"\", #\n \"passwd = Crackle4421\", #\n \"passwd = 'Crackle4421'\", #\n \"passwd='''MyP@5$word''';\", #\n 'passwd=\"\"\"MyP@5$word\"\"\";', #\n \"passwd = 'Crackle4421'\", #\n \"export passwd=Crackle4421;\", #\n \"// passwd = Crackle4421\", #\n \"/* passwd = Crackle4421\", #\n \" * passwd = Crackle4421\", #\n \"# passwd = Crackle4421\", #\n]\n\n\n@pytest.fixture(params=success_line_list)\ndef success_line(request) -> str:\n return request.param\n\n\nKEYWORD_PASSWORD_PATTERN = KeywordPattern.get_keyword_pattern(\n r\"(?.*)$\")\n\nLINE_VARIABLE_PATTERN = re.compile(r\"^(?P.*)$\")\n\nDUMMY_DESCRIPTOR = Descriptor(\"\", \"\", \"\")\n\nDUMMY_ANALYSIS_TARGET = AnalysisTarget(line_pos=0, lines=[\"\"], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n" }, { "path": "tests/filters/test_line_git_binary_check.py", "content": "import pytest\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters import LineGitBinaryCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_DESCRIPTOR\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestLineGitBinaryCheck:\n\n @pytest.mark.parametrize(\"line\",\n ['{\"test\":1,\"pw\":\"sn2e8dgWwW\",\"payload\":\"EYlS}b+C(YT)lWLGxNdj7Pw=w\"}', 'XcmV?d00001'])\n def test_line_specific_key_check_p(self, file_path: pytest.fixture, line: str) -> None:\n cred_candidate = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n assert LineGitBinaryCheck().run(cred_candidate, target) is False\n\n @pytest.mark.parametrize(\"line\",\n ['zxNdj)EYlS}b8JGyg7Pw=wujtWvwg9)mv+;vvr}dADtX-(^(6N+C(YT)lWLG7tdu$7', 'HcmV?d00001'])\n def test_line_specific_key_check_n(self, file_path: pytest.fixture, line: str) -> None:\n cred_candidate = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n assert LineGitBinaryCheck().run(cred_candidate, target) is True\n" }, { "path": "tests/filters/test_line_specific_key_check.py", "content": "import pytest\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters import LineSpecificKeyCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_DESCRIPTOR\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestLineSpecificKeyCheck:\n\n @pytest.mark.parametrize(\"line\", [\n '\"AwsAccessKey\": \"AKIAGIREOGIAWSKEY123,',\n ])\n def test_line_specific_key_check_p(self, file_path: pytest.fixture, line: str) -> None:\n cred_candidate = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n assert LineSpecificKeyCheck().run(cred_candidate, target) is False\n\n @pytest.mark.parametrize(\"line\", [\n '\"AwsAccessKey\": enc(\"AKIAGIREOGIAWSKEY123\"),',\n '\"AwsAccessKey as example\": \"AKIAGIREXAMPLEKEY123\"',\n ])\n def test_line_specific_key_check_n(self, file_path: pytest.fixture, line: str) -> None:\n cred_candidate = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n # LINE_VALUE_PATTERN does not detect a value position\n cred_candidate.value_start = line.find(\"AKIA\")\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n assert LineSpecificKeyCheck().run(cred_candidate, target) is True\n" }, { "path": "tests/filters/test_line_uue_part_check.py", "content": "from unittest import TestCase\n\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters.line_uue_part_check import LineUUEPartCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_DESCRIPTOR\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestLineUUEPartCheck(TestCase):\n\n def test_line_uue_part_check_short_n(self):\n line = \"\"\"#````\"\"\"\n cred_candidate = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line, line], line_nums=[1, 2], descriptor=DUMMY_DESCRIPTOR)\n self.assertFalse(LineUUEPartCheck().run(cred_candidate, target))\n\n def test_line_uue_part_check_uue__n(self):\n line = \"\"\"M[@%]PW:2Z.Q?2M^S;`4G?E0C.@V&?0KY]]\"H3Y@6$#I4V*R^\"+B,2P6`A)UL\"\"\"\n cred_candidate = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n cred_candidate.line_pos = 1\n target = AnalysisTarget(line_pos=1,\n lines=[\"begin 644 x3wo.bin\", line, \"#````\", \"`\", \"end\"],\n line_nums=[1, 2, 3, 4, 5],\n descriptor=DUMMY_DESCRIPTOR)\n self.assertFalse(LineUUEPartCheck().run(cred_candidate, target))\n\n def test_line_uue_part_single_n(self):\n line = \"\"\"M[@%]PW:2Z.Q?2M^S;`4G?E0C.@V&?0KY]]\"H3Y@6$#I4V*R^\"+B,2P6`A)UL\"\"\"\n cred_candidate = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=DUMMY_DESCRIPTOR)\n self.assertFalse(LineUUEPartCheck().run(cred_candidate, target))\n\n def test_line_uue_part_check_n(self):\n line = \"\"\"M[@%]PW:2Z.Q?2M^S;`4G?E0C.@V&?0KY]]\"H3Y@6$#I4V*R^\"D+lowercase\"\"\"\n cred_candidate = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line, line], line_nums=[1, 2], descriptor=DUMMY_DESCRIPTOR)\n self.assertFalse(LineUUEPartCheck().run(cred_candidate, target))\n\n def test_line_uue_part_check_p(self):\n line = \"\"\"M[@%]PW:2Z.Q?2M^S;`4G?E0C.@V&?0KY]]\"H3Y@6$#I4V*R^\"+B,2P6`A)UL\"\"\"\n cred_candidate = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n target = AnalysisTarget(line_pos=0, lines=[line, line], line_nums=[1, 2], descriptor=DUMMY_DESCRIPTOR)\n self.assertTrue(LineUUEPartCheck().run(cred_candidate, target))\n # check for empty line\n cred_candidate.line = ''\n self.assertTrue(LineUUEPartCheck().run(cred_candidate, target))\n" }, { "path": "tests/filters/test_value_allowlist_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueAllowlistCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueAllowlistCheck:\n\n @pytest.mark.parametrize(\n \"line\",\n [ #\n \"password = $4eCr3t\", #\n \"pass=$((0394584039))\", #\n \"password = 'F(b7)]DAS^iCv0vqIJOvGg<5(pass);\", #\n \"password = ***test***\", #\n \"password = .*@@@@@@\", #\n \"pass=get->pass('''ARGS\", #\n \"password = '$34%4reGE_'\", #\n \"password = '$D34%4reGE_'\", #\n ])\n def test_value_allowlist_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path=file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueAllowlistCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [ #\n '$passwordLabel = $sourceLabel.SelectItem(\"password\")', #\n 'password=$this->cryptCore->getPw()', #\n 'password=$this::cryptCore', #\n 'pass=$(a-tool-invocation --arg 1)', # ???\n 'pass=\"$(a-tool-invocation | pipe-processing)\"', #\n \"pass=get->pass(arg\", #\n \"PASS:@@@hl@@@PASS@@@endhl@@@\", #\n \"pass:='ENC(Crackle123)'\", #\n \"pass:'ENC[Crackle123]'\", #\n \"pass=${REMOVE_PREFIX#prefix}\", #\n \"pass=$PASSWORD\", #\n \"pass===#{PASSWORD}\", #\n \"pass=>#{{PASSWORD}}\", #\n \"pass:test*****\", #\n 'PASS=\"${*}\"', #\n 'PASS=\"$123\"', #\n 'PASS=\"$A1B2C3D\"', #\n ])\n def test_value_allowlist_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path=file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueAllowlistCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_array_dictionary_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueArrayDictionaryCheck\nfrom credsweeper.rules.rule import Rule\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueArrayDictionaryCheck:\n\n @pytest.fixture\n def token_rule(self, config) -> Rule:\n token_rule_without_filters = {\n \"name\": \"Password\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"type\": \"keyword\",\n \"values\": [\"pass\"],\n \"filter_type\": [ValueArrayDictionaryCheck.__name__],\n \"use_ml\": True,\n \"min_line_len\": 0,\n \"target\": [\"code\", \"doc\"],\n }\n rule = Rule(config, token_rule_without_filters)\n return rule\n\n def test_value_array_dictionary_p(self, token_rule: Rule, file_path: pytest.fixture,\n success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=token_rule.patterns[0])\n assert ValueArrayDictionaryCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\n \"passwd = values[k+1:j]\",\n \"passwd = values[i]\",\n \"passwd = values[145]\",\n \"passwd = values[token_id]\",\n ])\n def test_value_array_dictionary_n(self, token_rule: Rule, file_path: pytest.fixture, line: str) -> None:\n \"\"\"Evaluate that filter do remove calls to arrays and arrays declarations\"\"\"\n line_data = get_line_data(file_path, line=line, pattern=token_rule.patterns[0])\n assert ValueArrayDictionaryCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n @pytest.mark.parametrize(\"line\", [\n '{\"password\":[{\"id\":\"09b51f37-8583-17ae-2a50-246c1b63150e\",\"use\":\"alg\",\"k\":\"XcFt0hJ4kA-1D9L37ZGu2_P\"},{\"kty\"',\n \"password = passwords['user1']\",\n \"password = passwords('user1')\",\n \"passwd[i] = 'root'\",\n \"users[i] = {passwd: 'root'}\",\n \"user = {passwd: 'root'}\",\n \"passwd = {'root'}\",\n \"user = get_user_data(passwd='root', user=users[i])\",\n \"user = get_user_data(user=users[i], passwd='root')\",\n ])\n def test_array_assignment_n(self, token_rule: Rule, file_path: pytest.fixture, line: str) -> None:\n \"\"\"Evaluate that filter do not remove assignments to array or dictionary declaration\"\"\"\n line_data = get_line_data(file_path, line=line, pattern=token_rule.patterns[0])\n assert ValueArrayDictionaryCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n" }, { "path": "tests/filters/test_value_atlassian_token_check.py", "content": "import base64\nimport binascii\n\nimport pytest\n\nfrom credsweeper.common.constants import LATIN_1\nfrom credsweeper.filters import ValueAtlassianTokenCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueAtlassianTokenCheck:\n\n @pytest.mark.parametrize(\"line\", [\"12345:«VÏel\\tSpÁß¡»q¾ä×^0÷ÕJür°eÆ\\r\"])\n def test_value_structured_token_check_p(self, file_path: pytest.fixture, line: str) -> None:\n encoded_line = base64.b64encode(line.encode(LATIN_1)).decode('ascii')\n line_data = get_line_data(file_path, line=encoded_line, pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n bbdc_line_data = get_line_data(file_path, line=f\"BBDC-{encoded_line}\", pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(bbdc_line_data, DUMMY_ANALYSIS_TARGET) is False\n payload = f\"ATBB{encoded_line}\"[:28]\n crc32 = f\"{binascii.crc32(payload.encode('ascii')):08x}\".upper()\n bbdc_line_data = get_line_data(file_path, line=f\"{payload}{crc32}\", pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(bbdc_line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\",\n [\"12x45:asbdsa:28yd\", \"12345:bsskwjdsfskjdhrebewr\", \"022:OrganizationInvitation6080804\"])\n def test_value_structured_token_check_n(self, file_path: pytest.fixture, line: str) -> None:\n encoded_line = base64.b64encode(line.encode('ascii')).decode('ascii')\n line_data = get_line_data(file_path, line=encoded_line, pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n bbdc_line_data = get_line_data(file_path, line=f\"BBDC-{encoded_line}\", pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(bbdc_line_data, DUMMY_ANALYSIS_TARGET) is True\n bbdc_line_data = get_line_data(file_path, line=f\"ATBB{encoded_line[:28]}012345678\", pattern=LINE_VALUE_PATTERN)\n assert ValueAtlassianTokenCheck().run(bbdc_line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_azure_token_check.py", "content": "import unittest\n\nfrom credsweeper.filters import ValueAzureTokenCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueAzureTokenCheck(unittest.TestCase):\n\n def test_value_AzureToken_check_p(self):\n self.assertTrue(ValueAzureTokenCheck().run(get_line_data(line=\"eyJungle\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueAzureTokenCheck().run(\n get_line_data(line=\"eyJhbGciOjEsInR5cCI6Miwia2lkIjozfQo\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueAzureTokenCheck().run(\n get_line_data(line=\"eyJhbGciOjEsInR5cCI6Miwia2lkIjozfQo.eyJhbGciOjEsInR5cCI6Miwia2lkIjozfQo\"\n \".eyJhbGciOjEsInR5cCI6Miwia2lkIjozfQo\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n\n def test_value_AzureToken_check_n(self):\n self.assertFalse(ValueAzureTokenCheck().run(\n get_line_data(line=\"eyJhbGciOjEsInR5cCI6Miwia2lkIjozfQo.eyJpc3MiOjEsImV4cCI6MiwiaWF0IjozfQo\"\n \".1234567890qwertyuiopasdfghjklzxc\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n" }, { "path": "tests/filters/test_value_base32_data_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueBase32DataCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueBase32DataCheck:\n\n @pytest.mark.parametrize(\"line\", [\"SUAML2GCZ7IK7E7UD4VZ7ELPZW7DK2ZNL35WSMW3IORHC3BWBSDQXUQRBU\", \"WXFES7QNTET5DQYC\"])\n def test_value_entropy_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueBase32DataCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"PMRGSZBCHIYTEM35\", \"ABCDEFGHIJKLMNOP\", \"5555555555555555\", \"GAYDAMBQGAYDAMBQ\"])\n def test_value_entropy_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueBase32DataCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_base64_data_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueBase64DataCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueBase64DataCheck:\n\n @pytest.mark.parametrize(\"line\", [\"0DiwN2M1NTeGd6S6jU\", \"o9LN618aEaH32KhF7e_L\"])\n def test_value_entropy_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueBase64DataCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"eyJ0eXAiOiJKV1QiLC\", \"2AA219GG746F88F6DDA0D852A0FD3211\", \"!@#$%^&*(_)0aA\"])\n def test_value_entropy_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueBase64DataCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_base64_key_check.py", "content": "import re\nimport unittest\n\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.filters import ValueBase64KeyCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET\n\n\nclass TestValueBase64KeyCheck(unittest.TestCase):\n ALL_LINE_PATTERN = re.compile(\n r\"(?P\\bMII[A-Za-f][0-9A-Za-z/+]{8}(?s:[^!#$&()*\\-.:;<=>?@\\[\\]^_{|}~]{8,8000}))\")\n\n def test_value_check_n(self) -> None:\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=\"MIIXXXXX\",\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=TestValueBase64KeyCheck.ALL_LINE_PATTERN)\n self.assertTrue(ValueBase64KeyCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_value_check_p(self) -> None:\n line = (\"'''MIICXAIBAAKBgQDFgQqUYexFziVtw\\\\n\\\\rnEz9XaYjmGdpGVWAqL1NX41LIxRAy1tbo1hCBUppqWGfn\"\n \"\\nWHwZE5k4sYt5cE6n4hcdEPj9kdrDaeF7Te9JZg1eDE9RwWColxC+5neCBCmQY2LmWJa6+HDgDKq+DJIpx8PCDb\"\n \"+i3oeOwHn00H/4T9JczK/XJzhQIDAQABAoGBALbGxu2u\"\n \"+aNYNZcv/Odi4FAqY/gprYY9hmV7DcNT6L8IO8AsMTZ87mjPShv/Z\"\n \"/Esl6M7Adzr+hyYjgWReTH3o6qMBdHyJhU28Ngsrt8EIaSYpE\"\n \"/O 2 h d p 6 l Z vSWVt/KD+HJMRIDVqj39DphuU8f0cqJkpLoP5xcetOH\"\n \" /XVnIVQXm5AkEA4gc5HjeggbJkj4bJg/ROmKlLgMKalg0LS7Z3\"\n \"\\tYXIhIGJcwE27ERB5DjqMJp38Yvz8WqUchNFqF4fxSEYTWVIiMwJBAN\"\n \"\\t\\t\\t+xiNpJtX3qWI4T5iOQM7pE8Ngx+olpOpZkwQ6jBzNyTfaZZT\\\"\"\n \"XpmvzvBZKWgkvxAE3BaeHjuXKlRYp7dVTXi2cCQEeKL7rvsl66nveKmueoAO \\\\\\\\\"\n \"\\nRy2RH1Bkat9EBPjXOLUw7T8zVupOHey+IEB+4FHSgb\"\n \"\\r\\n\\tmKf8EI29Vo4CGg1dGKyxwV8CQAqZ/\"\n \"\\r WRrDeDz1FKXetbApNL1JXz5kWglxpMOH2A0NckoZ62CQ5u0gJXwNhFmdLJor5z\"\n \"/x6bfBhD66DrR8xOcS40CQBoGNvyzjHXUdx64Yxmtz2FXq0fYI8J8ChgNfTe6l6d1nzEQ7i0SspM45L\"\n \"/n5tgyrBBGcqzQ/WBL1C8Ny5K+RxY='''\\n -----END\")\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=line,\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=TestValueBase64KeyCheck.ALL_LINE_PATTERN)\n self.assertFalse(ValueBase64KeyCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n" }, { "path": "tests/filters/test_value_base64_part_check.py", "content": "import re\nimport unittest\n\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.filters import ValueBase64PartCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET\n\n\nclass TestValueBase64PartCheck(unittest.TestCase):\n\n def test_value_check_n(self) -> None:\n for prefix, value, suffix in [\n (\"fp: zza0dxVlt0/\", \"TijfkIXPhSdtdakk9G\", \"\\\\nCIpPqrtaOxOx0sEXzS/MuYT4rE3363cXp1yCxqF3dhUP\"),\n (\"sha512-eGuFFw7Upda+g4p+QHvnW0RyTX/SVeJBDM/\", \"gCtMARO0cLuT2HcEKnTPvhjV6aGeqrCB\", \"/sbNop0Kszm0jsaWU4A==\"),\n # left and right boundaries\n (\"qcE81rS+FJHGy7KedoQ4juvg3FZ9lz4T/\", \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eo\",\n \"+se0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\"),\n # only left\n (\"qcE81rS+FJHGy7KedoQ4juvg3FZ9lz4T/\", \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eo\", \"\"),\n # only right\n (\"\", \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eo\", \"/qcE81rS+FJHGy7KedoQ4juvg3FZ9lz4T\"),\n (\"hj4Ov3rIwAAdHIIAC7ARR4daWuDXZoA41Bk6QJC\\\\nLwgikiCrNulUp0VYmrLoEE/\", \"sBY3YlVbQdYgS9ulYJcKyInd8hWQ31TG\",\n \"/SSyz1SRd\\\\ncp8SD9bAu8SbqX4DWa6tV2XxopsabwQgWqGtJWzYIyuVFvdSuXGaZ\"),\n (\"aWrnS3VQGR0j4mLkKC1NUeljjA77zYyhVbIE0dR%2By7fmaHq7U%2BdegXWGpAZ+/\", \"4pR32luBFTAtWgUcCv56\",\n \"/p5y30X87Yz1khTIycdgpUW9kY7WdsC9zxoXTvMvWuVV98YyMnSGH2SYE5pwALBIr9QKi\"),\n (\"04MjE2MGFkOTFhYzgiLCJlbmMiOiJBMTlwIj+\", \"GgzlFDwPikM5vUkIT2WOtQxKWceQ4wzV\",\n \"/p9Y0jfEpUq6XHZIlai1oYHbDtx2Nc1k3z7\"),\n (\"GuBdjqFPQXaaOcxuJ5oLRDC7IxtkpNz1P9CByI/\", \"eEZQFtJDUtShrP0tTC\",\n \"\\\\nztg1zgkXhaz7IMxm4SgeuOUFy4mEcAGjQxs7qays\"),\n (\"sha512-eGuFFw7Upda+g4p+QHvnW0RyTX/SVeJBDM/\", \"gCtMARO0cLuT2HcEKnTPvhjV6aGeqrCB\", \"/sbNop0Kszm0jsaWU4A==\"),\n (\"sha512-eGuFFw7Upda+g4p+QHvnW0RyTX/SVeJBDM/\", \"gCtMARO0cLuT2HcEKnTPvhjV6aGeqrCB\", \"/sbNop0Kszm0jsaWU4A==\"),\n (\"FklyR1uZ/\", \"wPJjj611cdBcztlPdqoxssQGnh85BzCj\",\n \"/u3WqBpE2vjvyyvyI5kX6zk7S0ljKtt2jny2+00VsBerQ==\"),\n (\"sha512-h7fJ/\", \"5uWuRVyOtkO45pnt1Ih40CEleeyCHzipqAZO2e5H20g25Y48uYnFUiShvY4rZWNJ\", \"/Bib/KVPmanaCtOhA==\"),\n ]:\n line = ''.join([prefix, value, suffix])\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=line,\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=re.compile(fr\"(?P{value})\"))\n self.assertTrue(ValueBase64PartCheck().run(line_data, DUMMY_ANALYSIS_TARGET), line)\n\n def test_value_check_p(self) -> None:\n for prefix, value, suffix in [\n (\" http://localhost:8888/v1/api/get?token=\", \"zUkITxodk63bDVUMwIymb3zKTxICz85zC00cv0Geline80\", \"\"),\n (\"http://example.com/api/v3/\", \"T1029384756B102984756\", \"\"),\n # part of jwt\n (\"04MjE2MGFkOTFhYzgiLCJlbmMiOiJBMTlwIj.\", \"GgzlFDwPikM5vUkIT2WOtQxKWceQ4wzV\",\n \".p9Y0jfEpUq6XHZIlai1oYHbDtx2Nc1k3z7\"),\n (\"https://yourInstance.salesforce.com/services/Soap/m/{version}/\", \"00Dx0000006Y0xy\", \"\")\n ]:\n line = ''.join([prefix, value, suffix])\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=line,\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=re.compile(fr\"(?P{value})\"))\n self.assertFalse(ValueBase64PartCheck().run(line_data, DUMMY_ANALYSIS_TARGET), line)\n" }, { "path": "tests/filters/test_value_basic_auth_check.py", "content": "import re\nimport unittest\n\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.filters.value_basic_auth_check import ValueBasicAuthCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET\n\n\nclass TestValueBasicAuthCheck(unittest.TestCase):\n\n def test_value_check_n(self) -> None:\n for value in [\n \"VGhlVXNlcjtUaGVQYXM1dzByZA==\", #\n \"Programming_Language\", #\n \"OjEyMzQ1Njc4\", #\n \"MTIzNDU6Njc4\", #\n ]:\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=value,\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=re.compile(fr\"(?P{value})\"))\n self.assertTrue(ValueBasicAuthCheck().run(line_data, DUMMY_ANALYSIS_TARGET), value)\n\n def test_value_check_p(self) -> None:\n for value in [\n \"MToxMjM0NTY3\", #\n \"VGhlVXNlcjpUaGVQYXM1dzByZA==\", #\n ]:\n line_data = LineData(config=None,\n path=\"dummy\",\n file_type=\"\",\n line=value,\n info=\"\",\n line_num=1,\n line_pos=0,\n pattern=re.compile(fr\"(?P{value})\"))\n self.assertFalse(ValueBasicAuthCheck().run(line_data, DUMMY_ANALYSIS_TARGET), value)\n" }, { "path": "tests/filters/test_value_blocklist_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueBlocklistCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueBlocklistCheck:\n\n def test_value_blocklist_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=LINE_VALUE_PATTERN)\n assert ValueBlocklistCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"string12\", \"uuid5\"])\n def test_value_blocklist_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueBlocklistCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_camel_case_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueCamelCaseCheck\nfrom tests.filters.conftest import KEYWORD_PASSWORD_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueCamelCaseCheck:\n\n def test_value_camelcase_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueCamelCaseCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"password = CamelCase\", \"password = camelCase\"])\n def test_value_camelcase_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueCamelCaseCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_dictionary_keyword_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueDictionaryKeywordCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueDictionaryKeywordCheck:\n\n def test_value_dictionary_keyword_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=LINE_VALUE_PATTERN)\n assert ValueDictionaryKeywordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"abstract123\"])\n def test_value_dictionary_keyword_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueDictionaryKeywordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_entropy_base32_check.py", "content": "import sys\n\nimport pytest\n\nfrom credsweeper.filters import ValueEntropyBase32Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueEntropyBase32Check:\n\n @pytest.mark.parametrize(\"line\", [\"WXFES7QNTET5DQYC\"])\n def test_value_entropy_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase32Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"200X300X4000X123\"])\n def test_value_entropy_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase32Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n @pytest.mark.parametrize((\"size\", \"entropy\", \"deviation\"), [\n (16, 3.553197207016156, 0.20104579535116426),\n (32, 4.175560617601108, 0.15800526502749024),\n (33, 4.1969606087810565, 0.15484387204591749),\n (sys.maxsize, 4.04, 0),\n ])\n def test_get_min_data_entropy_p(self, size: int, entropy: float, deviation: float) -> None:\n min_entropy = ValueEntropyBase32Check.get_min_data_entropy(size)\n diff = abs(min_entropy - (entropy - deviation))\n max_diff = deviation / 4\n assert 0 <= diff\n assert diff <= max_diff\n\n @pytest.mark.parametrize(\"size\", [0, 1, -1, -sys.maxsize])\n def test_get_min_data_entropy_n(self, size: int) -> None:\n assert 0 == ValueEntropyBase32Check.get_min_data_entropy(size) == 0\n" }, { "path": "tests/filters/test_value_entropy_base36_check.py", "content": "import sys\n\nimport pytest\n\nfrom credsweeper.filters import ValueEntropyBase36Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueEntropyBase36Check:\n\n @pytest.mark.parametrize(\"line\", [\"2wp3v1jq9x1wa87n0bn5n46e\", \"snck3id95hab1jfnvlp109fs8\"])\n def test_value_entropy_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase36Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"testtesttest\", \"noncenoncenoncenoncenonce\"])\n def test_value_entropy_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase36Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n @pytest.mark.parametrize((\"size\", \"entropy\", \"deviation\"), [\n (15, 3.374, 0.0),\n (16, 3.593320328115991, 0.19663735985864308),\n (24, 4.0019667180259315, 0.1767051932594335),\n (25, 4.039642026714182, 0.1731145889575481),\n (sys.maxsize, 3.9, 0),\n ])\n def test_get_min_data_entropy_p(self, size: int, entropy: float, deviation: float) -> None:\n min_entropy = ValueEntropyBase36Check.get_min_data_entropy(size)\n diff = abs(min_entropy - (entropy - deviation))\n max_diff = deviation / 4\n assert 0 <= diff\n assert diff <= max_diff\n\n @pytest.mark.parametrize(\"size\", [0, 1, -1, -sys.maxsize])\n def test_get_min_data_entropy_n(self, size: int) -> None:\n assert 0 == ValueEntropyBase36Check.get_min_data_entropy(size) == 0\n" }, { "path": "tests/filters/test_value_entropy_base64_check.py", "content": "import sys\n\nimport pytest\n\nfrom credsweeper.filters import ValueEntropyBase64Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueEntropyBase64Check:\n\n @pytest.mark.parametrize(\"line\", [\"0wz92+C275sfJHb2r5tS5o/u9y862lR4\"])\n def test_value_entropy_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase64Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"D6018D91B502C475E8FC27D5F05387558A002B9283DA7E252896950917476ECE\"])\n def test_value_entropy_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueEntropyBase64Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n @pytest.mark.parametrize((\"size\", \"entropy\", \"deviation\"), [\n (12, 3.402832674668131, 0.16390772966021167),\n (18, 3.901894088228036, 0.1507035617252249),\n (20, 4.027133655487158, 0.14789802297157817),\n (25, 4.2799509786429715, 0.1469939952270194),\n (35, 4.636189424519627, 0.1325272934890342),\n (45, 4.877311178212475, 0.11797362443045391),\n (65, 5.183120734812424, 0.10823342697093974),\n (80, 5.329761693425697, 0.09159231726044716),\n (100, 5.4658131564512376, 0.08210420023521858),\n (256, 5.77, 0.02),\n (512, 5.89, 0.015),\n (1024, 5.94, 0.003),\n (sys.maxsize, 6.0, 0.0000000000000001),\n ])\n def test_get_min_data_entropy_p(self, size: int, entropy: float, deviation: float) -> None:\n min_entropy = ValueEntropyBase64Check.get_min_data_entropy(size)\n diff = abs(min_entropy - (entropy - deviation))\n max_diff = deviation / 4\n assert 0 <= diff\n assert diff <= max_diff\n\n @pytest.mark.parametrize(\"size\", [0, 1, -1, -sys.maxsize])\n def test_get_min_data_entropy_n(self, size: int) -> None:\n assert 0 == ValueEntropyBase64Check.get_min_data_entropy(size) == 0\n" }, { "path": "tests/filters/test_value_file_path_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueFilePathCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueFilePathCheck:\n\n @pytest.mark.parametrize(\"line\", [\n \"/u5r/d3v/f1le\",\n \"5//0KCPafDhZvtCwqrsyiKFeDGT_0ZGHiI-E0ClIWrLC7tZ1WE5vHc4-Y2qi1IhPy3Pz5fmCe9OPIxEZUONUg7SWJF9nwQ_j2lIdXU0\",\n \"SDF;4s]dDe\"\n ])\n def test_value_file_path_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueFilePathCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"[DEPOT]/${path}/$(date)/config/credentials\", #\n \"/mnt/x\", #\n \"/srv/x\", #\n \"/var/lib/\", # path\n \"~/.ssh/id_rsa\", # path\n \"../key\", # path\n \"../../log\", # path\n \"/home/user/.ssh/id_rsa\", # path\n \"../.ssh/id_rsa\", # path\n \"crackle/filepath.txt\",\n \"/home/user/tmp\", # simple path\n \"file:///Crackle/filepath/\", # path from browser url\n \"~/.custompass\", # path with synonym\n \"./sshpass.sh\", # path with synonym\n \"crackle/file.path\", #\n \"C:\\\\Crackle\\\\filepath\", #\n ])\n def test_value_file_path_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueFilePathCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_github_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueGitHubCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueGitHubCheck:\n\n @pytest.mark.parametrize(\"line\",\n [\"gh?_00000000000000000000000000000004WZ4EQ\", \"npm_00000000000000000000000000000004WZ4EQ\"])\n def test_value_github_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueGitHubCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\",\n [\"hhh_00000000000000000000000000000004WZ4EQ\", \"npm_00000000000000000000000000000004WZAEQ\"])\n def test_value_github_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueGitHubCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_grafana_check.py", "content": "import base64\n\nimport pytest\n\nfrom credsweeper.filters import ValueGrafanaCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueGrafanaCheck:\n\n @pytest.mark.parametrize(\"line\", ['{\"o\":\"O\",\"n\":\"N\",\"k\":\"K\",\"m\":{\"r\":\"0\"}}'])\n def test_value_grafana_token_p(self, file_path: pytest.fixture, line: str) -> None:\n payload = base64.b64encode(line.encode('ascii')).decode('ascii')\n line_data = get_line_data(file_path, line=f\"glc_{payload}\", pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", ['{\"k\":\"K\",\"n\":\"N\",\"id\":1}'])\n def test_value_grafana_key_p(self, file_path: pytest.fixture, line: str) -> None:\n payload = base64.b64encode(line.encode('ascii')).decode('ascii')\n line_data = get_line_data(file_path, line=f\"{payload}\", pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", ['{\"K\":\"K\",\"n\":\"N\",\"id\":1}', '{\"0\":\"O\",\"W\":\"N\",\"Y\":\"K\",\"X\":{\"r\":\"0\"}}'])\n def test_value_grafana_n(self, file_path: pytest.fixture, line: str) -> None:\n payload = base64.b64encode(line.encode('ascii')).decode('ascii')\n line_data = get_line_data(file_path, line=f\"{payload}\", pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n line_data = get_line_data(file_path, line=f\"glc_{payload}\", pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_grafana_service_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueGrafanaServiceCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueGrafanaServiceCheck:\n\n @pytest.mark.parametrize(\"line\", [\"glsa_DuMmY-T0K3N-f0R-tHe-Te5t-CRC32Ok_770c8cda\"])\n def test_value_sgrafana_service_check_p(self, file_path: pytest.fixture, line: str) -> None:\n glsa_line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaServiceCheck().run(glsa_line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"glpl_DuMmY-T0K3N-f0R-tHe-Te5t-CRC32Ok_770c8CdA\"])\n def test_value_sgrafana_service_check_n(self, file_path: pytest.fixture, line: str) -> None:\n glsa_line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueGrafanaServiceCheck().run(glsa_line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_hex_number_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueHexNumberCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueHexNumberCheck:\n\n @pytest.mark.parametrize(\"line\", [\"0xabcdI234\", \"0xabcd0987654321371\"])\n def test_value_number_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueHexNumberCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"0xaBcd1234\", \"0xAbCd098765432137\"])\n def test_value_number_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueHexNumberCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_json_web_key_check.py", "content": "import base64\nimport unittest\n\nfrom credsweeper.filters.value_json_web_key_check import ValueJsonWebKeyCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueJsonWebKeyCheck(unittest.TestCase):\n\n def test_value_jwk_check_n(self):\n self.assertTrue(ValueJsonWebKeyCheck().run(get_line_data(line=\".\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebKeyCheck().run(get_line_data(line=\"eyJungle\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebKeyCheck().run(\n get_line_data(line=\"eyJ1234567890qwertyu#@$^$^&iopasdfghjklzxc\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebKeyCheck().run(\n get_line_data(line=base64.b64encode(b'{\"kty\": \"oct\",\"x\": \"WrMwQfoNaHTgXU5fZvRGAD\"}').decode(),\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n\n def test_value_jwt_check_p(self):\n self.assertFalse(ValueJsonWebKeyCheck().run(\n get_line_data(line=base64.b64encode(b'{\"kty\": \"oct\",\"k\": \"WrMwQfoNaHTgXU5fZvRGAD\"}').decode(),\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n" }, { "path": "tests/filters/test_value_json_web_token_check.py", "content": "import unittest\n\nfrom credsweeper.filters import ValueJsonWebTokenCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueJsonWebTokenCheck(unittest.TestCase):\n\n def test_value_jwt_check_p(self):\n self.assertTrue(ValueJsonWebTokenCheck().run(get_line_data(line=\".\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebTokenCheck().run(get_line_data(line=\"eyJungle\", pattern=LINE_VALUE_PATTERN),\n DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"1234567890qwertyuiopasdfghjklzxc\", pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"eyJhbGciOiJSUzI1NiJ9Cg.eyJleHAiOjY1NTM2fQo.eyJleHAiOjY1NTM2fQo\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"eyJhbGciOiJSUzI1NiJ9Cg.eyJleHAiOjY1NTM2fQo.AAAAAAAAAAAAAAAAAAAAAAA\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n self.assertTrue(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.x3.GFsFyGiCUIP5VHI9CEJL9thWsGjSZf1fJfarNk-LGTM\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n\n def test_value_jwt_check_n(self):\n self.assertFalse(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"eyJhbGciOiJQUzM4NCJ9.eyJkdW1teSI6bnVsbH0.eyJpc3MiOiJqb2UifQ.\" \\\n \"_VP9ZxcPkOptWScOUMXriLH31bTcrg0YhlYL-A7TTHLX7LTDKjggtVq3Nmdl4GIS\" \\\n \"gJdM7GHHZOJHckUjgD-T3X6oHQanKqjpWjU-GxcnOkM86e0joZgJUL7CpHUt7e3W\" \\\n \"MhbUrOCyCFRrxOXtuTvGr2m_LdS7I5OyZ4xEP4JRcsOgOnGq-MEWmLqrRvc4zy5m\" \\\n \"pM6tJwJXI8fr1tF4pcAZxXR17ITCrocVSRC6NuWOVzh_XyyEVRUfqlDbJnU2Z_I0\" \\\n \"dfEQIcC6K5hAgQGSZQC_pQDA51RUoUHa9KfNskerI681fJ8mbjIlbf68CFdXZnjE\" \\\n \"zobUhMn5Z544PF9DjW1BVtsQgXtHlSDFxl6MIMVdvM8oLRbrjlf6BYCRnCxuTA_y\" \\\n \"Ui1o9ndy7ckISHQVhuYFKu78l7nqC4heghK_Gw4h7EB7s8eEuUC-D6JjVtX10IyS\" \\\n \"vCRkRo7f8dWQTjFLs7mlPowjRz0cP5J-MmCoegKHYagOHZ_ArXOR91_u8jMdwmOf\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n self.assertFalse(ValueJsonWebTokenCheck().run(\n get_line_data(line=\"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.\" \\\n \"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.\" \\\n \".e30.GFsFyGiCUIP5VHI9CEJL9thWsGjSZf1fJfarNk-LGTM\",\n pattern=LINE_VALUE_PATTERN), DUMMY_ANALYSIS_TARGET))\n" }, { "path": "tests/filters/test_value_last_word_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueLastWordCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueLastWordCheck:\n\n def test_value_last_word_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueLastWordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"password = value:\"])\n def test_value_last_word_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueLastWordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_length_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueLengthCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueLengthCheck:\n\n def test_value_length_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=LINE_VALUE_PATTERN)\n assert ValueLengthCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"Cra\", \"CrackleCrackleCrackleCrackleCrackleCrackle123\"])\n def test_value_length_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueLengthCheck(max_len=42).run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_method_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueMethodCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueMethodCheck:\n\n def test_value_method_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueMethodCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"pass=Crac.method()\", \"pass=Crac_function\"])\n def test_value_method_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueMethodCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_morphemes_check.py", "content": "import math\nimport unittest\nfrom unittest.mock import MagicMock\n\nimport pytest\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueMorphemesCheck\nfrom tests import AZ_STRING\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueMorphemesCheck(unittest.TestCase):\n\n def setUp(self) -> None:\n self.config = MagicMock(spec=Config)\n\n def test_min_patter_len_n(self) -> None:\n with self.assertRaises(ValueError):\n ValueMorphemesCheck(self.config, -1)\n\n def test_init_n(self) -> None:\n test_filter = ValueMorphemesCheck(self.config)\n self.assertListEqual([1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8], test_filter.thresholds)\n\n def test_init_p(self) -> None:\n test_filter = ValueMorphemesCheck(self.config, 7)\n self.assertListEqual([7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7], test_filter.thresholds)\n\n def test_run_small_n(self) -> None:\n line_data = get_line_data(self.config, file_path=\"file_path\", line='*', pattern=LINE_VALUE_PATTERN)\n self.assertFalse(ValueMorphemesCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_run_oversize_n(self) -> None:\n line_data = get_line_data(self.config, file_path=\"file_path\", line='*', pattern=LINE_VALUE_PATTERN)\n line_data.value = '*' * (2**16)\n value_morpheme_check = ValueMorphemesCheck()\n self.assertGreater(len(line_data.value).bit_length(), len(value_morpheme_check.thresholds))\n self.assertFalse(value_morpheme_check.run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_run_true_p(self) -> None:\n line_data = get_line_data(self.config, file_path=\"file_path\", line='tizen', pattern=LINE_VALUE_PATTERN)\n self.assertTrue(ValueMorphemesCheck(None, 0).run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_run_false_p(self) -> None:\n line_data = get_line_data(self.config, file_path=\"file_path\", line='tizen', pattern=LINE_VALUE_PATTERN)\n self.assertFalse(ValueMorphemesCheck(None, 1).run(line_data, DUMMY_ANALYSIS_TARGET))\n\n\nclass TestValueMorphemesCheckFixture:\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"the 0ne l1ne\",\n \"ani dammi lwnes\",\n \"burito\",\n \"31415926535897932384626433832795\", # first 32 symbols from https://oeis.org/A000796\n \"27182818284590452353602874713526\", # first 32 symbols from https://oeis.org/A001113\n ])\n def test_value_couple_keyword_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueMorphemesCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"deadbeefdeadbeefdeadbeefdeadbeef\",\n str(math.pi),\n str(math.e),\n \"3141592653589793238462643383279\", # first 31 symbols from https://oeis.org/A000796\n \"2718281828459045235360287471352\", # first 31 symbols from https://oeis.org/A001113\n \"crack\",\n \"example\",\n \"motorcyclingend\",\n \"mulicrashprocid\",\n \"rgb195DiscretVideo\",\n \"GetSet\",\n \"GetDummyValue\",\n \"SetAnyString\",\n \"handleDeleteFriend\",\n \"acknowledgments\",\n \"somethingelse\",\n ])\n def test_value_couple_keyword_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueMorphemesCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n @pytest.mark.parametrize(\"line\", [AZ_STRING])\n def test_value_couple_keyword_check_arg_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueMorphemesCheck(threshold=9).run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [AZ_STRING])\n def test_value_couple_keyword_check_arg_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueMorphemesCheck(threshold=8).run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_not_allowed_pattern.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueNotAllowedPatternCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, LINE_VALUE_PATTERN, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueLastWordCheck:\n\n def test_value_last_word_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueNotAllowedPatternCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"[{ \", \"\\\\n\", \"\\t\\t\\t\\\\\", \"\\t \\\\n\\t \\t\"])\n def test_value_last_word_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueNotAllowedPatternCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_not_part_encoded.py", "content": "import pytest\n\nfrom credsweeper.common.constants import Chars\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters import ValueNotPartEncodedCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_DESCRIPTOR\n\n\nclass TestValueNotPartEncodedCheck:\n\n def test_value_not_part_encoded_p(self, config: pytest.fixture) -> None:\n val = 'Q' * 64\n target = AnalysisTarget(0, [val, '/usr/local/host/'], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, val, 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is False\n target = AnalysisTarget(0, [\"AAA\", \"BBB\"], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, \"XXX\", 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is False\n\n def test_value_not_part_encoded_n(self, config: pytest.fixture) -> None:\n val = 'Q' * 64\n target = AnalysisTarget(0, [val, '/etc/localhost=='], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, val, 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n val = 'Q' * 64\n target = AnalysisTarget(0, [val, '0123456789ABCDEF'], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, val, 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n val = \"/123\" + 'Q' * 64\n target = AnalysisTarget(0, [val, '/123456789ABCDE='], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, val, 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n target = AnalysisTarget(1, ['Q' * 64, val, \"1234\"], [1, 2, 3], DUMMY_DESCRIPTOR)\n line_data = LineData(config, val, 1, 2, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n target = AnalysisTarget(1, [Chars.BASE64STD_CHARS.value, \"XXX\"], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, \"XXX\", 1, 2, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n target = AnalysisTarget(0, [\"XXX\", Chars.BASE64STD_CHARS.value], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, \"XXX\", 0, 1, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n target = AnalysisTarget(1, [Chars.BASE64STD_CHARS.value, \"XXX\"], [1, 2], DUMMY_DESCRIPTOR)\n line_data = LineData(config, \"XXX\", 1, 333, \"\", \"\", \"\", LINE_VALUE_PATTERN)\n assert ValueNotPartEncodedCheck().run(line_data, target) is True\n" }, { "path": "tests/filters/test_value_number_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueNumberCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueNumberCheck:\n\n @pytest.mark.parametrize(\"line\", [\"0123423423x\", \"abcdefg\", \"0123456789abcdef012345\"])\n def test_value_number_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueNumberCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\n \"0123456789abcdef01234\", \"0123456789abcdef0123U\", \"0x0123456789abcdefULL\", \"555\", \"314ULL\", \"0xabcdefU\", \"0xfL\",\n \"010101010101\", \"-201760\", \"-1ULL\"\n ])\n def test_value_number_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueNumberCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_pattern_check.py", "content": "import unittest\nfrom unittest.mock import MagicMock\n\nimport pytest\n\nfrom credsweeper.common.constants import DEFAULT_PATTERN_LEN\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValuePatternCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValuePatternCheck(unittest.TestCase):\n\n def setUp(self) -> None:\n self.config = MagicMock(spec=Config)\n\n def test_min_patter_len_n(self) -> None:\n with self.assertRaises(ValueError):\n ValuePatternCheck(self.config, DEFAULT_PATTERN_LEN - 1)\n\n def test_init_n(self) -> None:\n test_filter = ValuePatternCheck(self.config)\n self.assertEqual(-1, test_filter.pattern_len)\n self.assertListEqual([4, 4, 4, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], test_filter.pattern_lengths)\n\n def test_init_p(self) -> None:\n test_filter = ValuePatternCheck(self.config, DEFAULT_PATTERN_LEN)\n self.assertEqual(DEFAULT_PATTERN_LEN, test_filter.pattern_len)\n self.assertListEqual([4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4], test_filter.pattern_lengths)\n\n def test_duple_pattern_check_n(self) -> None:\n self.assertFalse(ValuePatternCheck(self.config).duple_pattern_check(\"20201030\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).duple_pattern_check(\"01000101\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).duple_pattern_check(\"10305070\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).duple_pattern_check(\"11224433\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).duple_pattern_check(\"11000000\", DEFAULT_PATTERN_LEN))\n\n def test_duple_pattern_check_p(self) -> None:\n self.assertTrue(ValuePatternCheck(self.config).duple_pattern_check(\"11223344\", DEFAULT_PATTERN_LEN))\n self.assertTrue(ValuePatternCheck(self.config).duple_pattern_check(\"010101010\", DEFAULT_PATTERN_LEN))\n self.assertTrue(ValuePatternCheck(self.config).duple_pattern_check(\"40302010\", DEFAULT_PATTERN_LEN))\n\n def test_equal_pattern_check_n(self) -> None:\n self.assertFalse(ValuePatternCheck(self.config).equal_pattern_check(\"Crackle123\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).equal_pattern_check(\"IEEE32441\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(self.config).equal_pattern_check(\"Pass...\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(pattern_len=4).equal_pattern_check(\"Pass:\\\\n Crackle123\", 5))\n\n def test_equal_pattern_check_p(self) -> None:\n self.assertTrue(ValuePatternCheck(self.config).equal_pattern_check(\"AAAABCD\", DEFAULT_PATTERN_LEN))\n self.assertTrue(ValuePatternCheck(pattern_len=4).equal_pattern_check(\"-------BEGIN\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(pattern_len=8).equal_pattern_check(\"-------BEGIN\", DEFAULT_PATTERN_LEN))\n\n def test_ascending_pattern_check_n(self) -> None:\n self.assertFalse(ValuePatternCheck(self.config).ascending_pattern_check(\"Crackle123\", DEFAULT_PATTERN_LEN))\n self.assertFalse(\n ValuePatternCheck(pattern_len=4).ascending_pattern_check(\"Crackle987654321\", DEFAULT_PATTERN_LEN))\n\n def test_ascending_pattern_check_p(self) -> None:\n self.assertTrue(ValuePatternCheck(self.config).ascending_pattern_check(\"Crackle1234\", DEFAULT_PATTERN_LEN))\n self.assertTrue(ValuePatternCheck(pattern_len=4).ascending_pattern_check(\"Cracklefgh\", DEFAULT_PATTERN_LEN))\n\n def test_descending_pattern_check_n(self) -> None:\n self.assertFalse(ValuePatternCheck(self.config).descending_pattern_check(\"Crackle321\", DEFAULT_PATTERN_LEN))\n self.assertFalse(ValuePatternCheck(pattern_len=4).descending_pattern_check(\"Crackle123456789\", 5))\n\n def test_descending_pattern_check_p(self) -> None:\n self.assertTrue(ValuePatternCheck(self.config).descending_pattern_check(\"Crackle4321\", DEFAULT_PATTERN_LEN))\n self.assertTrue(ValuePatternCheck(pattern_len=4).descending_pattern_check(\"Crackledcba\", DEFAULT_PATTERN_LEN))\n\n\nclass TestValuePatternCheckFixture:\n\n def test_value_similarity_check_p(self, file_path: pytest.fixture, config: Config,\n success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=LINE_VALUE_PATTERN)\n assert ValuePatternCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\n \"000102030405060708090a0b0c0d0e0f101112131415161718191a1b1c1d1e1f20212223242526\",\n \"c0ffeecc-dead-beef-cafe-1a2b3c4d5e6f\", \"123456ff-dead-beef-cafe-7a24ca6a903c\",\n \"ffffff00-dead-beef-cafe-4a25c06a902d\", \"Crackle4444\", \"Crackle1234\", \"Crackle4321\", \"@$%\", \"a5\", \"_\"\n ])\n def test_value_similarity_check_n(self, file_path: pytest.fixture, config: Config, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValuePatternCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_sealed_secret_check.py", "content": "import re\nimport unittest\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.filters import ValueSealedSecretCheck\nfrom tests import AZ_STRING\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueSealedSecretCheck(unittest.TestCase):\n\n def test_value_search_check_n(self):\n line_data = get_line_data(line=AZ_STRING, pattern=LINE_VALUE_PATTERN)\n self.assertFalse(ValueSealedSecretCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n line_data = get_line_data(line=\"AQA\", pattern=LINE_VALUE_PATTERN)\n self.assertFalse(ValueSealedSecretCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n line_data = get_line_data(line=f\"AgA{'A' * MAX_LINE_LENGTH}\", pattern=LINE_VALUE_PATTERN)\n self.assertFalse(ValueSealedSecretCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_value_search_check_p(self):\n line = f\"AgA{'A' * 1000}\\nbitnami\\nSealedSecret\\nencryptedData\\n\"\n line_data = get_line_data(line=line, pattern=re.compile(r\"(?P\\S+)\"))\n target = AnalysisTarget(line_pos=0, lines=[line], line_nums=[1], descriptor=None)\n self.assertTrue(ValueSealedSecretCheck().run(line_data, target))\n" }, { "path": "tests/filters/test_value_search_check.py", "content": "import re\nimport unittest\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH\nfrom credsweeper.filters import ValueSearchCheck\nfrom tests import AZ_STRING\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueSearchCheck(unittest.TestCase):\n\n def test_value_search_check_n(self):\n line_data = get_line_data(line=AZ_STRING, pattern=LINE_VALUE_PATTERN)\n # None in constructor returns False always\n self.assertFalse(ValueSearchCheck().run(line_data, DUMMY_ANALYSIS_TARGET))\n # empty pattern - too\n self.assertFalse(ValueSearchCheck(pattern='').run(line_data, DUMMY_ANALYSIS_TARGET))\n # smallest pattern does not exist in value\n self.assertFalse(ValueSearchCheck(pattern=\"zyzzyva\").run(line_data, DUMMY_ANALYSIS_TARGET))\n # smallest value does not exist in pattern\n self.assertFalse(ValueSearchCheck(pattern='_' * MAX_LINE_LENGTH).run(line_data, DUMMY_ANALYSIS_TARGET))\n\n def test_value_search_check_p(self):\n line_data = get_line_data(line=AZ_STRING, pattern=LINE_VALUE_PATTERN)\n # a word in value\n self.assertTrue(ValueSearchCheck(pattern=\"lazy\").run(line_data, DUMMY_ANALYSIS_TARGET))\n line_data = get_line_data(line=AZ_STRING, pattern=re.compile(r\"(?Plazy)\"))\n # a word in value\n self.assertTrue(ValueSearchCheck(pattern=\"over lazy dog\").run(line_data, DUMMY_ANALYSIS_TARGET))\n" }, { "path": "tests/filters/test_value_similarity_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueSimilarityCheck\nfrom credsweeper.rules.rule import Rule\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueSimilarityCheck:\n\n @pytest.fixture\n def password_rule(self, config) -> Rule:\n pass_rule_without_filters = {\n \"name\": \"Password\",\n \"severity\": \"medium\",\n \"confidence\": \"moderate\",\n \"type\": \"keyword\",\n \"values\": [\"password|passwd|pwd\"],\n \"use_ml\": True,\n \"min_line_len\": 0,\n \"target\": [\"code\", \"doc\"],\n }\n rule = Rule(config, pass_rule_without_filters)\n return rule\n\n def test_value_similarity_check_p(self, password_rule: Rule, file_path: str, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path=file_path, line=success_line, pattern=password_rule.patterns[0])\n assert ValueSimilarityCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [\"password = 'password1'\", \"password = 'password123'\", \"pwd=$PWD\", '\"password\": \"password=`$vc1rQ5eBW*S`\"'])\n def test_value_similarity_check_n(self, password_rule: Rule, file_path: str, line: str) -> None:\n line_data = get_line_data(file_path=file_path, line=line, pattern=password_rule.patterns[0])\n assert ValueSimilarityCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_split_keyword_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueSplitKeywordCheck\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueSplitKeywordCheck:\n\n @pytest.mark.parametrize(\"line\", [\"abstract,and_so_on\", \"ani dammi lwnes\", \"unique#string\"])\n def test_value_split_keyword_check_p(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueSplitKeywordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"abstract and so on\", \"Any dummy lines\", \"unique string\"])\n def test_value_split_keyword_check_n(self, file_path: pytest.fixture, line: str) -> None:\n line_data = get_line_data(file_path, line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueSplitKeywordCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_string_type_check.py", "content": "import pytest\n\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters import ValueStringTypeCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueStringTypeCheck:\n\n def test_value_string_type_check_p(self, config: Config, success_line: pytest.fixture) -> None:\n file_path = \"path.txt\"\n line_data = get_line_data(config, file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueStringTypeCheck(config).run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"pass = DEAD314BEEF0CAFE\"])\n def test_value_string_type_check_n(self, config: Config, line: str) -> None:\n file_path = \"path.py\"\n line_data = get_line_data(config, file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueStringTypeCheck(config).run(line_data, DUMMY_ANALYSIS_TARGET) is True\n\n def test_value_string_type_check_none_path_n(self, config: Config, success_line: pytest.fixture) -> None:\n # even file_path is None it means \"\" - no extension\n file_path = None\n line_data = get_line_data(config, file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueStringTypeCheck(config).run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"pass = 314DEADBEEF0CAFE\"])\n def test_value_string_type_check_not_quoted_source_file_n(self, line: str, config: Config) -> None:\n file_path = \"path.py\"\n # guess, the keyword is TOKEN\n line_data = get_line_data(config, file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueStringTypeCheck(config).run(line_data, DUMMY_ANALYSIS_TARGET) is False\n" }, { "path": "tests/filters/test_value_token_base32_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueTokenBase32Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueTokenBase32Check:\n\n @pytest.mark.parametrize(\"line\", [\"4K26IPW7VBHMFT4D\", \"NAQ4BVWT\", \"WXFES7QNTET5DQYC\"])\n def test_value_token_base32_check_p(self, line: str) -> None:\n # import string;import random;print(''.join(random.choices(string.ascii_uppercase+'234567', k=16)))\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase32Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"OOOOOOMMMMMMMMMM\", \"1MZ0A9L2\", \"QAZXSWEDCVFRTGBN\"])\n def test_value_token_base32_check_n(self, line: str) -> None:\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase32Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_token_base36_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueTokenBase36Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueTokenBase36Check:\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"jvzec4y51fkrrd39czz1nfbw\", # 24\n \"nf6lqy74gp53f7w08gn4l0vrk\", # 25\n \"wpv1jq9xwanbn3n\", # 15\n \"123456789\", # 9 - not calculated\n ])\n def test_value_token_base36_check_p(self, line: str) -> None:\n # import string;import random;print(''.join(random.choices(string.digits+string.ascii_lowercase, k=15)))\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase36Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"100x200x300x400\", # 15\n \"qwertyui\", # 8\n \"0o9i8u7y6t5r4e3\", # 15\n \"0k9j8h7g6f5d4s3a\", # 16\n \"gfkjjhgy7r457y54jfhhgvcnf\", # 25\n ])\n def test_value_token_base36_check_n(self, line: str) -> None:\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase36Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_token_base64_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueTokenBase64Check\nfrom tests.filters.conftest import LINE_VALUE_PATTERN, DUMMY_ANALYSIS_TARGET\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueTokenBase64Check:\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"oXIO7p2R4Sx5UcHmUacu0-ojM8ELvCeskmyPuu4yaexoh5ExL4AFOWWI08G-IBVZ\", # 64\n \"9BlYTo-Fcthl_75PKfKQIWlYA6alA2uy\", # 32\n \"23OY2aMY4U3ubsQwBPvdyfYr\", # 24\n \"wSpv1jq9xwaXbn3n\", # 16\n ])\n def test_value_token_base64_check_p(self, line: str) -> None:\n # import string;import random;print(''.join(random.choices(string.digits+string.ascii_letters+'-_', k=64)))\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase64Check().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\n \"line\",\n [\n \"0oKiLoKkjUIhbYygVfcrTt6Dree3dSsBnJjiJKklLpMbV71X1QaSwDe23-9O_o01\", # 64\n \"09uulkjhbmnbvft565d4ddxvcvswq232\", # 32\n \"21WEasdVCfGGyrY6Ui8LkLpO\", # 24\n \"100x200x3S00x400\", # 16\n ])\n def test_value_token_base64_check_n(self, line: str) -> None:\n line_data = get_line_data(line=line, pattern=LINE_VALUE_PATTERN)\n assert ValueTokenBase64Check().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/filters/test_value_token_check.py", "content": "import pytest\n\nfrom credsweeper.filters import ValueTokenCheck\nfrom tests.filters.conftest import DUMMY_ANALYSIS_TARGET, KEYWORD_PASSWORD_PATTERN\nfrom tests.test_utils.dummy_line_data import get_line_data\n\n\nclass TestValueTokenCheck:\n\n def test_value_token_check_p(self, file_path: pytest.fixture, success_line: pytest.fixture) -> None:\n line_data = get_line_data(file_path, line=success_line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueTokenCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is False\n\n @pytest.mark.parametrize(\"line\", [\"pass=Crac>crackle1\", \"pass=my None:\n line_data = get_line_data(file_path, line=line, pattern=KEYWORD_PASSWORD_PATTERN)\n assert ValueTokenCheck().run(line_data, DUMMY_ANALYSIS_TARGET) is True\n" }, { "path": "tests/ml_model/__init__.py", "content": "" }, { "path": "tests/ml_model/test_features.py", "content": "import re\nfrom unittest import TestCase\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.common.constants import Severity, MAX_LINE_LENGTH\nfrom credsweeper.credentials.candidate import Candidate, LineData\nfrom credsweeper.ml_model.features.entropy_evaluation import EntropyEvaluation\nfrom credsweeper.ml_model.features.file_extension import FileExtension\nfrom credsweeper.ml_model.features.has_html_tag import HasHtmlTag\nfrom credsweeper.ml_model.features.is_secret_numeric import IsSecretNumeric\nfrom credsweeper.ml_model.features.length_of_attribute import LengthOfAttribute\nfrom credsweeper.ml_model.features.morpheme_dense import MorphemeDense\nfrom credsweeper.ml_model.features.rule_name import RuleName\nfrom credsweeper.ml_model.features.rule_severity import RuleSeverity\nfrom credsweeper.ml_model.features.search_in_attribute import SearchInAttribute\nfrom credsweeper.ml_model.features.word_in_path import WordInPath\nfrom credsweeper.ml_model.features.word_in_postamble import WordInPostamble\nfrom credsweeper.ml_model.features.word_in_preamble import WordInPreamble\nfrom credsweeper.ml_model.features.word_in_transition import WordInTransition\nfrom credsweeper.ml_model.features.word_in_value import WordInValue\nfrom credsweeper.ml_model.features.word_in_variable import WordInVariable\nfrom credsweeper.utils.util import Util\nfrom tests import AZ_STRING\n\nRE_TEST_PATTERN = re.compile(r\"quick (?Pbrown fox) jumps (?Pover) (?Pthe lazy) dog\")\n\n\nclass TestFeatures(TestCase):\n\n @staticmethod\n def init_feature_search_comment(comment: str) -> SearchInAttribute:\n feature = None\n model_config = Util.json_load(APP_PATH / \"ml_model\" / \"ml_config.json\")\n for feat in model_config[\"features\"]:\n if \"SearchInAttribute\" == feat[\"type\"] and comment == feat.get(\"comment\", ''):\n assert feature is None, f\"check duplication of '{comment}'\"\n feature = SearchInAttribute(**feat[\"kwargs\"])\n else:\n assert feature is not None, f\"missed SearchInAttribute for '{comment}'\"\n return feature\n\n def setUp(self):\n self.maxDiff = None\n self.model_config = Util.json_load(APP_PATH / \"ml_model\" / \"ml_config.json\")\n self.line_data = LineData(\n config=None,\n line=AZ_STRING,\n line_pos=0,\n line_num=1,\n path=\"src/path.ext\", # looks like after glob\n file_type=\".ext\",\n info=\"info\",\n pattern=RE_TEST_PATTERN)\n self.candidate = Candidate(line_data_list=[self.line_data],\n patterns=[],\n rule_name=\"rule\",\n severity=Severity.MEDIUM)\n\n def test_entropy_evaluation_n(self):\n feature = EntropyEvaluation()\n candidate = self.candidate\n self.line_data.value = \"\\0\\0\\0\"\n self.assertListEqual([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],\n feature.extract(candidate).tolist())\n\n def test_entropy_evaluation_p(self):\n feature = EntropyEvaluation()\n candidate = self.candidate\n extracted1 = feature.extract(candidate).tolist()\n self.assertListEqual([1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],\n extracted1)\n self.line_data.value = \"bace4d19-fa7e-beef-cafe-9129474bcd81\"\n extracted2 = feature.extract(candidate).tolist()\n self.assertListEqual([\n 0.7041769027709961, 0.6943118572235107, 0.6783386468887329, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,\n 1.0, 0.0, 0.0, 1.0, 1.0\n ], extracted2)\n\n def test_file_extension_n(self):\n self.assertListEqual([[0, 0, 0]], FileExtension([\".txt\", \".doc\", \".exe\"])([self.candidate]).tolist())\n\n def test_file_extension_p(self):\n self.assertListEqual([[0, 0, 1]], FileExtension([\".0\", \".abc\", \".ext\"])([self.candidate]).tolist())\n\n def test_length_attribute_unsupported_n(self):\n with self.assertRaises(Exception):\n LengthOfAttribute(\"separator\")\n\n def test_length_attribute_empty_n(self):\n feature = LengthOfAttribute(\"line\")\n candidate = self.candidate\n self.line_data.line = ''\n self.assertListEqual([0.0], feature.extract(candidate).tolist())\n\n def test_length_attribute_oversize_n(self):\n feature = LengthOfAttribute(\"line\")\n candidate = self.candidate\n self.line_data.line = ' ' * MAX_LINE_LENGTH\n self.assertListEqual([1.0], feature.extract(candidate).tolist())\n\n def test_length_attribute_p(self):\n feature = LengthOfAttribute(\"value\")\n candidate = self.candidate\n self.assertListEqual([0.12307692307692308], feature.extract(candidate).tolist())\n\n def test_word_in_path_empty_n(self):\n self.line_data.path = \"\"\n self.assertListEqual([[0, 0, 0, 0]], WordInPath([\"dog\", \"lazy\", \"small\", \"the\"])([self.candidate]).tolist())\n\n def test_word_in_path_n(self):\n self.assertListEqual([[0, 0, 0, 0]], WordInPath([\"dog\", \"lazy\", \"small\", \"the\"])([self.candidate]).tolist())\n\n def test_word_in_path_p(self):\n self.assertListEqual([[1, 1, 0, 0]], WordInPath([\"/src\", \"/path\", \"small\", \"the\"])([self.candidate]).tolist())\n\n def test_word_in_value_empty_n(self):\n self.line_data.value = None\n self.assertListEqual([[0, 0, 0, 0]], WordInValue([\"aaa\", \"bbb\", \"ccc\", \"ddd\"]).extract(self.candidate).tolist())\n\n def test_word_in_value_n(self):\n self.assertListEqual([[0, 0, 0, 0]], WordInValue([\"aaa\", \"bbb\", \"ccc\", \"ddd\"]).extract(self.candidate).tolist())\n\n def test_word_in_value_p(self):\n self.assertListEqual([[0, 1, 0, 1]],\n WordInValue([\"the\", \"small\", \"lazy\", \"dog\"]).extract(self.candidate).tolist())\n\n def test_word_in_variable_empty_n(self):\n self.line_data.variable = None\n self.assertListEqual([[0, 0, 0, 0]],\n WordInVariable([\"aaa\", \"bbb\", \"ccc\", \"ddd\"]).extract(self.candidate).tolist())\n\n def test_word_in_variable_n(self):\n self.assertListEqual([[0, 0, 0, 0]],\n WordInVariable([\"aaa\", \"bbb\", \"ccc\", \"ddd\"]).extract(self.candidate).tolist())\n\n def test_word_in_variable_p(self):\n self.assertListEqual([[1, 1, 0, 0]],\n WordInVariable([\"brown\", \"fox\", \"lazy\", \"the\"]).extract(self.candidate).tolist())\n\n def test_word_in_preamble_dup_n(self):\n with self.assertRaises(Exception):\n WordInPreamble([\"fox\", \"fox\"])\n\n def test_word_in_preamble_empty_n(self):\n self.line_data.line = \"\"\n self.line_data.value_start = 0\n test = WordInPreamble([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_preamble_n(self):\n test = WordInPreamble([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_preamble_p(self):\n test = WordInPreamble([\"dog\", \"the\"])\n self.assertListEqual([[0, 1]], test.extract(self.candidate).tolist())\n\n def test_word_in_transition_dup_n(self):\n with self.assertRaises(Exception):\n WordInTransition([\"fox\", \"fox\"])\n\n def test_word_in_transition_empty_n(self):\n self.line_data.line = \"\"\n self.line_data.value_start = 0\n test = WordInTransition([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_transition_n(self):\n test = WordInTransition([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_transition_p(self):\n test = WordInTransition([\"fox\", \"jumps\"])\n self.assertListEqual([[0, 1]], test.extract(self.candidate).tolist())\n\n def test_word_in_postamble_dup_n(self):\n with self.assertRaises(Exception):\n WordInPostamble([\"dog\", \"dog\"])\n\n def test_word_in_postamble_empty_n(self):\n self.line_data.line = \"\"\n self.line_data.value_start = 0\n test = WordInPostamble([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_postamble_n(self):\n test = WordInPostamble([\"dummy\", \"text\"])\n self.assertListEqual([[0, 0]], test.extract(self.candidate).tolist())\n\n def test_word_in_postamble_p(self):\n test = WordInPostamble([\"dog\", \"fox\"])\n self.assertListEqual([[1, 0]], test.extract(self.candidate).tolist())\n\n def test_has_html_tag_empty_n(self):\n self.line_data.line = \"\"\n self.line_data.value_start = 0\n test = HasHtmlTag()\n self.assertEqual(-1.0, test.extract(self.candidate))\n\n def test_has_html_tag_n(self):\n test = HasHtmlTag()\n self.assertEqual(-1.0, test.extract(self.candidate))\n\n def test_has_html_tag_p(self):\n test = HasHtmlTag()\n self.line_data.line = f\"
    {self.line_data.line}\"\n self.assertEqual(1.0, test.extract(self.candidate))\n self.line_data.line = f\"

    {self.line_data.line}

    \"\n self.assertEqual(1.0, test.extract(self.candidate))\n\n def test_is_secret_numeric_empty_n(self):\n self.line_data.value = \"\"\n test = IsSecretNumeric()\n self.assertEqual(-1.0, test.extract(self.candidate))\n\n def test_is_secret_numeric_n(self):\n test = IsSecretNumeric()\n self.assertEqual(-1.0, test.extract(self.candidate))\n\n def test_is_secret_numeric_p(self):\n test = IsSecretNumeric()\n self.line_data.value = \"2e+64\"\n self.assertEqual(1.0, test.extract(self.candidate))\n self.line_data.value = \"2.718281828\"\n self.assertEqual(1.0, test.extract(self.candidate))\n self.line_data.value = \"-0.5\"\n self.assertEqual(1.0, test.extract(self.candidate))\n self.line_data.value = \".33\"\n self.assertEqual(1.0, test.extract(self.candidate))\n self.line_data.value = \"+.33e-2\"\n\n def test_search_in_attribute_line_empty_n(self):\n self.line_data.line = \"\"\n self.assertEqual(-1.0, SearchInAttribute(\"^the lazy dog$\", \"line\").extract(self.candidate))\n\n def test_search_in_attribute_variable_empty_n(self):\n self.line_data.variable = \"\"\n self.assertEqual(-1.0, SearchInAttribute(\".*dog\", \"variable\").extract(self.candidate))\n self.line_data.variable = None\n self.assertEqual(-1.0, SearchInAttribute(\".*dog\", \"variable\").extract(self.candidate))\n\n def test_search_in_attribute_value_empty_n(self):\n self.line_data.value = \"\"\n self.assertEqual(-1.0, SearchInAttribute(\"fox\", \"value\").extract(self.candidate))\n\n def test_search_in_attribute_n(self):\n self.assertEqual(-1.0, SearchInAttribute(\"^the lazy dog$\", \"line\").extract(self.candidate))\n self.assertEqual(-1.0, SearchInAttribute(\".*dog\", \"variable\").extract(self.candidate))\n self.assertEqual(-1.0, SearchInAttribute(\"fox\", \"value\").extract(self.candidate))\n\n def test_search_in_attribute_p(self):\n self.assertEqual(1.0, SearchInAttribute(\".*the lazy dog$\", \"line\").extract(self.candidate))\n self.assertEqual(1.0, SearchInAttribute(\".*fox\", \"variable\").extract(self.candidate))\n self.assertEqual(1.0, SearchInAttribute(\"over\", \"separator\").extract(self.candidate))\n self.assertEqual(1.0, SearchInAttribute(\"^the lazy$\", \"value\").extract(self.candidate))\n\n def test_morpheme_dense_n(self):\n self.line_data.value = \"5A1T\"\n self.assertEqual(0, MorphemeDense().extract(self.candidate))\n self.line_data.value = \"ZaQ1@wSxCdE3$rFvbGt56yhNmJu7*ik\"\n self.assertEqual(0, MorphemeDense().extract(self.candidate))\n\n def test_morpheme_dense_p(self):\n self.assertEqual(0.875, MorphemeDense().extract(self.candidate))\n self.line_data.value = \"KeyApiPasswordToken\"\n self.assertEqual(1.0, MorphemeDense().extract(self.candidate))\n self.line_data.value = \"salt:saltSALTsalt\"\n self.assertEqual(0.9411764705882353, MorphemeDense().extract(self.candidate))\n self.line_data.value = \"deadbeefdeadbeefdeadbeefdeadbeefdeadbeef\"\n self.assertEqual(1.0, MorphemeDense().extract(self.candidate))\n\n def test_rule_name_n(self):\n self.assertListEqual([[0, 0]], RuleName([\"dummy\", \"test\"])([self.candidate]).tolist())\n\n def test_rule_name_p(self):\n self.assertListEqual([[0, 1]], RuleName([\"mock\", \"rule\"])([self.candidate]).tolist())\n\n COMMENT_STYLES = [\n \"camelStyle naming detection\",\n \"PascalStyle naming detection\",\n \"UPPERCASE naming detection\",\n \"lowercase naming detection\",\n ]\n STYLES_MAP = {\n \"\": None, #\n \"iii111oooXoooXoo\": None, #\n \"n0tCamlStyle23\": None, #\n \"notCam3lStyle23\": None, #\n \"NotPa5calStyle\": None, #\n \"__n0t_example_some_name_in_code_4__example\": None, #\n \"_N0T_EXAMPLE_WR0NG_\": None, #\n \"__MAIN__\": None, #\n \"___SLAVE\": None, #\n \"NOTEXAMPLE\": None, #\n \"4_EXAMPLE_NOT_VAR\": None, #\n \"PascalStyle\": \"PascalStyle naming detection\", #\n \"Pascal33Style\": \"PascalStyle naming detection\", #\n \"PascalX86Style\": \"PascalStyle naming detection\", #\n \"camelStyle\": \"camelStyle naming detection\", #\n \"testCamelStyle1\": \"camelStyle naming detection\", #\n \"test23Camel43Style65\": \"camelStyle naming detection\", #\n \"camelX86Style\": \"camelStyle naming detection\", #\n \"_MY_X86_DEMO_VAR\": \"UPPERCASE naming detection\", #\n \"_42_YOU_VAR\": \"UPPERCASE naming detection\", #\n \"_4_YOU_\": \"UPPERCASE naming detection\", #\n \"_H204__U_\": \"UPPERCASE naming detection\", #\n \"_AARCH64_X86_FLUCTUATOR\": \"UPPERCASE naming detection\", #\n \"EXAMPLE_IS_VAR\": \"UPPERCASE naming detection\", #\n \"EXAMPLE__VAR\": \"UPPERCASE naming detection\", #\n \"some_name_in_code\": \"lowercase naming detection\", #\n \"___some_name_in_code_4__example\": \"lowercase naming detection\", #\n }\n\n def test_style_n(self):\n candidate = self.candidate\n for comment in self.COMMENT_STYLES:\n feature = self.init_feature_search_comment(comment)\n for val, typ in self.STYLES_MAP.items():\n if typ is None or typ != comment:\n candidate.line_data_list[0].value = val\n self.assertEqual(-1.0, feature.extract(candidate), (comment, typ, val))\n\n def test_style_p(self):\n candidate = self.candidate\n for comment in self.COMMENT_STYLES:\n feature = self.init_feature_search_comment(comment)\n for val, typ in self.STYLES_MAP.items():\n if typ == comment:\n candidate.line_data_list[0].value = val\n self.assertEqual(1.0, feature.extract(candidate), (comment, typ, val))\n\n def test_rule_severity_n(self):\n self.candidate.severity = Severity.INFO\n self.assertEqual(0.0, RuleSeverity().extract(self.candidate))\n self.candidate.severity = None\n with self.assertRaises(ValueError):\n RuleSeverity().extract(self.candidate)\n\n def test_rule_severity_p(self):\n self.line_data.value = \"\"\n self.assertEqual(0.5, RuleSeverity().extract(self.candidate))\n self.candidate.severity = Severity.CRITICAL\n self.assertEqual(1.0, RuleSeverity().extract(self.candidate))\n" }, { "path": "tests/ml_model/test_ml_validator.py", "content": "import copy\nimport re\nimport unittest\nfrom typing import Tuple\n\nimport numpy as np\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.common.constants import Severity, MAX_LINE_LENGTH, MIN_DATA_LEN, ThresholdPreset\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.candidate import Candidate\nfrom credsweeper.credentials.candidate_key import CandidateKey\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.ml_model.ml_validator import MlValidator\nfrom credsweeper.utils.util import Util\nfrom tests import AZ_STRING, ML_DELTA\n\n\nclass TestMlValidator(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n self.ml_validator = MlValidator(threshold=ThresholdPreset.medium)\n assert self.ml_validator is not None\n file_name = APP_PATH / \"secret\" / \"config.json\"\n config_dict = Util.json_load(file_name)\n config_dict[\"use_filters\"] = True\n config_dict[\"find_by_ext\"] = False\n config_dict[\"pedantic\"] = False\n config_dict[\"depth\"] = 0\n config_dict[\"doc\"] = False\n config_dict[\"find_by_ext_list\"] = []\n config_dict[\"size_limit\"] = None\n self.config = Config(config_dict)\n\n def validate(self, _candidate: Candidate) -> Tuple[bool, float]:\n \"\"\"Validate single credential candidate.\"\"\"\n candidate_key = CandidateKey(_candidate.line_data_list[0])\n sample_as_batch = [(candidate_key, [_candidate])]\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 1)\n return is_cred_batch[0], probability_batch[0]\n\n def test_ml_validator_simple_n(self):\n candidate = Candidate.get_dummy_candidate(self.config, \"main.py\", \".py\", \"info\", \"Password\")\n candidate.line_data_list[0].line = 'password=\"Ahga%$FiQ@Ei8\"'\n candidate.line_data_list[0].variable = \"password\"\n candidate.line_data_list[0].value_start = 16\n candidate.line_data_list[0].value_end = 25\n candidate.line_data_list[0].value = \"Ahga%$FiQ@Ei8\"\n\n decision, probability = self.validate(candidate)\n self.assertAlmostEqual(0.9873854517936707, probability, delta=ML_DELTA)\n\n candidate.line_data_list[0].path = \"main.yaml\"\n candidate.line_data_list[0].file_type = \".yaml\"\n decision, probability = self.validate(candidate)\n self.assertAlmostEqual(0.9031195044517517, probability, delta=ML_DELTA)\n\n candidate.line_data_list[0].path = \"main.zip\"\n candidate.line_data_list[0].file_type = \".zip\"\n decision, probability = self.validate(candidate)\n self.assertAlmostEqual(0.8412226438522339, probability, delta=ML_DELTA)\n\n candidate.line_data_list[0].path = \"main.txt\"\n candidate.line_data_list[0].file_type = \".txt\"\n decision, probability = self.validate(candidate)\n self.assertAlmostEqual(0.8234410285949707, probability, delta=ML_DELTA)\n\n def test_ml_validator_auxiliary_p(self):\n candidate = Candidate.get_dummy_candidate(self.config, \"mycred\", \"\", \"\", \"Secret\")\n candidate.line_data_list[0].line = \"secret=238475614782\"\n candidate.line_data_list[0].variable = \"secret\"\n candidate.line_data_list[0].value_start = 7\n candidate.line_data_list[0].value_end = 43\n candidate.line_data_list[0].value = \"238475614782\"\n # auxiliary candidate for a pattern rule - without variable\n aux_candidate = copy.deepcopy(candidate)\n aux_candidate.line_data_list[0].variable = None\n\n # todo: the scores are low for current ML model - will be changed after train\n\n candidate_key = CandidateKey(candidate.line_data_list[0])\n sample_as_batch = [(candidate_key, [candidate])]\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.591613233089447, probability_batch[0], delta=ML_DELTA)\n\n # auxiliary rule which was not trained - keeps the same ML probability\n aux_candidate.rule_name = \"PASSWD_PAIR\"\n sample_as_batch = [(candidate_key, [candidate, aux_candidate])]\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.591613233089447, probability_batch[0], delta=ML_DELTA)\n\n # auxiliary rule in train increases ML probability\n aux_candidate.rule_name = \"Token\"\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.6740559339523315, probability_batch[0], delta=ML_DELTA)\n\n # which real line may be\n candidate.line_data_list[0].line = \"secret=func(token=238475614782)\"\n aux_candidate.line_data_list[0].line = \"secret=func(token=238475614782)\"\n aux_candidate.line_data_list[0].variable = \"token\"\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.5733864307403564, probability_batch[0], delta=ML_DELTA)\n\n def test_ml_validator_auxiliary_n(self):\n candidate = Candidate.get_dummy_candidate(self.config, \"secret\", \"\", \"\", \"Secret\")\n candidate.line_data_list[0].line = \"secret=bace4d19-dead-beef-cafe-9129474bcd81\"\n candidate.line_data_list[0].variable = \"secret\"\n candidate.line_data_list[0].value_start = 7\n candidate.line_data_list[0].value_end = 43\n candidate.line_data_list[0].value = \"bace4d19-dead-beef-cafe-9129474bcd81\"\n # auxiliary candidate for a pattern rule - without variable\n aux_candidate = copy.deepcopy(candidate)\n aux_candidate.line_data_list[0].variable = None\n\n # todo: the scores are low for current ML model - will be changed after train\n\n candidate_key = CandidateKey(candidate.line_data_list[0])\n sample_as_batch = [(candidate_key, [candidate])]\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.9984369277954102, probability_batch[0], delta=ML_DELTA)\n\n # auxiliary rule in train does not increase ML probability yet - will be used after next train\n\n aux_candidate.rule_name = \"UUID\"\n sample_as_batch = [(candidate_key, [candidate, aux_candidate])]\n is_cred_batch, probability_batch = self.ml_validator.validate_groups(sample_as_batch, 2)\n self.assertAlmostEqual(0.9984369277954102, probability_batch[0], delta=ML_DELTA)\n\n def test_extract_features_n(self):\n candidate1 = Candidate.get_dummy_candidate(self.config, \"___.x3\", \".x3\", \"\", \"\")\n candidate1.line_data_list[0].line = ''\n candidate1.line_data_list[0].variable = ''\n candidate1.line_data_list[0].value_start = 0\n candidate1.line_data_list[0].value_end = 0\n candidate1.line_data_list[0].value = ''\n features1 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(20, np.count_nonzero(features1))\n\n def test_extract_features_p(self):\n candidate1 = Candidate.get_dummy_candidate(self.config, \"???.py\", \".py\", \"\", \"???????\")\n candidate1.line_data_list[0].line = '??????????????????????????'\n candidate1.line_data_list[0].variable = \"???????\"\n candidate1.line_data_list[0].value_start = 2\n candidate1.line_data_list[0].value_end = 6\n candidate1.line_data_list[0].value = \"???????????????????\"\n features1_0 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(28, np.count_nonzero(features1_0))\n candidate1.rule_name = \"Password\"\n features1_1 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(29, np.count_nonzero(features1_1))\n candidate1.line_data_list[0].value = \"example/\"\n features1_2 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(36, np.count_nonzero(features1_2))\n candidate1.line_data_list[0].value = \"undefined/\"\n features1_3 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(35, np.count_nonzero(features1_3))\n candidate1.line_data_list[0].value = \"undefined/example\"\n features1_4 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(36, np.count_nonzero(features1_4))\n\n candidate2 = copy.deepcopy(candidate1)\n candidate2.rule_name = \"UNKNOWN RULE\"\n features2 = self.ml_validator.extract_features([candidate1, candidate2])\n self.assertEqual(36, np.count_nonzero(features2))\n candidate2.rule_name = \"Secret\"\n features3 = self.ml_validator.extract_features([candidate1, candidate2])\n self.assertEqual(37, np.count_nonzero(features3))\n\n def testVariableNotAllowedPatternCheck_n(self):\n candidate1 = Candidate.get_dummy_candidate(self.config, \"???.py\", \".py\", \"\", \"##########\")\n candidate1.line_data_list[0].line = '?????????????:!!!!!!!!!!!!!'\n candidate1.line_data_list[0].variable = \"?????????????\"\n candidate1.line_data_list[0].value_start = 14\n candidate1.line_data_list[0].value_end = 27\n candidate1.line_data_list[0].value = \"!!!!!!!!!!!!!\"\n features1_1 = self.ml_validator.extract_features([candidate1])\n\n self.assertEqual(27, np.count_nonzero(features1_1))\n candidate1.line_data_list[0].variable = \"pub_key\"\n features1_2 = self.ml_validator.extract_features([candidate1])\n self.assertEqual(27, np.count_nonzero(features1_2))\n\n def test_extract_features_normalized_n(self):\n line_data = LineData(config=self.config,\n line=AZ_STRING,\n line_pos=0,\n line_num=1,\n path=\"path.ext\",\n file_type=\"type\",\n info=\"info\",\n pattern=re.compile(r\"(?P.*) (?Pover) (?P.+)\"))\n candidate = Candidate([line_data], [], \"rule\", Severity.MEDIUM)\n features = self.ml_validator.extract_features([candidate])\n self.assertLess(0, np.count_nonzero(features))\n for i in features.tolist()[0]:\n self.assertLessEqual(-1.0, i)\n self.assertGreaterEqual(1.0, i)\n\n def test_encode_n(self):\n self.assertEqual(0, np.count_nonzero(self.ml_validator.encode(None, 0)))\n self.assertEqual(0, np.count_nonzero(self.ml_validator.encode(\"\", 10)))\n self.assertEqual(0, np.count_nonzero(self.ml_validator.encode(\"AAA\", 0)))\n\n def test_encode_p(self):\n self.assertEqual(MIN_DATA_LEN, np.count_nonzero(self.ml_validator.encode(AZ_STRING, MIN_DATA_LEN)))\n self.assertEqual(len(AZ_STRING), np.count_nonzero(self.ml_validator.encode(AZ_STRING, MAX_LINE_LENGTH)))\n self.assertEqual(7, np.count_nonzero(self.ml_validator.encode(\"\\xFE\\xFF \\n\\t`\\0\", MIN_DATA_LEN)))\n self.assertEqual(\n [[\n 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ],\n [\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,\n 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0\n ]],\n self.ml_validator.encode(\"\\xFE\\xFF \\n\\t`\\0\", MIN_DATA_LEN).tolist())\n" }, { "path": "tests/rules/__init__.py", "content": "" }, { "path": "tests/rules/common.py", "content": "from typing import List\n\nimport pytest\n\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\n\n\nclass BaseTestRule:\n\n def test_scan_p(self, file_path: pytest.fixture, lines: pytest.fixture,\n scanner_without_filters: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=file_path)\n scan_result = scanner_without_filters.scan(provider)\n assert len(scan_result) == 1, (lines, scan_result)\n\n @pytest.mark.parametrize(\"lines\",\n [[\"\"], [\"String secret = new String('p****');\"], [\"SZa6TWGF2XuWdl7c2s2xB1iSlnZJLbvH\"]])\n def test_scan_n(self, file_path: pytest.fixture, lines: List[str], scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 0, scan_result[0]\n\n\nclass BaseTestNoQuotesRule:\n \"\"\"\n If secret declared in a code file (\".cpp\", \".py\", etc) in should be escaped with quotes. Otherwise it cannot be a\n string secret, as no string literal declared.\n Exceptions: comments. In comment secret can be unquoted\n\n This test checks if unquoted password is not comment and declared in code file.\n \"\"\"\n\n def test_scan_quote_p(self, file_path: pytest.fixture, lines: pytest.fixture, scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 1, (lines, scan_result)\n\n def test_scan_quote_n(self, python_file_path: pytest.fixture, lines: pytest.fixture,\n scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=python_file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 0, scan_result\n\n\nclass BaseTestCommentRule:\n \"\"\"\n If secret declared in a code file (\".cpp\", \".py\", etc) in should be escaped with quotes. Otherwise it cannot be a\n string secret, as no string literal declared.\n Exceptions: comments. In comment secret can be unquoted\n\n This test checks if unquoted password is comment in code file\n \"\"\"\n\n def test_scan_comment_p(self, python_file_path: pytest.fixture, lines: pytest.fixture,\n scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=python_file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 1, (lines, scan_result)\n\n def test_scan_comment_n(self, python_file_path: pytest.fixture, lines: pytest.fixture,\n scanner: pytest.fixture) -> None:\n lines = [line[1:] for line in lines]\n provider = StringContentProvider(lines, file_path=python_file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 0, scan_result\n\n\nclass BaseTestMultiRule:\n\n def test_scan_line_data_p(self, file_path: pytest.fixture, lines: pytest.fixture, scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines)\n scan_result = scanner.scan(provider)\n assert len(scan_result) != 0\n assert len(scan_result[0].line_data_list) == 2\n\n def test_scan_line_data_n(self, file_path: pytest.fixture, scanner: pytest.fixture) -> None:\n lines = [\"\"]\n provider = StringContentProvider(lines)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 0\n" }, { "path": "tests/rules/test_api.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestApi(BaseTestRule):\n\n @pytest.fixture(params=[[\"gi_reo_gi_api = \\\"@@cacklecackle_gi_reo_gi@@\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"API\"\n" }, { "path": "tests/rules/test_auth.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestAuth(BaseTestRule):\n\n @pytest.fixture(params=[[\"oauth_nonce: '1gZG4eh6qR6Ul2pqbKc5PwKjNlKadCwW7VW4uSyi9',\"], [\"authold = 'gigigi'\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture(params=[\"\", \"author='bob'\"])\n def empty_line(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Auth\"\n" }, { "path": "tests/rules/test_aws_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestAwsKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"\\\"AwsAccessKey\\\": \\\"AKIAGIREOGIAWSKEY123\\\",\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"AWS Client ID\"\n" }, { "path": "tests/rules/test_aws_multi.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestMultiRule, BaseTestRule\n\n\nclass TestAwsMulti(BaseTestRule, BaseTestMultiRule):\n\n @pytest.fixture(params=[[\n \"\\\"AwsAccessKey\\\": \\\"AKIAGIREOGIAWSKEY123\\\",\", \"\\\"AwsSecretKey\\\": \\\"exA3p1E42db9bbba8f7ea0f9e47b287de5fc7E57\\\"\"\n ]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"AWS Multi\"\n" }, { "path": "tests/rules/test_aws_mws_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestAwsMwsKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"AWS_MWS_KEY = \\\"amzn.mws.abcaef12-1231-5671-1231-abadea123156\\\"\\n\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"AWS MWS Key\"\n" }, { "path": "tests/rules/test_credential.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestCredential(BaseTestRule):\n\n @pytest.fixture(params=[[\"gi_reo_gi_credential = \\\"cracklecrackle\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Credential\"\n" }, { "path": "tests/rules/test_dynatrace_api_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestStripeApiKey(BaseTestRule):\n # Example from official site\n # https://www.dynatrace.com/support/help/dynatrace-api/basics/dynatrace-api-authentication/\n @pytest.fixture(\n params=[[\"dt0c01.ST2EY72KQINMH574WMNVI7YN.G3DFPBEJYMODIDAEX454M7YWBUVEFOWKPRVMWFASS64NFH52PX6BNDVFFM572RZM\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Dynatrace API Token\"\n" }, { "path": "tests/rules/test_facebook_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestFacebookKey(BaseTestRule):\n\n @pytest.fixture(params=[[\n 'FACEBOOK_T0KEN = '\n '\"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\"'\n ]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Facebook Access Token\"\n" }, { "path": "tests/rules/test_firebase_domain.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestFirebasDomain(BaseTestRule):\n\n @pytest.fixture(params=[ #\n [\"api-project-615509201590.firebaseio.com\"], #\n [\"api-project-615509201590.firebaseapp.com\"] #\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Firebase Domain\"\n" }, { "path": "tests/rules/test_github_classic_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestClassicToken(BaseTestRule):\n\n @pytest.fixture(params=[ #\n [\"ghu_00000000000000000000000000000004WZ4EQ\"] #\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Github Classic Token\"\n" }, { "path": "tests/rules/test_github_fine_granted_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestGithubFineGrantedToken(BaseTestRule):\n\n @pytest.fixture(params=[\n [\"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Q\"], #\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Github Fine-granted Token\"\n" }, { "path": "tests/rules/test_google_api_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestGoogleApiKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"AIzaGiReoGiCrackleCrackle12315618112315\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Google API Key\"\n" }, { "path": "tests/rules/test_google_multi.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestMultiRule, BaseTestRule\n\n\nclass TestGoogleMulti(BaseTestRule, BaseTestMultiRule):\n\n @pytest.fixture(\n params=[[\"012-gireogigireogigireogigireogi1230.apps.googleusercontent.com\\n\", \"4L2QMyTm6Rr0o46ytGiReoG1\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Google Multi\"\n" }, { "path": "tests/rules/test_google_oauth_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestGoogleOAuthKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"google_oauth = \\\"ya29.gi_reo_gi_crackle_ln22\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Google OAuth Access Token\"\n" }, { "path": "tests/rules/test_instagram_access_token.py", "content": "import random\nimport string\nfrom typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestInstagramAccessToken(BaseTestRule):\n\n @pytest.fixture(\n params=[[\"IGQVJ\" + ''.join(random.choice(string.ascii_letters + string.digits) for i in range(157))]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Instagram Access Token\"\n" }, { "path": "tests/rules/test_jwt.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestJwt(BaseTestRule):\n\n @pytest.fixture(params=[[\n \"jwt: 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxN\"\n \"TE2MjM5MDIyLCJ0ZXN0IjoiSSBuZWVkIHJlYWxseSByZWFsbHkgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nI\"\n \"GxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvb\"\n \"mcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgb\"\n \"G9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZ\"\n \"yBsb25nIGxvbmcgbG9uZyBsb25nIGxvbmcgbG9uZyBqd3QgdG9rZW4ifQ.4pWgA4mthx4FPPh1AZQY0luTKTQ7VOj6PGwwiANvtqg'\"\n ]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"JSON Web Token\"\n" }, { "path": "tests/rules/test_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"hmac_key = 'zdosafhzwhpelghs';\"], [\"keydocker = 'gigigi'\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture(params=[\"\", \"keyword='hamming'\"])\n def empty_line(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Key\"\n" }, { "path": "tests/rules/test_mailchimp_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestMailChimpKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"mailchimp_key = \\\"abcaefaacdaf01214561891121451781-us12\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"MailChimp API Key\"\n" }, { "path": "tests/rules/test_nonce.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestNone(BaseTestRule):\n\n @pytest.fixture(params=[[\"nonce = '0vXb8c1vXzgU5m2591'\"], [\"nonce = 'a1L28lmUiLnOUVJRVl'\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture(params=[\"\", \"keyword='hamming'\"])\n def empty_line(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Nonce\"\n" }, { "path": "tests/rules/test_password.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestCommentRule, BaseTestNoQuotesRule, BaseTestRule\n\n\nclass TestPassword(BaseTestRule):\n\n @pytest.fixture(params=[[\"password = \\\"cackle!\\\"\"], [\"gi_reo_gi_passwd = \\\"cackle!\\\"\"], [\"pwd = \\\"cackle!\\\"\"],\n [\"data[\\\"pwd\\\"] = \\\"cackle!\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Password\"\n\n\nclass TestPasswordNoQuotes(BaseTestNoQuotesRule):\n\n @pytest.fixture(params=[[\"password = cackle!\"], [\"gi_reo_gi_passwd = cackle!\"], [\"pwd = cackle!\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Password\"\n\n\nclass TestPasswordComment(BaseTestCommentRule):\n\n @pytest.fixture(params=[[\"# password = cackle!\"], [\"# gi_reo_gi_passwd = cackle!\"], [\"# pwd = cackle!\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Password\"\n" }, { "path": "tests/rules/test_paypal_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestPayPalKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"access_token$production$gireogi121451781$abcaeaabadef01134517891121451781\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"PayPal Braintree Access Token\"\n" }, { "path": "tests/rules/test_pem_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom .common import BaseTestRule\n\n\nclass TestPemKey(BaseTestRule):\n\n @pytest.fixture(params=[\n [\n \"-----BEGIN RSA PRIVATE KEY-----\", #\n \"MIICXAIBAAKBgQCqGKukO1De7zhZj6+H0qtjTkVxwTCpvKe4eCZ0FPqri0cb2JZfXJ/DgYSF6vUp\", #\n \"wmJG8wVQZKjeGcjDOL5UlsuusFncCzWBQ7RKNUSesmQRMSGkVb1/3j+skZ6UtW+5u09lHNsj6tQ5\", #\n \"1s1SPrCBkedbNf0Tp0GbMJDyR4e9T04ZZwIDAQABAoGAFijko56+qGyN8M0RVyaRAXz++xTqHBLh\", #\n \"3tx4VgMtrQ+WEgCjhoTwo23KMBAuJGSYnRmoBZM3lMfTKevIkAidPExvYCdm5dYq3XToLkkLv5L2\", #\n \"pIIVOFMDG+KESnAFV7l2c+cnzRMW0+b6f8mR1CJzZuxVLL6Q02fvLi55/mbSYxECQQDeAw6fiIQX\", #\n \"GukBI4eMZZt4nscy2o12KyYner3VpoeE+Np2q+Z3pvAMd/aNzQ/W9WaI+NRfcxUJrmfPwIGm63il\", #\n \"AkEAxCL5HQb2bQr4ByorcMWm/hEP2MZzROV73yF41hPsRC9m66KrheO9HPTJuo3/9s5p+sqGxOlF\", #\n \"L0NDt4SkosjgGwJAFklyR1uZ/wPJjj611cdBcztlPdqoxssQGnh85BzCj/u3WqBpE2vjvyyvyI5k\", #\n \"X6zk7S0ljKtt2jny2+00VsBerQJBAJGC1Mg5Oydo5NwD6BiROrPxGo2bpTbu/fhrT8ebHkTz2epl\", #\n \"U9VQQSQzY1oZMVX8i1m5WUTLPz2yLJIBQVdXqhMCQBGoiuSoSjafUhV7i1cEGpb88h5NBYZzWXGZ\", #\n \"37sJ5QsW+sJyoNde3xH8vdXhzU7eT82D6X/scw9RZz+/6rCJ4p0=\", #\n \"-----END RSA PRIVATE KEY-----\" #\n ],\n [\n \"-----BEGIN RSA PRIVATE KEY-----\", #\n \"Proc-Type: 4,ENCRYPTED\", #\n \"DEK-Info: AES-256-CBC,2AA219GG746F88F6DDA0D852A0FD3211\", #\n \"MIICXAIBAAKBgQCqGKukO1De7zhZj6+H0qtjTkVxwTCpvKe4eCZ0FPqri0cb2JZfXJ/DgYSF6vUp\", #\n \"wmJG8wVQZKjeGcjDOL5UlsuusFncCzWBQ7RKNUSesmQRMSGkVb1/3j+skZ6UtW+5u09lHNsj6tQ5\", #\n \"1s1SPrCBkedbNf0Tp0GbMJDyR4e9T04ZZwIDAQABAoGAFijko56+qGyN8M0RVyaRAXz++xTqHBLh\", #\n \"3tx4VgMtrQ+WEgCjhoTwo23KMBAuJGSYnRmoBZM3lMfTKevIkAidPExvYCdm5dYq3XToLkkLv5L2\", #\n \"pIIVOFMDG+KESnAFV7l2c+cnzRMW0+b6f8mR1CJzZuxVLL6Q02fvLi55/mbSYxECQQDeAw6fiIQX\", #\n \"GukBI4eMZZt4nscy2o12KyYner3VpoeE+Np2q+Z3pvAMd/aNzQ/W9WaI+NRfcxUJrmfPwIGm63il\", #\n \"AkEAxCL5HQb2bQr4ByorcMWm/hEP2MZzROV73yF41hPsRC9m66KrheO9HPTJuo3/9s5p+sqGxOlF\", #\n \"L0NDt4SkosjgGwJAFklyR1uZ/wPJjj611cdBcztlPdqoxssQGnh85BzCj/u3WqBpE2vjvyyvyI5k\", #\n \"X6zk7S0ljKtt2jny2+00VsBerQJBAJGC1Mg5Oydo5NwD6BiROrPxGo2bpTbu/fhrT8ebHkTz2epl\", #\n \"U9VQQSQzY1oZMVX8i1m5WUTLPz2yLJIBQVdXqhMCQBGoiuSoSjafUhV7i1cEGpb88h5NBYZzWXGZ\", #\n \"37sJ5QsW+sJyoNde3xH8vdXhzU7eT82D6X/scw9RZz+/6rCJ4p0=\", #\n \"-----END RSA PRIVATE KEY-----\" #\n ],\n [\n '[\"-----BEGIN RSA PRIVATE KEY-----\",', #\n '\"Proc-Type: 4,ENCRYPTED\",', #\n '\"DEK-Info: AES-256-CBC,2AA219GG746F88F6DDA0D852A0FD3211\",', #\n '\"MIICXAIBAAKBgQCqGKukO1De7zhZj6+H0qtjTkVxwTCpvKe4eCZ0FPqri0cb2JZfXJ/DgYSF6vUp\",', #\n '\"wmJG8wVQZKjeGcjDOL5UlsuusFncCzWBQ7RKNUSesmQRMSGkVb1/3j+skZ6UtW+5u09lHNsj6tQ5\",', #\n '\"1s1SPrCBkedbNf0Tp0GbMJDyR4e9T04ZZwIDAQABAoGAFijko56+qGyN8M0RVyaRAXz++xTqHBLh\",', #\n '\"3tx4VgMtrQ+WEgCjhoTwo23KMBAuJGSYnRmoBZM3lMfTKevIkAidPExvYCdm5dYq3XToLkkLv5L2\",', #\n '\"pIIVOFMDG+KESnAFV7l2c+cnzRMW0+b6f8mR1CJzZuxVLL6Q02fvLi55/mbSYxECQQDeAw6fiIQX\",', #\n '\"GukBI4eMZZt4nscy2o12KyYner3VpoeE+Np2q+Z3pvAMd/aNzQ/W9WaI+NRfcxUJrmfPwIGm63il\",', #\n '\"AkEAxCL5HQb2bQr4ByorcMWm/hEP2MZzROV73yF41hPsRC9m66KrheO9HPTJuo3/9s5p+sqGxOlF\",', #\n '\"L0NDt4SkosjgGwJAFklyR1uZ/wPJjj611cdBcztlPdqoxssQGnh85BzCj/u3WqBpE2vjvyyvyI5k\",', #\n '\"X6zk7S0ljKtt2jny2+00VsBerQJBAJGC1Mg5Oydo5NwD6BiROrPxGo2bpTbu/fhrT8ebHkTz2epl\",', #\n '\"U9VQQSQzY1oZMVX8i1m5WUTLPz2yLJIBQVdXqhMCQBGoiuSoSjafUhV7i1cEGpb88h5NBYZzWXGZ\",', #\n '\"37sJ5QsW+sJyoNde3xH8vdXhzU7eT82D6X/scw9RZz+/6rCJ4p0=\",', #\n '\"-----END RSA PRIVATE KEY-----\"]' #\n ]\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"PEM Private Key\"\n\n\nclass TestEmptyPemKey:\n\n @pytest.fixture(params=[\n [\"-----BEGIN RSA PRIVATE KEY-----\", \"-----END RSA PRIVATE KEY-----\"],\n [\n \"-----BEGIN RSA PRIVATE KEY-----\", #\n \"Proc-Type: 4,ENCRYPTED\", #\n \"DEK-Info: AES-256-CBC,2AA219GG746F88F6DDA0D852A0FD3211\", #\n \"-----END RSA PRIVATE KEY-----\" #\n ],\n [\"-----BEGIN RSA PRIVATE KEY-----\", \"...\", \"-----END RSA PRIVATE KEY-----\"],\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"PEM Private Key\"\n\n def test_scan_no_division_by_zero_exception_n(self, file_path: pytest.fixture, lines: pytest.fixture,\n scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines, file_path=file_path)\n scan_result = scanner.scan(provider)\n assert len(scan_result) == 0\n" }, { "path": "tests/rules/test_picatic_key.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestPicaticKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"sk_live_gireogicracklegireogicrackle1231\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Picatic API Key\"\n" }, { "path": "tests/rules/test_pypi_api_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestPyPiApiToken(BaseTestRule):\n\n @pytest.fixture(params=[\n [\n \"pypi-AgEIcHlwaS5vcmc\" #\n \"CJGE3ZjdlNzVmLTRhOGEtNGY1MC1iMzEwLWQzZTQ1NmJiYzMzMQ\" #\n \"ACJXsicGVybWlzc2lvbnMiOiAidXNlciIsICJ2ZXJzaW9uIjogM\" #\n \"X0AAAYgdUBLuCnfvl7n3ZIgLjCvIDuk9GQxDbw4PHxRUAwPvIk\" #\n ],\n [\n \"pypi-AgENdGVzdC5weXB\" #\n \"CJDc5ZThjYzc4LWViY2YtNGFiZS1iOTNiLTQ3ZWVjOGFmYjIxNQ\" #\n \"ACJXsicGVybWlzc2lvbnMiOiAidXNlciIsICJ2ZXJzaW9uIjogM\" #\n \"X0AAAYgNJxF-my_lC6DUayAYu3KhiASbVvQA8FLI7wo-OkXoLs\" #\n ]\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"PyPi API Token\"\n" }, { "path": "tests/rules/test_rule.py", "content": "from copy import deepcopy\nfrom typing import Any\n\nimport pytest\n\nfrom credsweeper.common.constants import Severity, RuleType\nfrom credsweeper.config.config import Config\nfrom credsweeper.filters.group import GeneralPattern\nfrom credsweeper.rules.rule import Rule\n\n\nclass TestRuleConfigParsing:\n\n @pytest.fixture(params=[\n # Check proper config\n {\n \"name\": \"Twilio API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"values\": [\"(?PSK[0-9a-fA-F]{32})\"],\n \"filter_type\": GeneralPattern.__name__,\n \"min_line_len\": 32,\n \"use_ml\": False,\n \"target\": [\"code\", \"doc\"],\n },\n # Check proper config with no filters\n {\n \"name\": \"Twilio API Key\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"values\": [\"(?PSK[0-9a-fA-F]{32})\"],\n \"filter_type\": [],\n \"min_line_len\": 32,\n \"use_ml\": False,\n \"target\": [\"code\", \"doc\"],\n },\n ])\n def rule_config(self, request: str) -> Any:\n return deepcopy(request.param)\n\n def test_create_from_config_p(self, config: Config, rule_config: pytest.fixture) -> None:\n rule = Rule(config, rule_config)\n assert rule.rule_type == RuleType.PATTERN\n assert rule.patterns[0].pattern == \"(?PSK[0-9a-fA-F]{32})\"\n assert rule.rule_name == \"Twilio API Key\"\n assert rule.severity == Severity.HIGH\n\n @pytest.mark.parametrize(\"field, error\", [[\"severity\", \"none\"], [\"type\", \"none\"], [\"filter_type\", \"none\"]])\n def test_create_from_malformed_config_n(self, config: Config, rule_config: pytest.fixture, field: str,\n error: str) -> None:\n rule_config[field] = error\n with pytest.raises(ValueError, match=r\"Malformed .*\"):\n Rule(config, rule_config)\n\n def test_create_from_missing_fields_n(self, config: Config) -> None:\n with pytest.raises(ValueError, match=r\"Malformed rule config file. Contain rule with missing fields:.*\"):\n Rule(config, {})\n" }, { "path": "tests/rules/test_salt.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestSalt(BaseTestRule):\n\n @pytest.fixture(params=[[\"salt_data = '^S4lt$'\"], [\"salt = '1L1SziaanR3sdPz51cHA'\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture(params=[\"\", \"keyword='hamming'\"])\n def empty_line(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Salt\"\n" }, { "path": "tests/rules/test_secret.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestCommentRule, BaseTestNoQuotesRule, BaseTestRule\n\n\nclass TestSecret(BaseTestRule):\n\n @pytest.fixture(params=[[\"secret = \\\"cackle!\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Secret\"\n\n\nclass TestSecretNoQuotes(BaseTestNoQuotesRule):\n\n @pytest.fixture(params=[[\"secret = cackle!\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Secret\"\n\n\nclass TestSecretComment(BaseTestCommentRule):\n\n @pytest.fixture(params=[[\"# secret = cackle!\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Secret\"\n" }, { "path": "tests/rules/test_sendgrid_api_key_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestSendGridApiKey(BaseTestRule):\n\n @pytest.fixture(params=[[\"SG.gireogigireogigi.gireogigireogigi\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"SendGrid API Key\"\n" }, { "path": "tests/rules/test_shopify_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestShopifyToken(BaseTestRule):\n\n @pytest.fixture(params=[[\"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\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Shopify Token\"\n" }, { "path": "tests/rules/test_slack_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestSlackToken(BaseTestRule):\n\n @pytest.fixture(params=[[\"xoxa-FLYLIKEAGIREOGI-9d8cfc0f59\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Slack Token\"\n" }, { "path": "tests/rules/test_slack_webhook.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestSlackToken(BaseTestRule):\n\n @pytest.fixture(params=[[\"https://hooks.slack.com/services/TGIREOGIT/BEEFLYING/Slack1webhook2teststring\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Slack Webhook\"\n" }, { "path": "tests/rules/test_square_access_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestSquareAccessToken(BaseTestRule):\n\n @pytest.fixture(params=[[\"EAAAEEPtuW9FnP_CuCV-GIREOGIGIREOGIGIREOGIGIREOGIGIREOGIGIREOGIGI\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Square Access Token\"\n" }, { "path": "tests/rules/test_telegram_bot_api_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestTelegramBotApiToken(BaseTestRule):\n\n @pytest.fixture(params=[\n [\"4603348066:AAFMepdNauS475gWKEpuDt9NpytDegUz4-o\"], #\n [\"3039734276:AAHp--rsrIsieHSGWMPMQ8xAzztmgCp009c\"]\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Telegram Bot API Token\"\n" }, { "path": "tests/rules/test_token.py", "content": "from typing import List\n\nimport pytest\n\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom .common import BaseTestCommentRule, BaseTestNoQuotesRule, BaseTestRule\n\n\nclass TestToken(BaseTestRule):\n\n @pytest.fixture(params=[[\"gi_reo_gi_token = \\\"@@cacklecackle_gi_reo_gi@@\\\"\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Token\"\n\n\nclass TestTokenNoQuotes(BaseTestNoQuotesRule):\n\n @pytest.fixture(params=[[\"gi_reo_gi_token = @@cacklecackle_gi_reo_gi@@\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Token\"\n\n\nclass TestTokenComment(BaseTestCommentRule):\n\n @pytest.fixture(params=[[\"# gi_reo_gi_token = @@cacklecackle_gi_reo_gi@@\"]])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Token\"\n\n\nclass TestTokenWhitespaceBeforeQuote:\n\n @pytest.fixture\n def lines(self) -> List[str]:\n lines = \" \\\"gi_reo_gi_token\\\": \\\"@@cacklecackle_gi_reo_gi@@\\\"\".splitlines()\n return lines\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"Token\"\n\n def test_scan_whitespace_before_quote_p(self, file_path: pytest.fixture, lines: pytest.fixture,\n scanner: pytest.fixture) -> None:\n provider = StringContentProvider(lines)\n assert len(scanner.scan(provider)) == 1\n" }, { "path": "tests/rules/test_url_credentials.py", "content": "from typing import List\n\nimport pytest\n\nfrom .common import BaseTestRule\n\n\nclass TestUrlCredentials(BaseTestRule):\n\n @pytest.fixture(params=[\n [\"https://user:pass12AB@your.domain.com/path\"], #\n [\"url='https://user:pass12AB@your.domain.com/path'\"]\n ])\n def lines(self, request) -> List[str]:\n return request.param\n\n @pytest.fixture\n def rule_name(self) -> str:\n return \"URL Credentials\"\n" }, { "path": "tests/scanner/__init__.py", "content": "" }, { "path": "tests/scanner/scan_type/__init__.py", "content": "" }, { "path": "tests/scanner/scan_type/test_multipattern.py", "content": "import unittest\nfrom unittest.mock import MagicMock\n\nfrom credsweeper.common.constants import MAX_LINE_LENGTH, CHUNK_STEP_SIZE\nfrom credsweeper.config.config import Config\nfrom credsweeper.file_handler.analysis_target import AnalysisTarget\nfrom credsweeper.rules.rule import Rule\nfrom credsweeper.scanner.scan_type.multi_pattern import MultiPattern\nfrom tests import AZ_STRING\nfrom tests.filters.conftest import DUMMY_DESCRIPTOR\n\n\nclass TestMultiPattern(unittest.TestCase):\n\n def setUp(self) -> None:\n self.maxDiff = None\n self.config = MagicMock(spec=Config)\n self.config.exclude_lines = []\n self.config.exclude_values = []\n self.config.use_filters = True\n self.rule = Rule(\n self.config, {\n \"name\": \"MULTI_PATTERN_RULE\",\n \"severity\": \"info\",\n \"confidence\": \"moderate\",\n \"type\": \"multi\",\n \"values\": [\"(?Pa)\", \"(?Pb)\"],\n \"filter_type\": [],\n \"min_line_len\": 0,\n \"target\": [\"code\"],\n })\n\n def test_oversize_line_n(self) -> None:\n long_line_a: str = 'x' * CHUNK_STEP_SIZE + ' a ' + 'x' * CHUNK_STEP_SIZE\n long_line_b: str = 'x' * CHUNK_STEP_SIZE + ' b ' + 'x' * CHUNK_STEP_SIZE\n self.assertEqual(2 * CHUNK_STEP_SIZE + 3, len(long_line_a))\n target = AnalysisTarget(0, [long_line_a, long_line_b], [1, 2], DUMMY_DESCRIPTOR)\n result = MultiPattern.run(self.config, self.rule, target)\n self.assertEqual(1, len(result))\n\n def test_oversize_line_p(self) -> None:\n long_line: str = 'x' * MAX_LINE_LENGTH\n self.assertEqual(MAX_LINE_LENGTH, len(long_line))\n target = AnalysisTarget(0, [long_line + ' a', long_line + ' b'], [1, 2], DUMMY_DESCRIPTOR)\n result = MultiPattern.run(self.config, self.rule, target)\n self.assertEqual(1, len(result))\n\n def test_get_line_positions_n(self):\n target = AnalysisTarget(0, [AZ_STRING], [1], DUMMY_DESCRIPTOR)\n self.assertListEqual([0], MultiPattern.get_line_positions(0, target))\n target = AnalysisTarget(-1, [AZ_STRING], [1], DUMMY_DESCRIPTOR)\n self.assertListEqual([], MultiPattern.get_line_positions(-1, target))\n\n def test_get_line_positions_p(self):\n lines = [str(1 + x) for x in range(42)]\n line_nums = [1 + x for x in range(42)]\n target = AnalysisTarget(0, lines, line_nums, DUMMY_DESCRIPTOR)\n self.assertListEqual(list(range(11)), MultiPattern.get_line_positions(0, target))\n self.assertListEqual([41 - x for x in range(11)], MultiPattern.get_line_positions(41, target))\n self.assertListEqual([21, 22, 20, 23, 19, 24, 18, 25, 17, 26, 16, 27, 15, 28, 14, 29, 13, 30, 12, 31, 11],\n MultiPattern.get_line_positions(21, target))\n lines[20] = '{'\n target = AnalysisTarget(0, lines, line_nums, DUMMY_DESCRIPTOR)\n self.assertListEqual([21, 22, 23, 20, 24, 19, 25, 18, 26, 17, 27, 16, 28, 15, 29, 14, 30, 13, 31, 12, 11],\n MultiPattern.get_line_positions(21, target))\n lines[22] = '}'\n target = AnalysisTarget(0, lines, line_nums, DUMMY_DESCRIPTOR)\n self.assertListEqual([21, 22, 20, 23, 19, 24, 18, 25, 17, 26, 16, 27, 15, 28, 14, 29, 13, 30, 12, 31, 11],\n MultiPattern.get_line_positions(21, target))\n lines[16] = '{' * 10000\n target = AnalysisTarget(0, lines, line_nums, DUMMY_DESCRIPTOR)\n self.assertListEqual([21, 22, 20, 23, 19, 24, 18, 25, 17, 26, 27, 28, 29, 30, 31, 16, 15, 14, 13, 12, 11],\n MultiPattern.get_line_positions(21, target))\n" }, { "path": "tests/scanner/scan_type/test_pem_key_pattern.py", "content": "import unittest\n\nfrom credsweeper.utils.pem_key_detector import PemKeyDetector\n\n\nclass TestPemKeyPattern(unittest.TestCase):\n\n def test_remove_leading_config_lines_p(self):\n lines = [\"Proc-Type: 4,ENCRYPTED\", \"DEK-Info: DES-EDE3-CBC,BA2D3F11273F6I7A\", \"\"]\n for line in lines:\n self.assertTrue(PemKeyDetector.is_leading_config_line(line), line)\n\n def test_remove_leading_config_lines_n(self):\n lines = [\n \"MIICXAIBAAKBgQCqGKukO1De7zhZj6+H0qtjTkVxwTCpvKe4eCZ0FPqri0cb2JZfXJ/DgYSF6vUp\",\n \"wmJG8wVQZKjeGcjDOL5UlsuusFncCzWBQ7RKNUSesmQRMSGkVb1/3j+skZ6UtW+5u09lHNsj6tQ5\",\n \"1s1SPrCBkedbNf0Tp0GbMJDyR4e9T04ZZwIDAQABAoGAFijko56+qGyN8M0RVyaRAXz++xTqHBLh\"\n ]\n for line in lines:\n self.assertFalse(PemKeyDetector.is_leading_config_line(line), line)\n\n def test_sanitize_line_p(self):\n lines = [\n \" MIIEvgIBADANBgkqhkiG9w0BAQEFAASCBKgwggSkAgEAAoIBAQDCqx5mEeaMNCqr\",\n \" \\\" hNtDzrYypSREYpBHTUKoa+y0rRy74nLA1Z4+nKVOTdXNuMGLp9KxHqwIlDk8QK5n\\n' +\",\n \"# //tDzrYypSREYpBHTUKoa+y0rRy74nLA1Z4+nKVOTdXNuMGLp9KxHqwIlDk8QK5n\"\n ]\n should_be = [\n \"MIIEvgIBADANBgkqhkiG9w0BAQEFAASCBKgwggSkAgEAAoIBAQDCqx5mEeaMNCqr\",\n \"hNtDzrYypSREYpBHTUKoa+y0rRy74nLA1Z4+nKVOTdXNuMGLp9KxHqwIlDk8QK5n\",\n \"//tDzrYypSREYpBHTUKoa+y0rRy74nLA1Z4+nKVOTdXNuMGLp9KxHqwIlDk8QK5n\"\n ]\n for expect_line, line in zip(should_be, lines):\n self.assertEqual(expect_line, PemKeyDetector.sanitize_line(line), line)\n\n def test_sanitize_line_n(self):\n \"\"\"Check that valid PEM lines will not be changed\"\"\"\n lines = [\n \"MIIEvgIBADANBgkqhkiG9w0BAQEFAASCBKgwggSkAgEAAoIBAQDCqx5mEeaMNCqr\",\n \"hNtDzrYypSREYpBHTUKoa+y0rRy74nLA1Z4+nKVOTdXNuMGLp9KxHqwIlDk8QK5n\"\n ]\n for line in lines:\n self.assertEqual(line, PemKeyDetector.sanitize_line(line), line)\n" }, { "path": "tests/test_app.py", "content": "import binascii\nimport datetime\nimport hashlib\nimport json\nimport os\nimport re\nimport shutil\nimport subprocess\nimport sys\nimport tempfile\nimport time\nfrom typing import AnyStr, Tuple\nfrom unittest import TestCase\n\nimport deepdiff\nimport numpy as np\nimport pandas as pd\nimport pytest\nimport yaml\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.scanner.scanner import RULES_PATH\nfrom credsweeper.utils.util import Util\nfrom tests import AZ_STRING, SAMPLES_POST_CRED_COUNT, SAMPLES_IN_DEEP_3, SAMPLES_PATH, \\\n TESTS_PATH, SAMPLES_FILTERED_COUNT, SAMPLES_IN_DOC, ZERO_ML_THRESHOLD, SAMPLE_ZIP\n\nCHECK_WORKFLOW_PATH = TESTS_PATH.parent / \".github\" / \"workflows\" / \"check.yml\"\n\n\nclass TestApp(TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n @staticmethod\n def _m_credsweeper(args) -> Tuple[str, str]:\n with subprocess.Popen(\n args=[sys.executable, \"-m\", \"credsweeper\", *args], #\n cwd=APP_PATH.parent, #\n stdout=subprocess.PIPE, #\n stderr=subprocess.PIPE) as proc:\n _stdout, _stderr = proc.communicate()\n\n def transform(x: AnyStr) -> str:\n if isinstance(x, bytes):\n return x.decode(errors='replace')\n elif isinstance(x, str):\n return x\n else:\n raise ValueError(f\"Unknown type: {type(x)}\")\n\n return transform(_stdout), transform(_stderr)\n\n def test_it_works_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"uuid\")\n _stdout, _stderr = self._m_credsweeper([\"--path\", target_path, \"--log\", \"silence\"])\n output = \" \".join(_stdout.split()[:-1])\n\n expected = f\"\"\"\n rule: UUID\n | severity: info\n | confidence: strong\n | ml_probability: None\n | line_data_list:\n [path: {target_path}\n | line_num: 1\n | value: 'bace4d19-fa7e-beef-cafe-9129474bcd81'\n | line: 'bace4d19-fa7e-beef-cafe-9129474bcd81 # tp']\n Detected Credentials: 1\n Time Elapsed:\n \"\"\"\n expected = \" \".join(expected.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_huge_diff_p(self) -> None:\n # verifies issue when huge patch is parsed very slow\n # https://github.com/Samsung/CredSweeper/issues/242\n text = \"\"\"diff --git a/huge.file b/huge.file\n index 0000000..1111111 100644\n --- a/huge.file\n +++ a/huge.file\n @@ -3,13 +3,1000007 @@\n 00000000\n 11111111\n 22222222\n -33333333\n -44444444\n +55555555\n +66666666\n \"\"\"\n for n in range(0, 1000000):\n text += \"+\" + hex(n) + \"\\n\"\n with tempfile.TemporaryDirectory() as tmp_dir:\n target_path = os.path.join(tmp_dir, f\"{__name__}.diff\")\n start_time = datetime.datetime.now()\n _stdout, _stderr = self._m_credsweeper([\"--path\", target_path, \"--ml_threshold\", \"0\", \"--log\", \"silence\"])\n self.assertGreater(datetime.timedelta(seconds=100), datetime.datetime.now() - start_time)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_it_works_with_patch_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"uuid-update.patch\")\n _stdout, _stderr = self._m_credsweeper([\"--diff\", target_path, \"--log\", \"silence\"])\n output = \" \".join(_stdout.split()[:-1])\n\n expected = \"\"\"\n rule: UUID\n | severity: info\n | confidence: strong\n | ml_probability: None\n | line_data_list:\n [path: uuid\n | line_num: 1\n | value: 'bace4d19-fa7e-dead-beef-9129474bcd81'\n | line: 'bace4d19-fa7e-dead-beef-9129474bcd81']\n rule: UUID\n | severity: info\n | confidence: strong\n | ml_probability: None\n | line_data_list:\n [path: uuid\n | line_num: 1\n | value: 'bace4d19-fa7e-beef-cafe-9129474bcd81'\n | line: 'bace4d19-fa7e-beef-cafe-9129474bcd81']\n Added File Credentials: 1\n Deleted File Credentials: 1\n Time Elapsed:\n \"\"\"\n expected = \" \".join(expected.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_it_works_with_multiline_in_patch_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"multiline.patch\")\n _stdout, _stderr = self._m_credsweeper([\"--diff_path\", target_path, \"--log\", \"silence\"])\n output = \" \".join(_stdout.split()[:-1])\n\n expected = \"\"\"\n rule: AWS Client ID\n | severity: high\n | confidence: moderate\n | ml_probability: None\n | line_data_list:\n [path: creds.py\n | line_num: 4\n | value: 'AKIAQWADE5R42RDZ4JEM'\n | line: ' clid = \"AKIAQWADE5R42RDZ4JEM\"']\n rule: AWS Multi\n | severity: high\n | confidence: moderate\n | ml_probability: None\n | line_data_list:\n [path: creds.py\n | line_num: 4\n | value: 'AKIAQWADE5R42RDZ4JEM'\n | line: ' clid = \"AKIAQWADE5R42RDZ4JEM\"',\n path: creds.py\n | line_num: 5\n | value: 'V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ'\n | line: ' token = \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\"']\n rule: Token\n | severity: high\n | confidence: moderate\n | ml_probability: 0.9998588562011719\n | line_data_list:\n [path: creds.py\n | line_num: 5\n | value: 'V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ'\n | line: ' token = \"V84C7sDU001tFFodKU95USNy97TkqXymnvsFmYhQ\"']\n Added File Credentials: 3\n Deleted File Credentials: 0\n Time Elapsed:\n \"\"\"\n expected = \" \".join(expected.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_it_works_with_patch_color_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"uuid-update.patch\")\n _stdout, _stderr = self._m_credsweeper(\n [\"--diff_path\", target_path, \"--log\", \"silence\", \"--color\", \"--no-stdout\"])\n output = \" \".join(_stdout.split()[:-1])\n expected = \"\"\"\n \\x1b[1mUUID uuid:added:1\\x1b[0m\n \\x1b[93mbace4d19-fa7e-dead-beef-9129474bcd81\\x1b[0m\n \\x1b[1mUUID uuid:deleted:1\\x1b[0m\n \\x1b[93mbace4d19-fa7e-beef-cafe-9129474bcd81\\x1b[0m\n Added File Credentials: 1 Deleted File Credentials: 1 Time Elapsed:\n \"\"\"\n expected = \" \".join(expected.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_it_works_n(self) -> None:\n _stdout, _stderr = self._m_credsweeper([])\n\n # Merge more than two whitespaces into one because _stdout and _stderr are changed based on the terminal size\n output = \" \".join(_stderr.split())\n\n expected = \"usage: python -m credsweeper [-h]\" \\\n \" (--path PATH [PATH ...]\" \\\n \" | --diff_path PATH [PATH ...]\" \\\n \" | --export_config [PATH]\" \\\n \" | --export_log_config [PATH]\" \\\n \" | --git PATH\" \\\n \")\" \\\n \" [--ref REF]\" \\\n \" [--rules PATH]\" \\\n \" [--severity SEVERITY]\" \\\n \" [--config PATH]\" \\\n \" [--log_config PATH]\" \\\n \" [--denylist PATH]\" \\\n \" [--find-by-ext]\" \\\n \" [--pedantic | --no-pedantic]\" \\\n \" [--depth POSITIVE_INT]\" \\\n \" [--no-filters]\" \\\n \" [--doc]\" \\\n \" [--ml_threshold THRESHOLD_OR_FLOAT_OR_ZERO]\" \\\n \" [--ml_batch_size POSITIVE_INT]\" \\\n \" [--ml_config PATH]\" \\\n \" [--ml_model PATH]\" \\\n \" [--ml_providers STR] \" \\\n \" [--jobs POSITIVE_INT]\" \\\n \" [--thrifty | --no-thrifty]\" \\\n \" [--skip_ignored]\" \\\n \" [--error | --no-error]\" \\\n \" [--save-json [PATH]]\" \\\n \" [--save-xlsx [PATH]]\" \\\n \" [--stdout | --no-stdout]\" \\\n \" [--color | --no-color]\" \\\n \" [--hashed | --no-hashed]\" \\\n \" [--subtext | --no-subtext]\" \\\n \" [--sort | --no-sort]\" \\\n \" [--log LOG_LEVEL]\" \\\n \" [--size_limit SIZE_LIMIT]\" \\\n \" [--banner] \" \\\n \" [--version] \" \\\n \"python -m credsweeper: error: one of the arguments\" \\\n \" --path\" \\\n \" --diff_path\" \\\n \" --export_config\" \\\n \" --export_log_config\" \\\n \" --git\" \\\n \" is required \"\n expected = \" \".join(expected.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_log_p(self) -> None:\n _stdout, _stderr = self._m_credsweeper(\n [\"--log\", \"Debug\", \"--depth\", \"7\", \"--ml_threshold\", \"0\", \"--path\",\n str(SAMPLE_ZIP), \"not_existed_path\"])\n self.assertEqual(0, len(_stderr))\n\n self.assertIn(\"DEBUG\", _stdout)\n self.assertIn(\"INFO\", _stdout)\n self.assertIn(\"WARNING\", _stdout)\n self.assertNotIn(\"ERROR\", _stdout)\n self.assertNotIn(\"CRITICAL\", _stdout)\n\n for line in _stdout.splitlines():\n if 5 <= len(line) and \"rule:\" == line[0:5]:\n self.assertRegex(line, r\"rule: \\.*\")\n elif 21 <= len(line) and \"Detected Credentials:\" == line[0:21]:\n self.assertRegex(line, r\"Detected Credentials: \\d+\")\n elif 13 <= len(line) and \"Time Elapsed:\" == line[0:13]:\n self.assertRegex(line, r\"Time Elapsed: \\d+\\.\\d+\")\n else:\n self.assertRegex(\n line,\n r\"\\d{4}-\\d\\d-\\d\\d \\d\\d:\\d\\d:\\d\\d,\\d+ \\| (DEBUG|INFO|WARNING|ERROR) \\| \\w+:\\d+ \\| .*\",\n )\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_log_n(self) -> None:\n _stdout, _stderr = self._m_credsweeper([\"--log\", \"CriTicaL\", \"--rule\", \"NOT_EXISTED_PATH\", \"--path\", \".\"])\n self.assertEqual(0, len(_stderr))\n\n self.assertNotIn(\"DEBUG\", _stdout)\n self.assertNotIn(\"INFO\", _stdout)\n self.assertNotIn(\"WARNING\", _stdout)\n self.assertNotIn(\"ERROR\", _stdout)\n self.assertIn(\"CRITICAL\", _stdout)\n\n self.assertTrue(\n any(\n re.match(r\"\\d{4}-\\d\\d-\\d\\d \\d\\d:\\d\\d:\\d\\d,\\d+ \\| (CRITICAL) \\| \\w+:\\d+ \\| .*\", line)\n for line in _stdout.splitlines()), _stdout)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n # todo: fix when python 3.10 support ends\n @pytest.mark.skipif(10 < sys.version_info.minor, reason=\"argparse default was changed in 3.11\")\n def test_help_p(self) -> None:\n _stdout, _stderr = self._m_credsweeper([\"--help\"])\n output = \" \".join(_stdout.split())\n help_path = os.path.join(TESTS_PATH, \"..\", \"docs\", \"source\", \"guide.rst\")\n with open(help_path, \"r\") as f:\n text = \"\"\n started = False\n for line in f.read().splitlines():\n if \".. note::\" == line:\n break\n if \".. code-block:: text\" == line:\n started = True\n continue\n if started:\n text = ' '.join([text, line])\n expected = \" \".join(text.split())\n self.assertEqual(expected, output)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_version_p(self) -> None:\n _stdout, _stderr = self._m_credsweeper([\"--version\"])\n # Merge more than two whitespaces into one because _stdout and _stderr are changed based on the terminal size\n output = \" \".join(_stdout.split())\n self.assertRegex(output, r\"CredSweeper \\d+\\.\\d+\\.\\d+\")\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @pytest.mark.skipif(not CHECK_WORKFLOW_PATH.exists(), reason=\"Only for GitHub repo\")\n def test_banner_p(self) -> None:\n _stdout, _stderr = self._m_credsweeper([\"--banner\"])\n output = \" \".join(_stdout.split())\n banner_regex = re.compile(r\"^CredSweeper \\d+\\.\\d+\\.\\d+ crc32:[0-9a-f]{8}$\")\n banner_text = ''\n self.assertRegex(output, banner_regex, _stderr or _stdout)\n # check and fix the hash in .github action\n with open(CHECK_WORKFLOW_PATH, \"r\") as f:\n check_wf_lines = f.readlines()\n new_lines = []\n for line in check_wf_lines:\n env_banner_start = line.find('CREDSWEEPER_BANNER: \"CredSweeper')\n if 0 < env_banner_start:\n banner_text = line[env_banner_start + 21:-2]\n new_line = f'{line[:env_banner_start]}CREDSWEEPER_BANNER: \"{output}\"\\n'\n new_lines.append(new_line)\n else:\n new_lines.append(line)\n if output != banner_text:\n with open(CHECK_WORKFLOW_PATH, \"w\") as f:\n f.write(''.join(new_lines))\n self.fail(f\"The banner check was updated with '{output}'. Rerun the test.\")\n elif not banner_regex.fullmatch(banner_text) and not banner_text:\n self.fail(f\"Check output: '{_stdout}' or '{_stderr}'\")\n else:\n self.assertRegex(banner_text, banner_regex, _stderr or _stdout)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_patch_save_json_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"password.patch\")\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper(\n [\"--diff_path\", target_path, \"--no-stdout\", \"--save-json\", json_filename, \"--log\", \"silence\"])\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.added.json\")))\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.deleted.json\")))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_patch_save_json_n(self) -> None:\n start_time = time.time()\n target_path = str(SAMPLES_PATH / \"password.patch\")\n _stdout, _stderr = self._m_credsweeper([\"--diff_path\", target_path, \"--log\", \"silence\"])\n for root, dirs, files in os.walk(APP_PATH.parent):\n self.assertIn(\"credsweeper\", dirs)\n for file in files:\n # check whether the report was created AFTER test launch to avoid failures during development\n self.assertFalse(file.endswith(\".json\") and os.stat(os.path.join(root, file)).st_mtime > start_time)\n dirs.clear()\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_export_config_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\"--export_config\", json_filename, \"--log\", \"silence\"])\n self.assertTrue(os.path.exists(json_filename))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_import_config_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n custom_config = os.path.join(tmp_dir, f\"{__name__}.json\")\n shutil.copyfile(APP_PATH / \"secret\" / \"config.json\", custom_config)\n args = [\"--config\", custom_config, \"--path\", str(APP_PATH), \"--find-by-ext\", \"--log\", \"CRITICAL\"]\n _stdout, _stderr = self._m_credsweeper(args)\n self.assertEqual(\"\", _stderr)\n self.assertNotIn(\"CRITICAL\", _stdout)\n self.assertIn(\"Time Elapsed:\", _stdout)\n self.assertIn(\"Detected Credentials: 0\", _stdout)\n self.assertEqual(2, len(_stdout.splitlines()))\n # add .py to find by extension\n modified_config = Util.json_load(custom_config)\n self.assertIn(\"find_by_ext_list\", modified_config.keys())\n self.assertIsInstance(modified_config[\"find_by_ext_list\"], list)\n modified_config[\"find_by_ext_list\"].append(\".py\")\n Util.json_dump(modified_config, custom_config)\n _stdout, _stderr = self._m_credsweeper(args)\n self.assertEqual(\"\", _stderr)\n self.assertNotIn(\"CRITICAL\", _stdout)\n self.assertIn(\"Time Elapsed:\", _stdout)\n self.assertNotIn(\"Detected Credentials: 0\", _stdout)\n self.assertLess(5, len(_stdout.splitlines()))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_import_config_n(self) -> None:\n # not existed file\n _stdout, _stderr = self._m_credsweeper(\n [\"--config\", \"not_existed_file\", \"--path\",\n str(APP_PATH), \"--log\", \"CRITICAL\"])\n self.assertEqual(0, len(_stderr))\n self.assertIn(\"CRITICAL\", _stdout)\n # wrong config\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n with open(json_filename, \"w\") as f:\n f.write('{}')\n _stdout, _stderr = self._m_credsweeper(\n [\"--config\", json_filename, \"--path\",\n str(APP_PATH), \"--log\", \"CRITICAL\"])\n self.assertEqual(0, len(_stderr))\n self.assertIn(\"CRITICAL\", _stdout)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_export_log_config_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_filename = os.path.join(tmp_dir, f\"{__name__}.yaml\")\n _stdout, _stderr = self._m_credsweeper([\"--export_log_config\", test_filename, \"--log\", \"silence\"])\n self.assertTrue(os.path.exists(test_filename))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_import_log_config_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_filename = os.path.join(tmp_dir, f\"{__name__}.yaml\")\n _o, _e = self._m_credsweeper([\"--export_log_config\", test_filename, \"--log\", \"silence\"])\n self.assertFalse(os.path.exists(os.path.join(tmp_dir, \"log\")))\n with open(test_filename, 'r') as f:\n text = f.read().replace(\"filename: ./log\", f\"filename: {tmp_dir}/log\")\n with open(test_filename, 'w') as f:\n f.write(text)\n _stdout, _stderr = self._m_credsweeper([\"--log_config\", test_filename, \"--log\", \"silence\", \"--path\", \"X3\"])\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, \"log\")))\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, \"log\", \"error.log\")))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_find_by_ext_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n # .deR will be found also!\n for f in [\".pem\", \".cer\", \".csr\", \".deR\"]:\n file_path = os.path.join(tmp_dir, f\"dummy{f}\")\n self.assertFalse(os.path.exists(file_path))\n open(file_path, \"w\").write(AZ_STRING)\n\n # not of all will be found due they are empty\n for f in [\".jks\", \".KeY\"]:\n file_path = os.path.join(tmp_dir, f\"dummy{f}\")\n self.assertFalse(os.path.exists(file_path))\n open(file_path, \"w\").close()\n\n # the directory hides all files\n ignored_dir = os.path.join(tmp_dir, \"target\")\n os.mkdir(ignored_dir)\n for f in [\".pfx\", \".p12\"]:\n file_path = os.path.join(ignored_dir, f\"dummy{f}\")\n self.assertFalse(os.path.exists(file_path))\n open(file_path, \"w\").write(AZ_STRING)\n\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper(\n [\"--path\", tmp_dir, \"--find-by-ext\", \"--no-stdout\", \"--save-json\", json_filename, \"--log\", \"silence\"])\n self.assertTrue(os.path.exists(json_filename))\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(4, len(report), report)\n for t in report:\n self.assertEqual(0, t[\"line_data_list\"][0][\"line_num\"])\n self.assertIn(str(t[\"line_data_list\"][0][\"path\"][-4:]), [\".pem\", \".cer\", \".csr\", \".deR\"])\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_find_by_ext_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n for f in [\".pem\", \".cer\", \".csr\", \".der\", \".pfx\", \".p12\", \".key\", \".jks\"]:\n file_path = os.path.join(tmp_dir, f\"dummy{f}\")\n self.assertFalse(os.path.exists(file_path))\n open(file_path, \"w\").write(AZ_STRING)\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper(\n [\"--path\", tmp_dir, \"--no-stdout\", \"--save-json\", json_filename, \"--log\", \"silence\"])\n self.assertTrue(os.path.exists(json_filename))\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(0, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_depth_p(self) -> None:\n # check data samples integrity\n checksum = hashlib.md5(b'').digest()\n for root, dirs, files in os.walk(SAMPLES_PATH):\n for file in files:\n with open(os.path.join(root, file), \"rb\") as f:\n cvs_checksum = hashlib.md5(f.read()).digest()\n checksum = bytes(a ^ b for a, b in zip(checksum, cvs_checksum))\n # update the checksum manually and keep line endings in the samples as is (git config core.autocrlf false)\n self.assertEqual(\"31a7141e4dda9e99aaef688fc41c2ac3\", binascii.hexlify(checksum).decode())\n normal_report = []\n sorted_report = []\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n # depth = 3\n _stdout, _stderr = self._m_credsweeper([\n \"--log\", \"silence\", \"--path\",\n str(SAMPLES_PATH), \"--no-stdout\", \"--save-json\", json_filename, \"--depth\", \"3\"\n ])\n self.assertTrue(os.path.exists(json_filename))\n with open(json_filename, \"r\") as json_file:\n normal_report.extend(json.load(json_file))\n self.assertEqual(SAMPLES_IN_DEEP_3, len(normal_report))\n sorted_json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\n \"--log\", \"silence\", \"--path\",\n str(SAMPLES_PATH), \"--sort\", \"--no-stdout\", \"--save-json\", sorted_json_filename, \"--depth\", \"3\"\n ])\n self.assertTrue(os.path.exists(sorted_json_filename))\n with open(sorted_json_filename, \"r\") as json_file:\n sorted_report.extend(json.load(json_file))\n self.assertEqual(SAMPLES_IN_DEEP_3, len(sorted_report))\n self.assertTrue(deepdiff.DeepDiff(sorted_report, normal_report))\n # exclude equal items of dict instead custom __lt__ realization\n for n in range(len(normal_report) - 1, -1, -1):\n for i in sorted_report:\n if i == normal_report[n]:\n del normal_report[n]\n break\n # 0 - means all items were matched\n self.assertEqual(0, len(normal_report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_depth_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n # depth is not set\n _stdout, _stderr = self._m_credsweeper(\n [\"--log\", \"silence\", \"--path\",\n str(SAMPLES_PATH), \"--no-stdout\", \"--save-json\", json_filename])\n self.assertTrue(os.path.exists(json_filename))\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(SAMPLES_POST_CRED_COUNT, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_denylist_p(self) -> None:\n target_path = str(SAMPLES_PATH / \"github_classic_token\")\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n denylist_filename = os.path.join(tmp_dir, \"list.txt\")\n with open(denylist_filename, \"w\") as f:\n f.write('ghp_00000000000000000000000000000004WZ4EQ # classic') # full line\n _stdout, _stderr = self._m_credsweeper([\n \"--path\", target_path, \"--denylist\", denylist_filename, \"--no-stdout\", \"--save-json\", json_filename,\n \"--log\", \"silence\"\n ])\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(0, len(report))\n with open(denylist_filename, \"w\") as f:\n f.write('ghp_00000000000000000000000000000004WZ4EQ') # value only\n _stdout, _stderr = self._m_credsweeper([\n \"--path\", target_path, \"--denylist\", denylist_filename, \"--no-stdout\", \"--save-json\", json_filename,\n \"--log\", \"silence\"\n ])\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(0, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_denylist_n(self) -> None:\n target_path = str(SAMPLES_PATH / \"github_classic_token\")\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n denylist_filename = os.path.join(tmp_dir, \"list.txt\")\n with open(denylist_filename, \"w\") as f:\n f.write('4WZ4EQ # classic') # part of line - will not exclude\n _stdout, _stderr = self._m_credsweeper([\n \"--path\", target_path, \"--denylist\", denylist_filename, \"--no-stdout\", \"--save-json\", json_filename,\n \"--log\", \"silence\"\n ])\n with open(json_filename, \"r\") as json_file:\n report = json.load(json_file)\n self.assertEqual(1, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_rules_ml_p(self) -> None:\n # checks whether all rules have positive test samples with almost the same arguments during benchmark\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\n \"--path\",\n str(SAMPLES_PATH),\n \"--save-json\",\n json_filename,\n ])\n self.assertEqual(0, len(_stderr))\n report = Util.json_load(json_filename)\n report_set = set([i[\"rule\"] for i in report])\n rules = Util.yaml_load(RULES_PATH)\n # test rules integrity\n rules.sort(key=lambda x: x[\"name\"])\n rules_text = yaml.dump_all(rules, sort_keys=True)\n checksum = hashlib.md5(rules_text.encode()).hexdigest()\n # update the expected value manually if some changes\n self.assertEqual(\"c794796c4e2cb69b89f968a674919243\", checksum)\n rules_set = set([i[\"name\"] for i in rules if \"code\" in i[\"target\"]])\n self.assertSetEqual(rules_set, report_set)\n self.assertEqual(SAMPLES_POST_CRED_COUNT, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_rules_ml_n(self) -> None:\n # checks whether all rules have test samples which detected without ML\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\n \"--path\",\n str(SAMPLES_PATH),\n \"--ml_threshold\",\n \"0\",\n \"--save-json\",\n json_filename,\n ])\n self.assertEqual(0, len(_stderr))\n report = Util.json_load(json_filename)\n report_set = set([i[\"rule\"] for i in report])\n rules = Util.yaml_load(RULES_PATH)\n rules_set = set([i[\"name\"] for i in rules if \"code\" in i[\"target\"]])\n self.assertSetEqual(rules_set, report_set)\n self.assertEqual(SAMPLES_FILTERED_COUNT, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_no_filters_p(self) -> None:\n # checks with disabled ML and filtering\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\n \"--path\",\n str(SAMPLES_PATH),\n \"--ml_threshold\",\n \"0\",\n \"--no-filters\",\n \"--save-json\",\n json_filename,\n ])\n self.assertEqual(0, len(_stderr))\n report = Util.json_load(json_filename)\n # the number of reported items should increase\n self.assertLess(SAMPLES_FILTERED_COUNT, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_severity_patch_xlsx_n(self) -> None:\n # uuid is info level - no report\n with tempfile.TemporaryDirectory() as tmp_dir:\n _stdout, _stderr = self._m_credsweeper([ #\n \"--severity\",\n \"low\",\n \"--diff\",\n str(SAMPLES_PATH / \"uuid-update.patch\"),\n \"--save-xlsx\",\n os.path.join(tmp_dir, f\"{__name__}.xlsx\"),\n \"--save-json\",\n os.path.join(tmp_dir, f\"{__name__}.json\"),\n ])\n # reports are created\n self.assertEqual(3, len(os.listdir(tmp_dir)))\n # but empty\n self.assertListEqual([], Util.json_load(os.path.join(tmp_dir, f\"{__name__}.deleted.json\")))\n self.assertListEqual([], Util.json_load(os.path.join(tmp_dir, f\"{__name__}.added.json\")))\n self.assertEqual(0, len(pd.read_excel(os.path.join(tmp_dir, f\"{__name__}.xlsx\"))))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_severity_patch_xlsx_p(self) -> None:\n # info level produces xlsx file with \"added\" and \"deleted\" sheets and two json files\n with tempfile.TemporaryDirectory() as tmp_dir:\n xlsx_filename = os.path.join(tmp_dir, f\"{__name__}.xlsx\")\n _stdout, _stderr = self._m_credsweeper([ #\n \"--severity\",\n \"info\",\n \"--diff\",\n str(SAMPLES_PATH / \"uuid-update.patch\"),\n \"--save-xlsx\",\n xlsx_filename,\n \"--save-json\",\n os.path.join(tmp_dir, f\"{__name__}.json\"),\n ])\n deleted_report_file = os.path.join(tmp_dir, f\"{__name__}.deleted.json\")\n deleted_report = Util.json_load(deleted_report_file)\n self.assertEqual(\"UUID\", deleted_report[0][\"rule\"])\n added_report_file = os.path.join(tmp_dir, f\"{__name__}.added.json\")\n added_report = Util.json_load(added_report_file)\n self.assertEqual(\"UUID\", added_report[0][\"rule\"])\n book = pd.read_excel(xlsx_filename, sheet_name=None, header=None)\n # two sheets should be created\n self.assertSetEqual({\"deleted\", \"added\"}, set(book.keys()))\n # values in xlsx are wrapped to double quotes\n deleted_value = f'\"{deleted_report[0][\"line_data_list\"][0][\"value\"]}\"'\n self.assertTrue(np.isin(deleted_value, book[\"deleted\"].values))\n added_value = f'\"{added_report[0][\"line_data_list\"][0][\"value\"]}\"'\n self.assertTrue(np.isin(added_value, book[\"added\"].values))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_doc_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n _stdout, _stderr = self._m_credsweeper([\n \"--doc\",\n \"--path\",\n str(SAMPLES_PATH),\n \"--no-stdout\",\n \"--ml_threshold\",\n str(ZERO_ML_THRESHOLD),\n \"--save-json\",\n json_filename,\n ])\n report = Util.json_load(json_filename)\n self.assertEqual(SAMPLES_IN_DOC, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_external_ml_n(self) -> None:\n # not existed ml_config\n _stdout, _stderr = self._m_credsweeper(\n [\"--ml_config\", \"not_existed_file\", \"--path\",\n str(APP_PATH), \"--log\", \"CRITICAL\"])\n self.assertEqual(0, len(_stderr))\n self.assertIn(\"CRITICAL\", _stdout)\n # not existed ml_model\n _stdout, _stderr = self._m_credsweeper(\n [\"--ml_model\", \"not_existed_file\", \"--path\",\n str(APP_PATH), \"--log\", \"CRITICAL\"])\n self.assertEqual(0, len(_stderr))\n self.assertIn(\"CRITICAL\", _stdout)\n # wrong config\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n with open(json_filename, \"w\") as f:\n f.write('{}')\n _stdout, _stderr = self._m_credsweeper(\n [\"--ml_config\", json_filename, \"--path\",\n str(APP_PATH), \"--log\", \"CRITICAL\"])\n self.assertEqual(0, len(_stderr))\n self.assertIn(\"CRITICAL\", _stdout)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_external_ml_p(self) -> None:\n log_pattern = re.compile(r\".*Init ML validator with providers: \\S+ ;\"\n r\" model:'.+' md5:([0-9a-f]{32}) ;\"\n r\" config:'.+' md5:([0-9a-f]{32}).*\")\n _stdout, _stderr = self._m_credsweeper([\"--path\", str(APP_PATH), \"--log\", \"INFO\"])\n self.assertEqual(0, len(_stderr))\n self.assertNotIn(\"CRITICAL\", _stdout)\n for i in _stdout.splitlines():\n if log_match := re.match(log_pattern, i):\n md5_config = log_match.group(1)\n md5_model = log_match.group(2)\n break\n else:\n self.fail(f\"'Init ML validator' not found in {_stdout}\")\n with tempfile.TemporaryDirectory() as tmp_dir:\n custom_ml_config = os.path.join(tmp_dir, f\"{__name__}.json\")\n shutil.copyfile(APP_PATH / \"ml_model\" / \"ml_config.json\", custom_ml_config)\n custom_ml_model = os.path.join(tmp_dir, f\"{__name__}.onnx\")\n shutil.copyfile(APP_PATH / \"ml_model\" / \"ml_model.onnx\", custom_ml_model)\n with open(custom_ml_config, \"a\") as f:\n f.write(\"\\n\\n\\n\")\n args = [\n \"--ml_config\", custom_ml_config, \"--ml_model\", custom_ml_model, \"--path\",\n str(APP_PATH), \"--log\", \"INFO\"\n ]\n _stdout, _stderr = self._m_credsweeper(args)\n self.assertEqual(\"\", _stderr)\n self.assertNotIn(\"CRITICAL\", _stdout)\n # model hash is the same\n self.assertIn(md5_model, _stdout)\n # hash of ml config will be different\n self.assertNotIn(md5_config, _stdout)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n" }, { "path": "tests/test_doc.py", "content": "import unittest\n\nimport deepdiff # type: ignore\n\nfrom credsweeper.app import CredSweeper\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom tests import SAMPLES_PATH\n\n\nclass TestDoc(unittest.TestCase):\n\n def setUp(self) -> None:\n self.cred_sweeper = CredSweeper(doc=True, ml_threshold=0)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_secret_pair_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"doc_secret_pair\"])\n self.cred_sweeper.run(content_provider=content_provider)\n found_credentials = self.cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(40, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_passwd_pair_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"doc_passwd_pair\"])\n self.cred_sweeper.run(content_provider=content_provider)\n found_credentials = self.cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(76, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_ip_id_passwd_triple_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"doc_ip_id_password_triple\"])\n self.cred_sweeper.run(content_provider=content_provider)\n found_credentials = self.cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(5, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_id_pair_passwd_pair_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"doc_id_pair_passwd_pair\"])\n self.cred_sweeper.run(content_provider=content_provider)\n found_credentials = self.cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(248, len(found_credentials), found_credentials)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_id_passwd_pair_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"doc_id_passwd_pair\"])\n self.cred_sweeper.run(content_provider=content_provider)\n found_credentials = self.cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(44, len(found_credentials), found_credentials)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n" }, { "path": "tests/test_git.py", "content": "import base64\nimport gzip\nimport io\nimport os\nimport shutil\nimport sys\nimport tempfile\nimport time\nimport unittest\nfrom tarfile import TarFile\nfrom unittest import mock\nfrom unittest.mock import Mock\n\nfrom credsweeper.common.constants import Severity\nfrom credsweeper.main import EXIT_SUCCESS, main\nfrom credsweeper.utils.util import Util\n\n\nclass TestGit(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n # * commit b7b09c8cdec2904dbb6f77eec2aa6abaef975252 (HEAD -> master)\n # | Author: Your Name \n # | Date: Sun Jun 8 16:56:48 2025 +0300\n # |\n # | Key removed\n # |\n # * commit 9d3df94e8257240aa2b98dee47dc17992c0b7476\n # Author: Your Name \n # Date: Sun Jun 8 16:56:25 2025 +0300\n #\n # Key added\n git_repo_tar_gz_base64 = \"\"\"\n H4sICCSlRWgAA3NhbXBsZS50YXIA7DwNcBzVeTYMBC00Mb/JNIU+Vopl2drT/eok2ZYxko1F/SP8\n Uwi2EXu77+7Wuts974+kA+OZFiZDYICQAAmEv1APNGQwGXcYCE06odRAan4LIWVaMiWpEwqmnQAB\n p1Do9733dm/vJFkSls9kuDcwvtt773vf//t+3iqSM9yOOUd2RGGk0yn8N5ZORcP/+mNOLBWNxxKx\n RDwJz2OxJPxMUkcYLzY8x1VtQuZk1Aw16fCk86b6/Y90RFD+VmYb1VznSOnBzOWfiEVjDfnXY1TJ\n P5M+IirwCeSfjDXkX5dRK/9MtFvr0nSqxbujST2T6cym0xS+qWqnmlFptjudiqfiM9sDBZxMJieV\n fzyRrJZ/PBYHlSDRI0Ny9fiMy39s7s3X/710TGzenAfeOf3fTtzzswcGzug/cNzl+5a8Nxj9zQnd\n v/volx/+9VvRY7+1re25z698cXf65LtffybW+hfzVyy68diLb2re+0pu3xMfdF8zr/n7X0mWR/9j\n yf5bB1buP0k9Yf6e5x7f3m08WThl5XnP3v/D984rlh4cvnLzgmPue2D3F//wtT0//s9vbOu+cuSf\n Th3u/8Llt8/7+d3a7n133froPx+/5vz/W/WXy275fd/JR5s3n4VRZf+p2FH3/7F0HP1/IhFv+P96\n jFr5J2lWSyaSnVoyFk9k4l3JqJoEcSXj8F8mBVJLZFLx2Mz2mMr/d8ZTNfIHbels+P96jLG5xRsf\n vuW7g6fN2frO6W+8f/CE/nk3fXFsyVnyqqu2DrbeEx24+ulfPPiTh+67I3PN19+M9JZO+eDN95fp\n V339itLSri1b327q7dky+K624Np5r7RdfdKlT12679RfPnfsXV/a9sauRw9mn/C6HrpAPv75XTc8\n 8bnHnyy88fy1N+9+Zef9dy29ueN2eeu/FIzv/uDOg6XMxYtuSSr/O5icbw0e3H3aRfN++pb105Nu\n 0246oO57W3/xxI82nb/xnJdjO49/+R/c25Rr771JfXr02/TegVfW7hi+5O17HzzuhYt/t//1V+dK\n //NnK4tnv/Q3V94YHdz8V6fZG254f/vr+0b37np/53M/7rrtOz96dezX1629iz6ya/iSnaUzvze6\n /ex1P/z5w7eUDpx63Tnb5z/7wXeuz7+5b9FZw088uiN13WvRvY9884J3Pnf+V3sXfvCjh27/0+9f\n /PQjyd/2n3fhfcWuLxzof+Hgs9K8TXd+/K83fbnttI96v3J//LXXUk8+b91/lrTjnV9d9IP/Kl70\n rUU3frj/xGV3uvfM65e2nXLGq7veKe85sPrzLS/8dljb/eaB7+19OLJ53ddaVy7fO+f3iT955Y2P\n czuP3bXsjm/UUf5V9l9SteEjcALMwP/HOyHwB3cTjTfy/7qMKvmnPwX5H5M/nP/JhvzrMWrl35XK\n 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TH+UrmH/0et/DfX/hf3n9lM0/rdi+qN0Lfsfy//a+spi/OeR4uN/w6Y/SjPX/9VKbPxr6+XF+d9c\n 0lVtZwvl4NeZovk/sm/LCeT66//KSm3h/zOXROOPl2n+P9P/yrXF+M8jRePvfKSr/m6hjlnr/8pa\n Yv6vry7wn+eS+LK7XlBgcKpCgSEN4B/hhwK6GW8m2CR9Rz1FLPOkR/edDMXUCPQWOYh/jVBpeMs6\n Oh+rvh9gxKXrqe18DI+DI1bwfiy+SxGvO6G7saRWjP4C9dQLVHZsQuX34ze3CwJlP1eHl5eLr337\n CP/5aaHGxJIMbMf5eHt1zDz/K8f1/2ptfWH/m0va2X2+DX/+AP/He4Tgzx//pqzK6Sd/cfRPj/7Z\n +8e/ffOfT/7n3/7mr//3v3b/cPivDz6e/9U/VP/u93+5/i//sfbvf/T13//35yV/kX5hovnPkdy3\n VsfM+b8Sv/+zurayWP/nkl4jgv8RAvXpo3y+/UBj2m8ymkrPIcjxTUU336VauMJvqq5NGCs9/8Tu\n 9TCQlLAVA53tc7dtkRZpkRZpkRZpkaan/wORQSDXAPAAAA==\n \"\"\"\n self.temp_dir_path = tempfile.mkdtemp(prefix=__name__)\n git_repo_tar_gz = base64.b64decode(git_repo_tar_gz_base64)\n with gzip.open(io.BytesIO(git_repo_tar_gz)) as gzipf:\n with TarFile(fileobj=io.BytesIO(gzipf.read())) as tf:\n for tfi in tf.getmembers():\n target = os.path.join(self.temp_dir_path, tfi.name)\n if tfi.isreg():\n with tf.extractfile(tfi) as tfd:\n with open(target, \"wb\") as f:\n f.write(tfd.read())\n else:\n os.mkdir(target)\n\n def tearDown(self):\n if 12 <= sys.version_info.minor and \"nt\" == os.name:\n # workaround for the case\n time.sleep(1)\n shutil.rmtree(self.temp_dir_path, ignore_errors=True)\n else:\n # all others\n shutil.rmtree(self.temp_dir_path)\n\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_git_n(self, mock_get_arguments) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, \"report.json\")\n args_mock = Mock(log='warning',\n config_path=None,\n path=[self.temp_dir_path],\n git=None,\n ref=None,\n diff_path=None,\n error=False,\n json_filename=json_filename,\n xlsx_filename=None,\n subtext=False,\n hashed=False,\n sort_output=True,\n rule_path=None,\n jobs=1,\n no_filters=False,\n log_config_path=None,\n ml_threshold=0,\n ml_batch_size=16,\n ml_config=None,\n ml_model=None,\n ml_providers=None,\n pedantic=False,\n depth=0,\n doc=False,\n size_limit=\"1G\",\n find_by_ext=False,\n denylist_path=None,\n severity=Severity.INFO.value)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_SUCCESS, main())\n # no files in last commit\n self.assertFalse(os.path.exists(json_filename))\n\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_git_p(self, mock_get_arguments) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, \"report.json\")\n args_mock = Mock(log='warning',\n config_path=None,\n path=None,\n git=self.temp_dir_path,\n ref=\"b7b09c8cdec2904dbb6f77eec2aa6abaef975252\",\n diff_path=None,\n error=False,\n json_filename=json_filename,\n xlsx_filename=None,\n subtext=False,\n hashed=False,\n sort_output=True,\n rule_path=None,\n jobs=1,\n no_filters=False,\n log_config_path=None,\n ml_threshold=0,\n ml_batch_size=16,\n ml_config=None,\n ml_model=None,\n ml_providers=None,\n pedantic=False,\n depth=0,\n doc=False,\n size_limit=\"1G\",\n find_by_ext=False,\n denylist_path=None,\n severity=Severity.INFO.value)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_SUCCESS, main())\n\n empty_report_filename = os.path.join(tmp_dir, \"report.b7b09c8cdec2904dbb6f77eec2aa6abaef975252.json\")\n self.assertFalse(os.path.exists(empty_report_filename))\n\n full_report_filename = os.path.join(tmp_dir, \"report.9d3df94e8257240aa2b98dee47dc17992c0b7476.json\")\n self.assertTrue(os.path.exists(full_report_filename))\n full_report = Util.json_load(full_report_filename)\n self.assertLessEqual(1, len(full_report))\n" }, { "path": "tests/test_main.py", "content": "import io\nimport logging\nimport os\nimport random\nimport shutil\nimport string\nimport tempfile\nimport unittest\nimport uuid\nfrom argparse import ArgumentTypeError\nfrom pathlib import Path\nfrom tarfile import ReadError\nfrom typing import List, Any, Dict\nfrom unittest import mock\nfrom unittest.mock import Mock, patch, call, ANY\n\nimport deepdiff # type: ignore\nimport pandas as pd\nimport pytest\n\nfrom credsweeper.app import APP_PATH, CredSweeper\nfrom credsweeper.common.constants import ThresholdPreset, Severity, MIN_DATA_LEN\nfrom credsweeper.file_handler.abstract_provider import AbstractProvider\nfrom credsweeper.file_handler.byte_content_provider import ByteContentProvider\nfrom credsweeper.file_handler.files_provider import FilesProvider\nfrom credsweeper.file_handler.string_content_provider import StringContentProvider\nfrom credsweeper.file_handler.text_content_provider import TextContentProvider\nfrom credsweeper.main import EXIT_FAILURE, main, EXIT_SUCCESS, get_arguments, positive_int, threshold_or_float_or_zero\nfrom credsweeper.utils.util import Util\nfrom tests import SAMPLES_FILTERED_COUNT, SAMPLES_POST_CRED_COUNT, SAMPLES_PATH, TESTS_PATH, SAMPLES_IN_DEEP_1, \\\n SAMPLES_IN_DEEP_3, SAMPLES_IN_DEEP_2, ZERO_ML_THRESHOLD, AZ_DATA, SAMPLE_HTML, SAMPLE_DOCX, SAMPLE_TAR, \\\n SAMPLE_PY, SAMPLES_FILES_COUNT\nfrom tests.data import DATA_TEST_CFG\n\n\nclass TestMain(unittest.TestCase):\n\n def setUp(self):\n self.maxDiff = None\n\n def tearDown(self):\n pass\n\n def test_ml_validation_p(self) -> None:\n cred_sweeper = CredSweeper()\n self.assertEqual(ThresholdPreset.medium, cred_sweeper.ml_threshold)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_ml_validation_n(self) -> None:\n cred_sweeper = CredSweeper(ml_threshold=0)\n self.assertEqual(0, cred_sweeper.ml_threshold)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_use_filters_p(self) -> None:\n cred_sweeper = CredSweeper(use_filters=True)\n files_provider = [TextContentProvider(SAMPLES_PATH / \"password_FALSE\")]\n cred_sweeper.scan(files_provider)\n creds = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(0, len(creds))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_use_filters_n(self) -> None:\n cred_sweeper = CredSweeper(use_filters=False)\n files_provider = [TextContentProvider(SAMPLES_PATH / \"password_FALSE\")]\n cred_sweeper.scan(files_provider)\n creds = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(3, len(creds))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_rules_dub_n(self) -> None:\n with self.assertRaisesRegex(RuntimeError, r\"Wrong rules 'None' were read from 'NotExistedPath'\"):\n CredSweeper(rule_path=\"NotExistedPath\")\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_rules_file = os.path.join(tmp_dir, \"test_rules.yaml\")\n dub_rules = [{\n \"name\": \"TestRuleNameDub\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"min_line_len\": 42,\n \"values\": [\"(?P.*)\"],\n \"target\": [\"code\"],\n }, {\n \"name\": \"TestRuleNameDub\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"min_line_len\": 42,\n \"values\": [\"(?P.*)\"],\n \"target\": [\"code\", \"doc\"],\n }]\n Util.yaml_dump(dub_rules, test_rules_file)\n with self.assertRaisesRegex(RuntimeError, r\"Duplicated rule name TestRuleNameDub\"):\n CredSweeper(rule_path=test_rules_file)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_rules_dub_p(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_rules_file = os.path.join(tmp_dir, \"test_rules.yaml\")\n dub_rules = [{\n \"name\": \"TestRuleNameDub\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"min_line_len\": 42,\n \"values\": [\"(?P.*)\"],\n \"target\": [\"code\"],\n }, {\n \"name\": \"TestRuleNameDub\",\n \"severity\": \"high\",\n \"confidence\": \"moderate\",\n \"type\": \"pattern\",\n \"min_line_len\": 42,\n \"values\": [\"(?P.*)\"],\n \"target\": [\"doc\"],\n }]\n Util.yaml_dump(dub_rules, test_rules_file)\n self.assertIsNotNone(CredSweeper(rule_path=test_rules_file))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @mock.patch(\"credsweeper.main.scan\", return_value=1)\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_main_n(self, mock_get_arguments, mock_scan) -> None:\n args_mock = Mock(log='debug',\n path=\"mocked-scan\",\n diff_path=None,\n error=True,\n json_filename=None,\n xlsx_filename=None,\n stdout=False,\n color=False,\n rule_path=None,\n jobs=1)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_FAILURE, main())\n self.assertTrue(mock_scan.called)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_main_path_p(self, mock_get_arguments) -> None:\n target_path = SAMPLES_PATH / \"password.patch\"\n with tempfile.TemporaryDirectory() as tmp_dir:\n args_mock = Mock(log='warning',\n path=None,\n config_path=None,\n diff_path=[str(target_path)],\n error=False,\n json_filename=Path(os.path.join(tmp_dir, f\"{__name__}.json\")),\n xlsx_filename=Path(os.path.join(tmp_dir, f\"{__name__}.xlsx\")),\n color=False,\n subtext=False,\n hashed=False,\n rule_path=None,\n jobs=1,\n ml_threshold=0,\n ml_batch_size=1,\n depth=0,\n doc=False,\n severity=Severity.INFO.value,\n size_limit=\"1G\",\n denylist_path=None)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_SUCCESS, main())\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.xlsx\")))\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.deleted.json\")))\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.added.json\")))\n report = Util.json_load(os.path.join(tmp_dir, f\"{__name__}.added.json\"))\n self.assertTrue(report)\n self.assertEqual(3, report[0][\"line_data_list\"][0][\"line_num\"])\n self.assertEqual(\"dkajco1\", report[0][\"line_data_list\"][0][\"value\"])\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_binary_patch_p(self, mock_get_arguments) -> None:\n # test verifies case when binary diff might be scanned\n target_path = SAMPLES_PATH / \"multifile.patch\"\n with tempfile.TemporaryDirectory() as tmp_dir:\n args_mock = Mock(log='warning',\n path=None,\n config_path=None,\n diff_path=[str(target_path)],\n error=False,\n json_filename=os.path.join(tmp_dir, f\"{__name__}.json\"),\n xlsx_filename=None,\n subtext=False,\n hashed=False,\n sort_output=False,\n rule_path=None,\n jobs=1,\n ml_threshold=0,\n ml_batch_size=1,\n depth=9,\n doc=False,\n severity=Severity.INFO.value,\n size_limit=\"1G\",\n denylist_path=None)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_SUCCESS, main())\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.deleted.json\")))\n self.assertTrue(os.path.exists(os.path.join(tmp_dir, f\"{__name__}.added.json\")))\n report = Util.json_load(os.path.join(tmp_dir, f\"{__name__}.added.json\"))\n self.assertTrue(report)\n self.assertEqual(5, len(report))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @mock.patch(\"credsweeper.main.get_arguments\")\n def test_report_p(self, mock_get_arguments) -> None:\n # verifies reports creations\n with tempfile.TemporaryDirectory() as tmp_dir:\n json_filename = os.path.join(tmp_dir, \"report.json\")\n xlsx_filename = os.path.join(tmp_dir, \"report.xlsx\")\n args_mock = Mock(log='warning',\n config_path=None,\n path=[str(SAMPLES_PATH)],\n diff_path=None,\n error=False,\n json_filename=json_filename,\n xlsx_filename=xlsx_filename,\n subtext=False,\n hashed=False,\n sort_output=True,\n rule_path=None,\n jobs=1,\n ml_threshold=0,\n ml_batch_size=16,\n ml_config=None,\n ml_model=None,\n ml_providers=None,\n pedantic=False,\n depth=0,\n doc=False,\n size_limit=\"1G\",\n find_by_ext=False,\n denylist_path=None,\n severity=Severity.INFO)\n mock_get_arguments.return_value = args_mock\n self.assertEqual(EXIT_SUCCESS, main())\n self.assertTrue(os.path.exists(xlsx_filename))\n self.assertTrue(os.path.exists(json_filename))\n report = Util.json_load(json_filename)\n self.assertTrue(report)\n self.assertEqual(SAMPLES_FILTERED_COUNT, len(report))\n self.assertIn(str(SAMPLES_PATH), report[0][\"line_data_list\"][0][\"path\"])\n self.assertTrue(\"info\", report[0][\"line_data_list\"][0].keys())\n for cred in report:\n for line_data in cred[\"line_data_list\"]:\n # check correctness start-end position\n line = line_data[\"line\"]\n value = line_data[\"value\"]\n value_start = line_data[\"value_start\"]\n value_end = line_data[\"value_end\"]\n if 0 <= value_start and 0 <= value_end:\n self.assertEqual(value, line[line_data[\"value_start\"]:line_data[\"value_end\"]], cred)\n df = pd.read_excel(xlsx_filename)\n excel_report_delta_rows = 288\n self.assertEqual(SAMPLES_FILTERED_COUNT + excel_report_delta_rows, len(df))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n @mock.patch(\"argparse.ArgumentParser.parse_args\")\n def test_parse_args_n(self, mock_parse) -> None:\n self.assertTrue(get_arguments())\n self.assertTrue(mock_parse.called)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_positive_int_p(self):\n i = random.randint(1, 100)\n self.assertEqual(positive_int(i), i)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_positive_int_n(self):\n i = random.randint(-100, 0)\n with pytest.raises(ArgumentTypeError):\n positive_int(i)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_threshold_or_float_or_zero_p(self):\n f = random.random()\n self.assertEqual(f, threshold_or_float_or_zero(str(f)))\n self.assertIsInstance(threshold_or_float_or_zero('0'), int)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_threshold_or_float_or_zero_n(self):\n with pytest.raises(ArgumentTypeError):\n threshold_or_float_or_zero(\"DUMMY STRING\")\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_wrong_severity_n(self) -> None:\n with self.assertRaises(RuntimeError):\n CredSweeper(severity=\"wrong\")\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_scan_bytes_p(self) -> None:\n to_scan = b\"line one\\npassword='in_line_2'\"\n cred_sweeper = CredSweeper()\n provider = ByteContentProvider(to_scan)\n results = cred_sweeper.file_scan(provider)\n self.assertEqual(1, len(results))\n self.assertEqual(\"Password\", results[0].rule_name)\n self.assertEqual(\"password\", results[0].line_data_list[0].variable)\n self.assertEqual(\"in_line_2\", results[0].line_data_list[0].value)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_scan_bytes_n(self) -> None:\n to_scan = \"line one\\npassword='in_line_2'\".encode('utf-32') # unsupported\n cred_sweeper = CredSweeper()\n provider = ByteContentProvider(to_scan)\n results = cred_sweeper.file_scan(provider)\n self.assertEqual(0, len(results))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_colored_line_p(self) -> None:\n cred_sweeper = CredSweeper()\n for to_scan in (\n \"토큰MTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy사용\".encode(),\n b'\\x1b[93mMTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy\\x1b[0m',\n b'\\r\\nMTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy\\r\\n',\n b'\\tMTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy\\n',\n b'%3DMTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy%3B',\n ):\n provider = ByteContentProvider(to_scan)\n results = cred_sweeper.file_scan(provider)\n self.assertEqual(1, len(results), to_scan)\n self.assertEqual(\"Jira / Confluence PAT token\", results[0].rule_name)\n self.assertEqual(\"MTAwMDoxVKvgS4Y7K7UIXHqBmV50aWFs5sb2heWGb3dy\", results[0].line_data_list[0].value)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_string_content_provider_n(self) -> None:\n random.seed(42)\n ascii_chars = string.digits + string.ascii_letters + string.punctuation + ' '\n text = ''.join(random.choice(ascii_chars) for _ in range(1 << 20)) # 1Mb dummy text\n cred_sweeper = CredSweeper()\n provider = StringContentProvider([text])\n results = cred_sweeper.file_scan(provider)\n self.assertAlmostEqual(14, len(results), delta=7) # various lines may look like tokens\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_find_by_ext_and_not_ignore_p(self) -> None:\n # checks only exact match (may be wrong for windows)\n config_dict = Util.json_load(APP_PATH / \"secret\" / \"config.json\")\n self.assertTrue(config_dict)\n find_by_ext_list_items = config_dict[\"find_by_ext_list\"]\n self.assertTrue(isinstance(find_by_ext_list_items, list))\n find_by_ext_list_set = set(find_by_ext_list_items)\n self.assertTrue(len(find_by_ext_list_items) > 0)\n # check whether ignored extension does not exist in find_by_ext_list\n exclude_extension_items = config_dict[\"exclude\"][\"extension\"]\n self.assertTrue(isinstance(exclude_extension_items, list))\n extension_conflict = find_by_ext_list_set.intersection(exclude_extension_items)\n self.assertSetEqual(set(), extension_conflict)\n # check whether ignored container does not exist in find_by_ext_list\n exclude_containers_items = config_dict[\"exclude\"][\"containers\"]\n self.assertTrue(isinstance(exclude_containers_items, list))\n containers_conflict = find_by_ext_list_set.intersection(exclude_containers_items)\n self.assertSetEqual(set(), containers_conflict)\n # check whether extension and containers have no duplicates\n containers_extension_conflict = set(exclude_extension_items).intersection(exclude_containers_items)\n self.assertSetEqual(set(), containers_extension_conflict)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_multi_jobs_n(self) -> None:\n logging.getLogger().setLevel(level=logging.INFO)\n with tempfile.TemporaryDirectory() as tmp_dir:\n # one file will be sent to single job\n content_provider: AbstractProvider = FilesProvider([tmp_dir])\n cred_sweeper = CredSweeper(pool_count=7)\n # empty dir returns nothing\n with patch('logging.Logger.info') as mocked_logger:\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n mocked_logger.assert_called_with(\"No scannable targets for %s paths\", 1)\n # one dummy file without credentials\n with open(os.path.join(tmp_dir, \"dummy\"), \"wb\") as f:\n f.write(AZ_DATA)\n with patch('logging.Logger.info') as mocked_logger:\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n mocked_logger.assert_has_calls([\n call(\"Scan for %s providers\", 1),\n call(\"Completed: processed %s providers with %s candidates\", 1, 0),\n call(\"Skip ML validation because no candidates were found\"),\n call(\"Exporting %s credentials\", 0)\n ])\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_multi_jobs_p(self) -> None:\n logging.getLogger().setLevel(level=logging.INFO)\n # samples dir - many providers\n cred_sweeper = CredSweeper(pool_count=3)\n with patch('logging.Logger.info') as mocked_logger:\n cred_sweeper.run(content_provider=FilesProvider([SAMPLES_PATH]))\n mocked_logger.assert_has_calls([\n call(\"Scan in %s processes for %s providers\", 3, SAMPLES_FILES_COUNT - 23),\n call(\"Grouping %s candidates\", SAMPLES_FILTERED_COUNT),\n ANY, # Run ML Validation for \\d+ groups\n ANY, # initial ML with various arguments, cannot predict\n call(\"Exporting %s credentials\", SAMPLES_POST_CRED_COUNT),\n ])\n self.assertEqual(SAMPLES_POST_CRED_COUNT, cred_sweeper.credential_manager.len_credentials())\n cred_sweeper.credential_manager.clear_credentials()\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n # each file as provider\n content_provider = FilesProvider([x for x in SAMPLES_PATH.glob(\"**/*\")])\n with patch('logging.Logger.info') as mocked_logger:\n cred_sweeper.run(content_provider=content_provider)\n mocked_logger.assert_has_calls([\n call(f\"Scan in %s processes for %s providers\", 3, SAMPLES_FILES_COUNT - 23),\n call(f\"Grouping %s candidates\", SAMPLES_FILTERED_COUNT),\n ANY, # Run ML Validation for \\d+ groups\n # no init\n call(f\"Exporting %s credentials\", SAMPLES_POST_CRED_COUNT),\n ])\n self.assertEqual(SAMPLES_POST_CRED_COUNT, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_find_by_ext_n(self) -> None:\n # test for finding files by extension\n with tempfile.TemporaryDirectory() as tmp_dir:\n ext_list = [\".pem\", \".cer\", \".csr\", \".der\", \".pfx\", \".p12\", \".key\", \".jks\"]\n for ext in ext_list:\n with open(os.path.join(tmp_dir, f\"dummy{ext}\"), \"wb\") as f:\n f.write(b'\\x00' * MIN_DATA_LEN)\n with open(os.path.join(tmp_dir, f\"short{ext}\"), \"wb\") as f:\n f.write(b'\\x00' * (MIN_DATA_LEN - 1))\n with open(os.path.join(tmp_dir, f\"dummy{ext}.bak\"), \"wb\") as f:\n f.write(AZ_DATA)\n content_provider: AbstractProvider = FilesProvider([tmp_dir])\n cred_sweeper = CredSweeper(find_by_ext=True)\n cred_sweeper.run(content_provider=content_provider)\n credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(len(ext_list), len(credentials))\n self.assertTrue(all(\"Suspicious File Extension\" == x.rule_name for x in credentials))\n # aux checks - only 1/3 of all files will be found by extension\n test_files_number = len(os.listdir(tmp_dir))\n self.assertEqual(len(ext_list), test_files_number // 3)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_tar_n(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_TAR])\n cred_sweeper = CredSweeper(depth=0)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_tar_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_TAR])\n cred_sweeper = CredSweeper(depth=1)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(1, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_bad_tar_n(self) -> None:\n # test for bad tar - throws exception\n bad_tar_sample = SAMPLES_PATH / \"bad.tar.bz2\"\n content_provider: AbstractProvider = FilesProvider([bad_tar_sample])\n cred_sweeper = CredSweeper(depth=2)\n with patch(\"logging.Logger.warning\") as mocked_logger:\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n mocked_logger.assert_called_with(\"%s:%s\", bad_tar_sample.as_posix()[:-4], ANY)\n args, _ = mocked_logger.call_args\n self.assertIsInstance(args[2], ReadError)\n self.assertEqual(\"unexpected end of data\", str(args[2]))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_png_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"sample.png\"])\n cred_sweeper = CredSweeper(depth=3, pedantic=True)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(4, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_aws_multi_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"aws_multi.md\"])\n cred_sweeper = CredSweeper(ml_threshold=0, color=True, hashed=True)\n cred_sweeper.run(content_provider=content_provider)\n for i in cred_sweeper.credential_manager.get_credentials():\n if \"AWS Multi\" == i.rule_name:\n self.assertEqual(7, i.line_data_list[0].line_num)\n self.assertEqual(8, i.line_data_list[1].line_num)\n break\n else:\n self.fail(\"AWS Multi was not found\")\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_depth_p(self) -> None:\n # test for finding files with --depth\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH])\n cred_sweeper = CredSweeper(depth=1)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(SAMPLES_IN_DEEP_1, cred_sweeper.credential_manager.len_credentials())\n cred_sweeper.config.depth = 2\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(SAMPLES_IN_DEEP_2, cred_sweeper.credential_manager.len_credentials())\n cred_sweeper.config.depth = 3\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(SAMPLES_IN_DEEP_3, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_depth_n(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH])\n cred_sweeper = CredSweeper(depth=0)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(SAMPLES_POST_CRED_COUNT, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_bzip2_p(self) -> None:\n # test for finding files by extension\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"pem_key.bz2\"])\n cred_sweeper = CredSweeper(depth=1)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(1, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_bzip2_n(self) -> None:\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_filename = os.path.join(tmp_dir, __name__)\n self.assertFalse(os.path.exists(test_filename))\n with open(test_filename, \"wb\") as f:\n f.write(b\"\\x42\\x5A\\x68\\x35\\x31\\x41\\x59\\x26\\x53\\x59\")\n content_provider: AbstractProvider = FilesProvider([test_filename])\n cred_sweeper = CredSweeper(depth=1)\n with patch('logging.Logger.warning') as mocked_logger:\n cred_sweeper.run(content_provider=content_provider)\n mocked_logger.assert_called_with(\"%s:%s\", test_filename, ANY)\n args, _ = mocked_logger.call_args\n self.assertIsInstance(args[2], ValueError)\n self.assertEqual(\"Compressed data ended before the end-of-stream marker was reached\", str(args[2]))\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_eml_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"test.eml\"])\n cred_sweeper = CredSweeper(doc=True, ml_threshold=ZERO_ML_THRESHOLD)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertLessEqual(1, len(found_credentials), found_credentials)\n self.assertEqual(\"PW: H1ddEn#ema1l\", found_credentials[0].line_data_list[0].line)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_pdf_p(self) -> None:\n # may be tested with\n # https://www.dcc.edu/documents/administration/offices/information-technology/password-examples.pdf\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"sample.pdf\"])\n cred_sweeper = CredSweeper(depth=7, ml_threshold=ZERO_ML_THRESHOLD)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertSetEqual({\"Password\", \"Token\", \"Github Classic Token\"}, set(i.rule_name for i in found_credentials))\n self.assertSetEqual(\n {\"Xdj@jcN834b\", \"bace4d31-fa7e-beef-cafe-912947cbe28\", \"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\"},\n set(i.line_data_list[0].value for i in found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_pdf_n(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"sample.pdf\"])\n cred_sweeper = CredSweeper()\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_py_n(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_PY])\n cred_sweeper = CredSweeper(severity=Severity.LOW, ml_threshold=0)\n cred_sweeper.run(content_provider=content_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_py_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_PY])\n cred_sweeper = CredSweeper(severity=Severity.LOW, ml_threshold=0, depth=1)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n expected_credentials = [{\n 'rul': 'API',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'API_SECRET_KEY'\n }, {\n 'rul': 'API',\n 'val': 'a3f1ef0ff53236141253c0372',\n 'var': 'SECRET_CREDENTIAL_API_KEY'\n }, {\n 'rul': 'Auth',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'AUTH_SECRET_NONCE'\n }, {\n 'rul': 'Auth',\n 'val': 'Hbr73gu7gdsr==',\n 'var': 'AUTH'\n }, {\n 'rul': 'Auth',\n 'val': 'RlQ8MGlWH8Hn1TrHn6WBfy31EhIIJmBsuUBOU8H2AJ6KnJC0L3djWHaqhDTZTth',\n 'var': 'AUTH_CREDENTIAL_SECRET'\n }, {\n 'rul': 'Auth',\n 'val': '\\\\t8ab20238fb3ef48823e75469b5712d3f0baf2e58\\\\r\\\\n',\n 'var': 'X_Auth_Tokens'\n }, {\n 'rul': 'Credential',\n 'val': 'RlQ8MGlWH8Hn1TrHn6WBfy31EhIIJmBsuUBOU8H2AJ6KnJC0L3djWHaqhDTZTth',\n 'var': 'AUTH_CREDENTIAL_SECRET'\n }, {\n 'rul': 'Credential',\n 'val': 'a3f1ef0ff53236141253c0372',\n 'var': 'SECRET_CREDENTIAL_API_KEY'\n }, {\n 'rul': 'Key',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'API_SECRET_KEY'\n }, {\n 'rul': 'Key',\n 'val': 'a3f1ef0ff53236141253c0372',\n 'var': 'SECRET_CREDENTIAL_API_KEY'\n }, {\n 'rul': 'Nonce',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'AUTH_SECRET_NONCE'\n }, {\n 'rul': 'Password',\n 'val': '\\\\udf42\\\\ud834\\\\udd1e\\\\ud824\\\\ud837\\\\ud801\\\\ud852\\\\udf62',\n 'var': 'PASSWORD'\n }, {\n 'rul': 'Salt',\n 'val': '\\\\xdf42\\\\xd834\\\\xdd1E\\\\xd824\\\\xd837\\\\xd801\\\\xd852\\\\xdf62',\n 'var': 'SALT'\n }, {\n 'rul': 'Secret',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'API_SECRET_KEY'\n }, {\n 'rul': 'Secret',\n 'val': '223, 66, 216, 52, 221, 30, 216, 36, 216, 55, 216, 1, 216, 82, 223, 98',\n 'var': 'AUTH_SECRET_NONCE'\n }, {\n 'rul': 'Secret',\n 'val': 'R15br4jtfcFbWh9G7EZTb6jR12c9We',\n 'var': 'SECRET'\n }, {\n 'rul': 'Secret',\n 'val': 'RlQ8MGlWH8Hn1TrHn6WBfy31EhIIJmBsuUBOU8H2AJ6KnJC0L3djWHaqhDTZTth',\n 'var': 'AUTH_CREDENTIAL_SECRET'\n }, {\n 'rul': 'Secret',\n 'val': 'a3f1ef0ff53236141253c0372',\n 'var': 'SECRET_CREDENTIAL_API_KEY'\n }, {\n 'rul': 'Token',\n 'val': '1102181139266001652353292050',\n 'var': 'TOKEN'\n }, {\n 'rul': 'Token',\n 'val': '\\\\t8ab20238fb3ef48823e75469b5712d3f0baf2e58\\\\r\\\\n',\n 'var': 'X_Auth_Tokens'\n }]\n expected_credentials.sort(key=lambda x: (x[\"rul\"], x[\"val\"], x[\"var\"]))\n actual_credentials = [ #\n {\n \"rul\": i.rule_name,\n \"val\": i.line_data_list[0].value,\n \"var\": i.line_data_list[0].variable\n } #\n for i in found_credentials\n ]\n actual_credentials.sort(key=lambda x: (x[\"rul\"], x[\"val\"], x[\"var\"]))\n self.assertListEqual(expected_credentials, actual_credentials)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_json_p(self) -> None:\n # test for finding credentials in JSON\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"struct.json\"])\n cred_sweeper = CredSweeper(depth=5)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(1, len(found_credentials))\n self.assertSetEqual({\"Password\"}, set(i.rule_name for i in found_credentials))\n self.assertSetEqual({\"Axt4T0eO0lm9sS==\"}, set(i.line_data_list[0].value for i in found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_json_n(self) -> None:\n # test to prove that no credentials are found without depth\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"struct.json\"])\n cred_sweeper = CredSweeper()\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(0, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_yaml_p(self) -> None:\n # test for finding credentials in YAML\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"binary.yml\"])\n cred_sweeper = CredSweeper(depth=5)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(2, len(found_credentials))\n self.assertSetEqual({\"Secret\", \"PEM Private Key\"}, set(i.rule_name for i in found_credentials))\n self.assertSetEqual({\"we5345d0f3da48544z1t1e275y05i161x995q485\", \"-----BEGIN RSA PRIVATE KEY-----\"},\n set(i.line_data_list[0].value for i in found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_yaml_n(self) -> None:\n # test to prove that no credentials are found without depth\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"binary.yml\"])\n cred_sweeper = CredSweeper()\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(0, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_encoded_p(self) -> None:\n # test for finding credentials in ENCODED data\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH / \"encoded_data\"])\n cred_sweeper = CredSweeper(depth=5, ml_threshold=0, color=True, subtext=True)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(1, len(found_credentials))\n self.assertSetEqual({\"Token\"}, set(i.rule_name for i in found_credentials))\n self.assertEqual(\"gireogicracklecrackle1231567190113413981\", found_credentials[0].line_data_list[0].value)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_docx_p(self) -> None:\n # test for finding credentials in docx\n content_provider: AbstractProvider = FilesProvider([SAMPLE_DOCX])\n cred_sweeper = CredSweeper(doc=True)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n expected_credential_lines = {\n \"second line bace4d11-a002-be1a-c3fe-9829474b5d84\",\n \"first_page_header bace4d11-f001-beea-c3fe-9829474b5d84\",\n \"2 Second page header bace4d19-b002-beda-cafe-0929375bcd82\",\n \"New page first line bace4d19-b001-b3e2-eac1-9129474bcd84\",\n \"Next page section bace4d19-c001-b3e2-eac1-9129474bcd84\",\n \"last page bace4d11-a003-be2a-c3fe-9829474b5d84\",\n \"First line bace4d11-a001-be1a-c3fe-9829474b5d84\",\n \"Default footer bace4119-f002-bdef-dafe-9129474bcd89\",\n \"next line in section bace4d19-c001-b3e2-eac1-9129474bcd84\",\n \"Third page header bace4d19-b003-beda-cafe-0929375bcd82\",\n \"Section R2C2 b5c6471d-a2b2-b4ef-ca5e-9121476bc881\",\n \"Innner cell bace4d11-b003-be1a-c3fe-9829474b5d84\",\n }\n found_lines_set = set(x.line_data_list[0].line for x in found_credentials)\n self.assertSetEqual(expected_credential_lines, found_lines_set)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_docx_n(self) -> None:\n # test docx - no credential should be found without 'doc'\n content_provider: AbstractProvider = FilesProvider([SAMPLE_DOCX])\n cred_sweeper = CredSweeper(doc=False)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(0, len(found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_html_p(self) -> None:\n # test for finding credentials in html\n content_provider: AbstractProvider = FilesProvider([SAMPLE_HTML])\n cred_sweeper = CredSweeper(depth=5, ml_threshold=0, severity=Severity.LOW)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n expected_credential_lines = {\n \"508627689:AAEuLPKs-EhrjrYGnz60bnYNZqakf6HJxc0\",\n \"secret : Ndjbwu88s22ygavsdhgt5454v3h1x\",\n \"password : Cr3DeHTbIal\",\n \"password : 0dm1nk0\",\n \"password : p@$$w0Rd42\",\n \"secret : BNbNbws73bdhss329ssakKhds120384\",\n \"token : H72gsdv2dswPneHduwhfd\",\n \"td : Password: MU$T6Ef09#D!\",\n \"# 94 ya29.dshMb48ehfXwydAj34D32J\",\n \"# 95 dop_v1_425522a565f532bc6532d453422e50334a42f5242a3090fbe553b543b124259b\",\n \"the line will be found twice # 100\"\n \" EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\",\n \"ALTER\\tUSER\\tdetector\\tIDENTIFIED\\tBY\\tSqLpa5sW0rD4;\",\n }\n found_lines_set = set(x.line_data_list[0].line for x in found_credentials)\n self.assertSetEqual(expected_credential_lines, found_lines_set)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_html_n(self) -> None:\n # test_html - no credential should be found without 'depth'\n content_provider: AbstractProvider = FilesProvider([SAMPLE_HTML])\n cred_sweeper = CredSweeper(severity=Severity.LOW)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertListEqual([], found_credentials)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n def test_exclude_value_p(self) -> None:\n cred_sweeper = CredSweeper(use_filters=True, exclude_values=[\"cackle!\"])\n files = [SAMPLES_PATH / \"password.gradle\"]\n files_provider = [TextContentProvider(file_path) for file_path in files]\n cred_sweeper.scan(files_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_exclude_value_n(self) -> None:\n cred_sweeper = CredSweeper(use_filters=True, exclude_values=[\"abc\"])\n files = [SAMPLES_PATH / \"password.gradle\"]\n files_provider = [TextContentProvider(file_path) for file_path in files]\n cred_sweeper.scan(files_provider)\n self.assertEqual(1, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_exclude_line_p(self) -> None:\n cred_sweeper = CredSweeper(use_filters=True, exclude_lines=['password = \"cackle!\"'])\n files = [SAMPLES_PATH / \"password.gradle\"]\n files_provider = [TextContentProvider(file_path) for file_path in files]\n cred_sweeper.scan(files_provider)\n self.assertEqual(0, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_exclude_line_n(self) -> None:\n cred_sweeper = CredSweeper(use_filters=True, exclude_lines=[\"abc\"])\n files = [SAMPLES_PATH / \"password.gradle\"]\n files_provider = [TextContentProvider(file_path) for file_path in files]\n cred_sweeper.scan(files_provider)\n self.assertEqual(1, cred_sweeper.credential_manager.len_credentials())\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_doc_p(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_HTML])\n cred_sweeper = CredSweeper(doc=True, severity=Severity.LOW)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n expected_credential_values = {\n \"508627689:AAEuLPKs-EhrjrYGnz60bnYNZqakf6HJxc0\",\n \"ya29.dshMb48ehfXwydAj34D32J\",\n \"dop_v1_425522a565f532bc6532d453422e50334a42f5242a3090fbe553b543b124259b\",\n \"EAACEb00Kse0BAlGy7KeQ5YnaCEd09Eose0cBAlGy7KeQ5Yna9CoDsup39tiYdoQ4jH9Coup39tiYdWoQ4jHFZD\",\n \"MU$T6Ef09#D!\",\n \"SqLpa5sW0rD4\",\n }\n self.assertSetEqual(expected_credential_values, set(x.line_data_list[0].value for x in found_credentials))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_doc_n(self) -> None:\n content_provider: AbstractProvider = FilesProvider([SAMPLE_HTML])\n cred_sweeper = CredSweeper(doc=False, severity=Severity.LOW)\n cred_sweeper.run(content_provider=content_provider)\n found_credentials = cred_sweeper.credential_manager.get_credentials()\n self.assertListEqual([], found_credentials)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_fallback_n(self) -> None:\n data_line = b'''\n \n '''\n content_provider: AbstractProvider = FilesProvider([io.BytesIO(data_line)])\n cred_sweeper = CredSweeper(doc=True, use_filters=False, ml_threshold=0, color=True)\n cred_sweeper.run(content_provider=content_provider)\n creds = cred_sweeper.credential_manager.get_credentials()\n self.assertListEqual([], creds)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_data_p(self) -> None:\n # the test modifies data/xxx.json with actual result - it discloses impact of changes obviously\n # use git diff to review the changes\n def prepare(report: List[Dict[str, Any]]):\n for x in report:\n # round ml_probability for macos\n ml_probability = x[\"ml_probability\"]\n if isinstance(ml_probability, float):\n x[\"ml_probability\"] = round(ml_probability, 3)\n for y in x[\"line_data_list\"]:\n # update windows style path\n y[\"path\"] = str(y[\"path\"]).replace('\\\\', '/')\n y[\"info\"] = str(y[\"info\"]).replace('\\\\', '/')\n # use relative path to project\n y[\"path\"] = str(y[\"path\"]).replace(TESTS_PATH.as_posix(), './tests')\n y[\"info\"] = str(y[\"info\"]).replace(TESTS_PATH.as_posix(), './tests')\n x[\"line_data_list\"].sort(key=lambda k: (\n k[\"path\"],\n k[\"line_num\"],\n k[\"value\"],\n k[\"info\"],\n k[\"line\"],\n k[\"value_start\"],\n k[\"value_end\"],\n ))\n report.sort(key=lambda k: (\n k[\"line_data_list\"][0][\"path\"],\n k[\"line_data_list\"][0][\"line_num\"],\n k[\"line_data_list\"][0][\"value\"],\n k[\"line_data_list\"][0][\"info\"],\n k[\"line_data_list\"][0][\"value_start\"],\n k[\"line_data_list\"][0][\"value_end\"],\n k[\"severity\"],\n k[\"rule\"],\n k[\"ml_probability\"],\n ))\n\n # instead the config file is used\n for cfg in DATA_TEST_CFG:\n with tempfile.TemporaryDirectory() as tmp_dir:\n expected_report = TESTS_PATH / \"data\" / cfg[\"json_filename\"]\n expected_result = Util.json_load(expected_report)\n # informative parameter, relative with other tests counters. CredSweeper does not know it and fails\n cred_count = cfg.pop(\"__cred_count\")\n prepare(expected_result)\n tmp_file = Path(tmp_dir) / cfg[\"json_filename\"]\n # apply the current path to keep equivalence in path\n content_provider: AbstractProvider = FilesProvider([SAMPLES_PATH])\n # replace output report file to place in tmp_dir\n cfg[\"json_filename\"] = str(tmp_file)\n cred_sweeper = CredSweeper(**cfg)\n cred_sweeper.run(content_provider=content_provider)\n test_result = Util.json_load(tmp_file)\n prepare(test_result)\n # use the same dump as in output\n Util.json_dump(test_result, tmp_file)\n\n diff = deepdiff.DeepDiff(test_result, expected_result)\n if diff:\n # prints produced report to compare with present data in tests/data\n print(f\"Review updated {cfg['json_filename']} with git.\", flush=True)\n shutil.copy(tmp_file, expected_report)\n # first run fails with the diff but next run will pass\n self.assertDictEqual({}, diff, cfg)\n # only count of items must be corrected manually\n self.assertEqual(cred_count, len(expected_result), cfg[\"json_filename\"])\n # check whether all files are real on disk\n for i in test_result:\n for j in i[\"line_data_list\"]:\n f = SAMPLES_PATH / Path(j[\"path\"]).parts[-1]\n self.assertTrue(f.exists(), (f, j))\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_param_n(self) -> None:\n # internal parametrized tests for quick debug - no itms should be found\n items = [ #\n (\"x.json\", b'\"\": \"\\\\u0230n0tAdr0PbX\"'),\n (\"any\", b'secret = \"mysecret\"'),\n (\"t.h\", b'#define TOKEN \"q1111119-fade-1111-c3f0-9129474bcd81\"'), #\n (\"t.h\", b\"#define SECRET 0x0200\"), #\n ('test.m', b's password=$$getTextValue^%dmzAPI(\"pass\",sessid)'),\n ('test.yaml', b'password: Fd[q#pX+@4*r`1]Io'),\n ('enc.yaml', b'password: ENC[qGOpXrr1Iog1W+fjOiIDOT0C/dBjHyhy]'),\n ('enc.yaml', b'password: \"ENC[qGOpXrr1Iog1W+fjOiIDOT0C/dBjHyhy]\"'),\n ('enc.yml', b'password: ENC(qGOpXrr1Iog1W+fjOiIDOT0C/dBjHyhy)'),\n ('enc.yml', b'password: \"ENC(qGOpXrr1Iog1W+fjOiIDOT0C/dBjHyhy)\"'),\n ('x3.txt', b'passwd = values[token_id]'),\n ('t.py', b'new_params = {\"dsn\": new_params[\"dsn\"], \"password\": new_params[\"password\"]}'),\n ('t.m', b'@\"otpauth://host/port?set=VNMXQKAZFVOYOJCDNBIYXYIWX2&algorithm=F4KE\",'),\n (\"test.c\", b\" *keylen = X448_KEYLEN;\"),\n (\"test.php\", b\"$yourls_user_passwords = $copy;\"),\n (\"\", b\"passwords = List\"),\n (\"test.template\", b\" API_KEY_ID=00209332 \"), #\n (\"test.template\", b\" AUTH_API_KEY_NAME='temporally_secret_api' \"), #\n (\"pager.ts\", b\"pagerLimitKey: 'size',\"), #\n (\"pager.rs\", b' this_circleci_pass_secret_id=\"buratino-circle-pass\"'), #\n (\"pager.rs\", b' secret_type: \"odobo\".to_string(),'), #\n (\"pager.rs\", b\" secret_key: impl AsRef, \"), #\n (\"pager.rs\", b\"token: impl AsRef,\"), #\n (\"pager.rs\", b\" let tokens = quote::quote! {\"), #\n (\"pager.rs\", b\" let cert_chain = x509_rx\"), #\n (\"my.kt\", b'val password: String? = null'), #\n ]\n content_provider: AbstractProvider = FilesProvider([(file_name, io.BytesIO(data_line))\n for file_name, data_line in items])\n cred_sweeper = CredSweeper()\n cred_sweeper.run(content_provider=content_provider)\n creds = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(0, len(creds), [x.to_json(False, False) for x in creds])\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_param_p(self) -> None:\n # internal parametrized tests for quick debug\n items = [ #\n (\"any\", b\"Authorization: token 944fb17dc1ca18eb2750b6238e5c5ad27b68aaab\", \"Authorization\",\n \"944fb17dc1ca18eb2750b6238e5c5ad27b68aaab\"),\n (\"any\",\n b'Authorization: NTLM TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=',\n \"Authorization\",\n \"TlRMTVNTUAADAAAAGAAYAFYAAAAYABgAbgAAAAAAAABIAAAADgAOAEgAAAAAAAAAVgAAAAAAAACGAAAARmFLZURhVGEAAAAPQwByAGUAZABTAHcAZQBlAHCgZQBy3wAAAAAAAAAAAAAAAAAAAAAph0MQmDQmCVaJEmhiOGSYIXNJMoc2KLo=\"\n ),\n (\"p.txt\", b'PASSWORD=$ADrn1N?', \"PASSWORD\", \"$ADrn1N?\"),\n (\"x.x\", b\"'token' : 'access_token=1f3a1d0x579bedc83419f39c06a71L01'\", \"access_token\",\n \"1f3a1d0x579bedc83419f39c06a71L01\"),\n (\"ba.sh\", b'if [ \"$DB_URL\" != \"mi6://james:bond#007@localhost:32768/api\" ]; then', \"mi6://\", \"bond#007\"),\n (\"t.h\", b'#define TOKEN \"q2d45d19-fade-1111-c3f0-9129474bcd81\"', \"TOKEN\",\n \"q2d45d19-fade-1111-c3f0-9129474bcd81\"), #\n (\"k.java\",\n b\"private static final long[] KEY = {0x9e37f3a21d0c18e9L, 0x579b9f39cc06a7c1L, 0x057f45cedc834108L, 0xf86c6a1276b27251L};\",\n \"KEY\", \"0x9e37f3a21d0c18e9L, 0x579b9f39cc06a7c1L, 0x057f45cedc834108L, 0xf86c6a1276b27251L\"),\n (\"k.c\", b'static const unsigned char key[] = {0,007, 0x65, 0x72, 0x73, 0x74, 999, 0x61 /* comment */};',\n \"key[]\", \"0,007, 0x65, 0x72, 0x73, 0x74, 999, 0x61 /* comment */\"),\n (\"c.go\", b'Credential: []byte{351, 266, ,1,2,7,4,010, 100, 114, 157},', \"Credential\",\n \"351, 266, ,1,2,7,4,010, 100, 114, 157\"),\n (\"pw.java\", b'\"--keystore-password\", \"WL3XSnGShS87KW\",', \"keystore-password\", \"WL3XSnGShS87KW\"),\n (\"pw.py\", b'[\"--password\", \"XCl5oOtGO9SP\"]', \"password\", \"XCl5oOtGO9SP\"),\n (\"pw.html\", b'user%3Dadmin;pw%3DjakC5df5G4WL;', \"pw\", \"jakC5df5G4WL\"),\n (\"pw.py\", b'pw=env.get(\"PASSWORD\", \"Qj5lo7nYV\"))', \"pw\", \"Qj5lo7nYV\"),\n (\"p.h\", b'.SetPassword(\"mHic7SmwL7lkn0\")', \"Password\", \"mHic7SmwL7lkn0\"),\n (\"pw.h\", b'#define key {0x35, 0x34, 0x65, 0x9b, 0x72, 0x73, 0x1c, 0x2e}', \"key\",\n \"0x35, 0x34, 0x65, 0x9b, 0x72, 0x73, 0x1c, 0x2e\"),\n (\"scrts.cs\", b'Secrets = new[] { new Secret( \"be31IjWLD2rSh6D0H430hg3\".Sha256() ) },', \"Secrets\",\n \"be31IjWLD2rSh6D0H430hg3\"),\n (\"pw.md\", b\"The login password => skWu850\", \"password\", \"skWu850\"), #\n (\"log.txt\", b'Authorization: SSWS 00QEi8-WW0HmCjAl4MlVjFx-vbGPXMD8sWXsua', \"Authorization\",\n \"00QEi8-WW0HmCjAl4MlVjFx-vbGPXMD8sWXsua\"),\n ('test.yaml', b'code\\u003epassword: \"Fd[q#pX+@4*r`1]Io\"', 'password', 'Fd[q#pX+@4*r`1]Io'),\n (\"any\", b'docker swarm join --token qii7t1m6423127xto389xc914l34451qz5135865564sg', 'token',\n 'qii7t1m6423127xto389xc914l34451qz5135865564sg'),\n (\"win.log\", b'java -Password $(ConvertTo-SecureString \"P@5$w0rD!\" -AsPlainText -Force)',\n \"ConvertTo-SecureString\", \"P@5$w0rD!\"),\n ('tk.java',\n b' final OAuth2AccessToken accessToken = new OAuth2AccessToken(\"7c9yp7.y513e1t629w7e8f3n1z4m856a05o\");',\n \"OAuth2AccessToken accessToken\", \"7c9yp7.y513e1t629w7e8f3n1z4m856a05o\"),\n ('my.toml', b'{nkey: XMIGDHSYNSJQ0XNR}', \"nkey\", \"XMIGDHSYNSJQ0XNR\"),\n ('my.yaml', b'%3Epassword: \"3287#JQ0XX@IG}\"', \"password\", \"3287#JQ0XX@IG}\"),\n (\"creds.py\", b'\"tokens\": [\"xabsjh1dbasu7d9g\", \"ashbjhd1ifufhsds\"]', \"tokens\", \"xabsjh1dbasu7d9g\"),\n (\"slt.py\", b'\\\\t\\\\tsalt = \"\\\\x187bhgerjhqw\\\\n iKa\\\\tW_R~0/8\"', \"salt\", \"\\\\x187bhgerjhqw\\\\n iKa\\\\tW_R~0/8\"),\n (\"log.txt\",\n b'json\\\\nAuthorization: Basic jfhlksadjiu9813ryiuhdfskadjlkjh34\\\\n\\\\u003c/code\\\\u003e\\\\u003c/pre\\\\u003e\"',\n \"Authorization\", \"jfhlksadjiu9813ryiuhdfskadjlkjh34\"),\n (\"pwd.html\", b'password => \"ji3_8iKgaW_R~0/8\"', \"password\", \"ji3_8iKgaW_R~0/8\"),\n (\"pwd.py\", b'password = \"/_tcTz None:\n # random generated value in well quoted value may be any (almost) chromium ... password_generator.cc\n safe_chars = [x for x in string.digits + string.ascii_letters + string.punctuation if x not in '\"\\\\01OIol']\n value = ''.join(random.choice(safe_chars) for _ in range(15))\n line = f'password = \"{value}\"'\n content_provider: AbstractProvider = FilesProvider([(\"cred.go\", io.BytesIO(line.encode()))])\n cred_sweeper = CredSweeper(ml_threshold=0)\n cred_sweeper.run(content_provider=content_provider)\n creds = cred_sweeper.credential_manager.get_credentials()\n self.assertEqual(1, len(creds), line)\n self.assertEqual(\"password\", creds[0].line_data_list[0].variable)\n self.assertEqual(value, creds[0].line_data_list[0].value)\n\n # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n\n def test_hashed_n(self) -> None:\n # checks whether hashed hides raw data from report\n test_values = list(str(uuid.uuid4()) for _ in range(7))\n with tempfile.TemporaryDirectory() as tmp_dir:\n test_filename = os.path.join(tmp_dir, f\"{__name__}.yaml\")\n with open(test_filename, 'w') as f:\n for x in test_values:\n f.write(f\"{x}\\n\")\n json_filename = os.path.join(tmp_dir, f\"{__name__}.json\")\n cred_sweeper = CredSweeper(json_filename=json_filename, hashed=True)\n cred_sweeper.run(FilesProvider([test_filename]))\n report = Util.json_load(json_filename)\n # UUID is detected\n self.assertAlmostEqual(len(report), 7, delta=3) # random uuid may be filtered with a pattern\n # but does not contain in report file\n for x in test_values:\n self.assertNotIn(x, str(report))\n" }, { "path": "tests/test_utils/__init__.py", "content": "" }, { "path": "tests/test_utils/dummy_line_data.py", "content": "import re\nfrom typing import Optional\n\nfrom credsweeper.app import APP_PATH\nfrom credsweeper.config.config import Config\nfrom credsweeper.credentials.line_data import LineData\nfrom credsweeper.utils.util import Util\nfrom tests.filters.conftest import LINE_VALUE_PATTERN\n\n\ndef config() -> Config:\n config_dict = Util.json_load(APP_PATH / \"secret\" / \"config.json\")\n\n config_dict[\"use_filters\"] = True\n config_dict[\"find_by_ext\"] = False\n config_dict[\"pedantic\"] = False\n config_dict[\"depth\"] = 0\n config_dict[\"doc\"] = False\n config_dict[\"size_limit\"] = None\n return Config(config_dict)\n\n\ndef get_line_data(test_config: Config = config(),\n file_path: str = \"\",\n line: str = \"\",\n pattern: Optional[re.Pattern] = None) -> LineData:\n pattern = re.compile(pattern) if pattern else re.compile(LINE_VALUE_PATTERN)\n line_data = LineData(test_config, line, 0, 1, file_path, Util.get_extension(file_path), \"info\", pattern)\n assert line_data.value # most important member for filters\n return line_data\n" }, { "path": "tests/utils/__init__.py", "content": "" }, { "path": "tests/utils/test_hop_stat.py", "content": "import unittest\n\nfrom credsweeper.utils.hop_stat import HopStat\n\n\nclass TestHopStat(unittest.TestCase):\n\n def test_hop_stat_n(self):\n HopStat()\n with self.assertRaises(ValueError):\n HopStat().stat('34')\n with self.assertRaises(ValueError):\n HopStat().stat('1')\n with self.assertRaises(ValueError):\n HopStat().stat('1')\n\n def test_hop_stat_p(self):\n self.assertTupleEqual((1, 0), HopStat().stat(\"qwerty\"))\n" }, { "path": "tests/utils/test_util.py", "content": "import binascii\nimport hashlib\nimport os\nimport random\nimport string\nimport tempfile\nimport unittest\nfrom pathlib import Path\nfrom xmlrpc.client import MAXINT\n\nfrom hypothesis import given, strategies\nfrom lxml.etree import XMLSyntaxError\n\nfrom credsweeper.common.constants import Chars, DEFAULT_ENCODING, UTF_8, MAX_LINE_LENGTH, CHUNK_STEP_SIZE, CHUNK_SIZE, \\\n OVERLAP_SIZE, UTF_16_LE\nfrom credsweeper.utils.util import Util\nfrom tests import AZ_DATA, AZ_STRING, SAMPLES_PATH\n\n\nclass TestUtils(unittest.TestCase):\n KOREAN_PANGRAM = \"키스의 고유조건은 입술끼리 만나야 하고 특별한 기술은 필요치 않다.\"\n DEUTSCH_PANGRAM = \"Üben von Xylophon und Querflöte ist ja zweckmäßig\"\n\n PKCS1 = \"\"\"\n MIIBOgIBAAJBAL1/hJjtuMbjbVXo6wYT1SxiROOvwgffVSvOAk5aN2d4wYTC25k3\n sklfpdwxvkjh4iGB6/qC+0RbmiLwaXaQT0ECAwEAAQJAeAlQyza6t3HVDnhud/kU\n LftJvBjXhfkYkJj8qPlI40dn/Tnwe6mywfly6hOvAn4TRBsnB/Eln6hJLmCrDvZv\n yQIhAPf7Uma4/Aqgoz3SfPyz9TaQXyD5JSC3ej7cOH7b3hgTAiEAw6AYhc/UKh8i\n IAPYGK15ImVmXAlxmhFD6xCWx9bcTdsCIQDiqOayWZaWKCnNEh2H5PzW+LLasp9K\n /ilQV32UBmdD3QIgbafQFzHoO7Q37Lo655pVzHIKbozcoQAMkjc6TcqiswECIBvX\n LFj5jkNs4iSqphZo8eISUdol/9Zo/dkrHC41kbYJ\n \"\"\"\n\n PKCS8 = \"\"\"\n MIIBVAIBADANBgkqhkiG9w0BAQEFAASCAT4wggE6AgEAAkEAvX+EmO24xuNtVejr\n BhPVLGJE46/CB99VK84CTlo3Z3jBhMLbmTeySV+l3DG+SOHiIYHr+oL7RFuaIvBp\n dpBPQQIDAQABAkB4CVDLNrq3cdUOeG53+RQt+0m8GNeF+RiQmPyo+UjjR2f9OfB7\n qbLB+XLqE68CfhNEGycH8SWfqEkuYKsO9m/JAiEA9/tSZrj8CqCjPdJ8/LP1NpBf\n IPklILd6Ptw4ftveGBMCIQDDoBiFz9QqHyIgA9gYrXkiZWZcCXGaEUPrEJbH1txN\n 2wIhAOKo5rJZlpYoKc0SHYfk/Nb4stqyn0r+KVBXfZQGZ0PdAiBtp9AXMeg7tDfs\n ujrnmlXMcgpujNyhAAySNzpNyqKzAQIgG9csWPmOQ2ziJKqmFmjx4hJR2iX/1mj9\n 2SscLjWRtgk=\n \"\"\"\n\n PKCS8_CHANGEME = \"\"\"\n MIIBvTBXBgkqhkiG9w0BBQ0wSjApBgkqhkiG9w0BBQwwHAQIT0gWHcAV1rACAggA\n MAwGCCqGSIb3DQIJBQAwHQYJYIZIAWUDBAEqBBBaZ0qE6fJsz9rDPoa2esruBIIB\n YF9QvKgDLA15MgXR8P73DRdrDJzEEoYe7bDtk+vnTzy6DNVwSfkgQLNLpKfnjPO3\n b1szG5md06Fai6Tuuc9kKDhaCWfGgw/xAeb4OEjWupyCUvmyWYBNqCC+DDQZb7cc\n ka4cuIRV7Ty0I/3AdGCZ/g4mDBozjtfLkLOvWzRuKXQYvGlPYd0HUWupKn2Sgduy\n rwKt43zq0j+t9UXMMFVYv7RZOzZruVcUkBKHoYDkgOl9OQ5tGE+atfhLZUVUKj4Q\n 7F+o6mlTy0JHxv94oUadDXJCyzivdes2RxabPDJ+1gEfNW8ZRZtselC+Pdy+KBIt\n Ln3f3FEWXpWbNPRzhElOUUaNgRNOQrmxoE09QxWLt8L3soArRfWe732Nw7N9izpU\n uKmL72bzbpetDQu/sn49CEnWcFGCZQ9inSiEogF0e2ncxnKfthRKzpT3K5JGiqcM\n mbcMoz5WjLks//PgWcZ/l2o=\n \"\"\"\n\n PKCS12 = \"\"\"\n MIIFNgIBAzCCBOwGCSqGSIb3DQEHAaCCBN0EggTZMIIE1TCCApIGCSqGSIb3DQEHBqCCAoMwggJ/\n AgEAMIICeAYJKoZIhvcNAQcBMFcGCSqGSIb3DQEFDTBKMCkGCSqGSIb3DQEFDDAcBAj/aKWRTdH5\n CwICCAAwDAYIKoZIhvcNAgkFADAdBglghkgBZQMEASoEEMGS8BBALDKdaLIFg5sofxKAggIQCtTT\n Q1PuFM7/QKiTMphxz9RLR+cYwdD/MMZsE4DbNiIt3jMbirbNW+QeEyN6wH+HH2H358pqsN3/8e40\n K0FDHvLsfs8eWkqtmPK4e6MYX/Iz5MxZqMxaJNpSoOmdSJYPJdBUf6X1Cc5r0Fe0j50DNGPYazQS\n Xik2U4v5ekvLIDNm9cRMcLOaF/Nf4qB1wMSrBWCMk75Nm1zllHyIuimCchNe04m3Rmpa2VXVSn3Q\n Zjp5b8QyY5K8Wz15gQAfuQWEu9hrh/qsVpISR2R492BDS3FY7cwvubjGgIxVH7V8B3noch4YENS2\n dlmQMWsJcOuhg8LTrRIyyzLJicP9O3VN9qF6jR++YBxekV56D54KjEeultUdpiD0Eqt3A5vUZyyY\n hWcPEzFEI+CgM7mrvgDHtrRqzr8WHwiuho6tsgrwlhDCvOxcF/cSjBcfwJiB4gJxtlMjCYdEq256\n KBU9Vq3kCKYglF4lwA5F498UZqgojx/t3vzLRGK3qp6ffXVPvcxZGjZjtfDwuY/rxYZfsrcsXdSS\n w8X6OA0AcDzxTFdSuRAdtb/xdA9rj+n4tLFIn1smDBSCAbxC1hcV5XLVfkU+75SjCHY7TjK9bChx\n IhMXJZFmX8JJF+B8PEtzkx/3mn+n/kWiEKPsWIerVVe1LqX/JWlMLucpKnGPKEXTUxmAc3Z8SFI0\n kK0UIp04crqq6DRnMIICOwYJKoZIhvcNAQcBoIICLASCAigwggIkMIICIAYLKoZIhvcNAQwKAQKg\n ggHBMIIBvTBXBgkqhkiG9w0BBQ0wSjApBgkqhkiG9w0BBQwwHAQIan4Jz+bein0CAggAMAwGCCqG\n SIb3DQIJBQAwHQYJYIZIAWUDBAEqBBCulAkqt2DLDD1aGAzE3ik1BIIBYI1yRnH3viudZ1k4tZgr\n ZijphnGvc4nlX8J0ImrH4Dqr90RKT7ZDFQldqr7XHsNwjpR6qGjkGu2xVS40AeBxFBsi5mDNMRcM\n LgZKBQNh8C+CXxkatdvC33hZ2EJ7JzEL3ejdZwzOCvjQpqfxQPLgFFTRQOMZnBXx0nn9QLoJ8HJG\n 8/QJ31aqrhDPEX64s3xhCBa0FLI34AoTpF2nDVTHt+v+1wakFdki4ABC9X0QgCAUYHf7OYZG7b7A\n 7RNYb0LUyX5OEYERi5oUkC4dh9qB250+3CG1mKk1WRpR147XWA25RTsF2/q42anrPR4c1/3DFlE5\n YtHx875SrGwxV9DRJytP6rum+b8nKxv91J7LbUUWBV5qX2cms2itPHSlNg1BhsnYtuMmKo1flIid\n BAhuhpAiCmj8myFTUQ3cJ4lfGNrFz225guZFIPElTxl9S9GmHX3KdUTDb8S8jqfOfFGkTs8xTDAj\n BgkqhkiG9w0BCRUxFgQUGY0PlBhhh6+fjx21HWim3e+syDowJQYJKoZIhvcNAQkUMRgeFgBlAHgA\n YQBtAHAAbABlAC4AYwBvAG0wQTAxMA0GCWCGSAFlAwQCAQUABCBmjoy3EmwmDqVl9ZwnqndJ0Sf3\n M1I223wax4Fje1dkegQIrDjD/AWVwj4CAggA\n \"\"\"\n\n PKCS12_CHANGEME = \"\"\"\n MIIFNgIBAzCCBOwGCSqGSIb3DQEHAaCCBN0EggTZMIIE1TCCApIGCSqGSIb3DQEHBqCCAoMwggJ/\n AgEAMIICeAYJKoZIhvcNAQcBMFcGCSqGSIb3DQEFDTBKMCkGCSqGSIb3DQEFDDAcBAhknVwZ/8XA\n BAICCAAwDAYIKoZIhvcNAgkFADAdBglghkgBZQMEASoEECI9IqqZ3J6xUKkiXcNZCaGAggIQrWgd\n iM7DBZIyAS6mocBSb/giKZLPMq23x1nZNdf4mkjEk2nLjNbtA09n8d/2FxBvFKLQfxZfxtq76Hza\n TlCvVz8PhcGPhHumOXUAzBtT3Mv4WDmub/1pAZsjInN6K+CCQlb7tPLy8OlHHHP5HYET6LXUUy1R\n cslDJNJdb9YDlhjhFOoGgd7fApnFAwsjQDjNVT/DCnuQQHrSylezYZP6HM4Sf7INrdbHviJU/K0A\n c1hBDXrndhaOWEGnaKXknycIZqN0HgftdUjiujPhI0XdIE008U+6hxibTe/Okdn6URlmOtbuXOFQ\n FYO7nAN8wOW2/n1nZSQkZflV7P0+Vq2Ce4tfCUCyj+pJuuKygGA6D4gUoY74N4LGjDHvzjY00f5h\n tdQ3WRAXcuG1zsORsjOhRB8Ag5tKOYCMQF9GMhFQfhZwg07zaZS7dU8fyvIPFYSAynr7Uef6GMkv\n Zyw8DF6dku4X/Jgm/h9b7jb7x289hjowUYVYZ7/+KQPdH2Pj68BrUxtFFc118W1P1FE4huYe11Kf\n RBgGy2NugCCPkExKfQrFPRM32hGd+2AMTrfpVoBkY1Dj4IKwEKIufSTnyvtl+MIMB2cwumD/A/IV\n ksr9qV7ptfwuZl1pzqkZIUAoVgDs8gqul/YOT9g0QWydP/Vwh30v/6RAmwAEUhTydhag2fP5JQgu\n oVQXcHPYgYfIqjf+MIICOwYJKoZIhvcNAQcBoIICLASCAigwggIkMIICIAYLKoZIhvcNAQwKAQKg\n ggHBMIIBvTBXBgkqhkiG9w0BBQ0wSjApBgkqhkiG9w0BBQwwHAQIA0VVM4PAVxMCAggAMAwGCCqG\n SIb3DQIJBQAwHQYJYIZIAWUDBAEqBBA5WjHZFqFYRnvekUsb7V82BIIBYG5T1b/dWIkUslM7f7tm\n Qy4vPlOeFDZv5U437Af9ZfrseIAiPXPXKUsQubwme2PH5cZQYV3AZY/6INPfSrhNw+feHGeSAYRm\n jugB8vEfaTV0Lml6MPi+sn+SaBGLYDNYRv8i4fb+V/cgUMGvVpMMKhDBiGrjjmC4d/R/asEcD3Gh\n JSerfECS1pg/CWckL8l86jwF+DbX90+xe1ReJ4c/64bnQzRbRKTQdu7bIbAuZjfbBd8a3zsRawmH\n 9uIE4RYNN9wHOSarwzKCT5JYMVBHv/tXqpxT12Z9z1sovAATo6JHIJ8x9qvmw3Yv7q20Vt5s/h8O\n 8RiFefJS8hWd0gX85oTpOO2mww0NmbPgH0At2VHPItK5HA4pM5/qPjSp0netZoaKrdJypSbMJfAj\n G99FmZgp3MLQYphYRbM6g7RhWCeW4mM6pvqrk6YKWBsMKPQPnLD25pMfrnjR0LG0FnEClQ8xTDAj\n BgkqhkiG9w0BCRUxFgQUGY0PlBhhh6+fjx21HWim3e+syDowJQYJKoZIhvcNAQkUMRgeFgBlAHgA\n YQBtAHAAbABlAC4AYwBvAG0wQTAxMA0GCWCGSAFlAwQCAQUABCBb+Q7hc25Mh35RU/6qtG8NxT87\n qGEE8yzsqZzIOG9iogQIO3wdxp2pvhECAggA\n \"\"\"\n\n def test_asn1_n(self):\n self.assertEqual(0, Util.get_asn1_size(b'0\\x84\\x01\\x00\\x00\\x00' + b'\\xA5' * (1 << 24 - 1)))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x83\\x01\\x00\\x00' + b'\\xA5' * (65536 - 1)))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x82\\xFF\\xFF' + b'\\xA5' * (65535 - 1)))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x8F' + b'\\xFF' * 200))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x82' + b'\\xFF' * 200))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x81' + b'\\xFF' * 200))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x80' + b'\\xFF' * 200))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x0fabcdef'))\n self.assertEqual(0, Util.get_asn1_size(b'0\\x01'))\n self.assertEqual(0, Util.get_asn1_size(b''))\n based_data = self.PKCS1\n data = Util.decode_base64(based_data)\n self.assertEqual(0, Util.get_asn1_size(data[:-1]))\n\n def test_asn1_p(self):\n self.assertEqual(16777222, Util.get_asn1_size(b'0\\x84\\x01\\x00\\x00\\x00' + b'\\xA5' * (1 << 24)))\n self.assertEqual(65541, Util.get_asn1_size(b'0\\x83\\x01\\x00\\x00' + b'\\xA5' * 65536))\n self.assertEqual(65539, Util.get_asn1_size(b'0\\x82\\xFF\\xFF' + b'\\xA5' * 65535))\n self.assertEqual(4, Util.get_asn1_size(b'0\\x81\\x01abcdef'))\n self.assertEqual(8, Util.get_asn1_size(b'0\\x80abcd\\000\\000'))\n self.assertEqual(3, Util.get_asn1_size(b'0\\x01abcdef'))\n self.assertEqual(2, Util.get_asn1_size(b'0\\x00'))\n data = Util.decode_base64(self.PKCS1)\n self.assertEqual(318, Util.get_asn1_size(data))\n over_data = bytearray(data) + random.randbytes(200)\n self.assertEqual(318, Util.get_asn1_size(over_data))\n\n def test_get_extension_n(self):\n self.assertEqual(\"\", Util.get_extension(None))\n self.assertEqual(\"\", Util.get_extension(\"/\"))\n self.assertEqual(\"\", Util.get_extension(\"/tmp\"))\n self.assertEqual(\"\", Util.get_extension(\"tmp\"))\n self.assertEqual(\"\", Util.get_extension(\"tmp/\"))\n self.assertEqual(\"\", Util.get_extension(\".gitignore\"))\n self.assertEqual(\"\", Util.get_extension(\"/tmp/.hidden\"))\n self.assertEqual(\"\", Util.get_extension(\"/tmp.ext/\"))\n self.assertEqual(\"\", Util.get_extension(\"http://127.0.0.1/index\"))\n\n def test_get_extension_p(self):\n self.assertEqual(\".ext\", Util.get_extension(\"tmp.ext\"))\n self.assertEqual(\".jpg\", Util.get_extension(\"tmp.JPG\"))\n self.assertEqual(\".ї\", Util.get_extension(\"tmp.Ї\", lower=True))\n self.assertEqual(\".Ї\", Util.get_extension(\"tmp.Ї\", lower=False))\n self.assertEqual(\".♡\", Util.get_extension(\"tmp.♡\"))\n self.assertEqual(\".ㅋㅅ\", Util.get_extension(\"tmp.ㅋㅅ\"))\n self.assertEqual(\".ß\", Util.get_extension(\"tmp.ß\"))\n self.assertEqual(\".txt\", Util.get_extension(\"/.hidden.tmp.txt\"))\n\n def test_colon_os_n(self):\n self.assertEqual(\"\", Util.get_extension(\":memory:\"))\n self.assertEqual(\".ext\", Util.get_extension(\"c:\\\\tmp.ext\"))\n self.assertEqual(\".json\", Util.get_extension(\"c:\\\\tmp.ext:zip:text.json\"))\n self.assertEqual(\".json\", Util.get_extension(\"/tmp.ext:zip:text.json\"))\n self.assertEqual(\".json:encoded\", Util.get_extension(\"c:\\\\tmp.ext:zip:text.json:ENCODED\"))\n self.assertEqual(\".json:raw\", Util.get_extension(\"/tmp.ext:zip:text.json:raw\"))\n with tempfile.TemporaryDirectory() as tmp_dir:\n file_name = os.path.join(tmp_dir, \"test_file.zip\")\n Path(file_name).touch()\n assert os.path.exists(file_name)\n new_name = f\"{file_name}:ZIP:dummy.txt\"\n assert not os.path.exists(new_name)\n\n @given(strategies.binary())\n def test_get_shannon_entropy_hypothesis_n(self, data):\n self.assertLessEqual(0.0, Util.get_shannon_entropy(data))\n\n def test_get_shannon_entropy_n(self):\n self.assertEqual(0, Util.get_shannon_entropy(None))\n self.assertEqual(0, Util.get_shannon_entropy(''))\n self.assertEqual(0, Util.get_shannon_entropy('x'))\n self.assertEqual(0, Util.get_shannon_entropy('♡'))\n self.assertEqual(0, Util.get_shannon_entropy(b'\\0'))\n\n def test_get_shannon_entropy_p(self):\n self.assertEqual(1.0, Util.get_shannon_entropy(\"01\"))\n self.assertEqual(1.0, Util.get_shannon_entropy(\"ÖЇ\"))\n self.assertEqual(1.0, Util.get_shannon_entropy(\"ㅋㅅ\"))\n self.assertEqual(4.431965045349459, Util.get_shannon_entropy(AZ_STRING))\n self.assertEqual(4.385453417442482, Util.get_shannon_entropy(AZ_STRING.lower()))\n self.assertEqual(4.385453417442482, Util.get_shannon_entropy(AZ_STRING.upper()))\n self.assertEqual(3.321928094887362, Util.get_shannon_entropy(string.digits))\n self.assertEqual(3.321928094887362, Util.get_shannon_entropy(string.ascii_uppercase[:10]))\n self.assertEqual(6.0, Util.get_shannon_entropy(Chars.BASE64STD_CHARS.value))\n self.assertEqual(6.0, Util.get_shannon_entropy(Chars.BASE64URL_CHARS.value))\n self.assertEqual(6.0223678130284535, Util.get_shannon_entropy(Chars.BASE64URLPAD_CHARS.value))\n self.assertEqual(6.643856189774724, Util.get_shannon_entropy(string.printable))\n self.assertEqual(6.62935662007961, Util.get_shannon_entropy(string.printable[:-1]))\n self.assertEqual(6.62935662007961, Util.get_shannon_entropy(string.printable[1:]))\n\n def test_util_read_file_n(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_file_p.tmp')\n # required binary write mode\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(AZ_DATA)\n assert os.path.isfile(file_path)\n # CP1026 incompatible with ASCII but encodes something\n test_result = Util.read_file(file_path, [1, 'fake', 'undefined', 'utf_16', 'utf_32', 'CP1026'])\n assert 1 == len(test_result)\n assert len(AZ_STRING) == len(test_result[0])\n assert AZ_STRING != test_result[0]\n\n def test_util_read_file_p(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_file_p.tmp')\n # required binary write mode\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(AZ_DATA)\n assert os.path.isfile(file_path)\n # windows might accept oem\n test_result = Util.read_file(file_path, ['oem', 'utf_8'])\n assert 1 == len(test_result)\n assert AZ_STRING == test_result[0]\n\n def test_util_read_utf8_bin_p(self):\n IOOOOOOO = int('10000000', 2)\n IOIIIIII = int('10111111', 2)\n IIOOOOOO = int('11000000', 2)\n IIIOOOOO = int('11100000', 2)\n IIIIOOOO = int('11110000', 2)\n IIIIIOOO = int('11111000', 2)\n bin_text = bytearray()\n n = 65536\n while 0 < n:\n bin_char = bytearray()\n r = random.randint(1, 255)\n if 128 > r:\n bin_char.append(r)\n elif IIOOOOOO == (IIIOOOOO & r):\n bin_char.append(r)\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n elif IIIOOOOO == (IIIIOOOO & r):\n bin_char.append(r)\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n elif IIIIOOOO == (IIIIIOOO & r):\n bin_char.append(r)\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n bin_char.append(random.randint(IOOOOOOO, IOIIIIII))\n else:\n continue\n try:\n utf8_char = bin_char.decode('utf-8')\n encoded_bin = utf8_char.encode('utf-8')\n if bin_char != encoded_bin:\n # print (f\"Wrong refurbish:{utf8_char} {bin_char} {encoded_bin}\")\n continue\n except UnicodeError:\n continue\n # the byte sequence is correct for UTF-8 and is added to data\n bin_text += bin_char\n n -= 1\n\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_utf8_bin_p.tmp')\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(bin_text)\n assert os.path.isfile(file_path)\n read_lines = Util.read_file(file_path)\n decoded_lines = Util.decode_bytes(bin_text)\n assert 0 < len(read_lines)\n assert decoded_lines == read_lines\n\n def test_util_read_utf16le_bin_p(self):\n bin_text = bytearray()\n bin_text += bytes([0xff, 0xfe]) # BOM LE\n n = 65536\n while 0 < n:\n bin_char = bytearray()\n try:\n bin_char.append(random.randint(0, 255))\n bin_char.append(random.randint(0, 255))\n utf16_char = bin_char.decode('utf-16-le')\n encoded_bin = utf16_char.encode('utf-16-le')\n if bin_char != encoded_bin:\n # print (f\"Wrong refurbish:{utf16_char} {bin_char} {encoded_bin}\")\n continue\n except UnicodeError:\n continue\n # the byte sequence is correct for UTF-16-LE and is added to data\n bin_text += bin_char\n n -= 1\n if 0 == n % 32:\n bin_char.append(0x0a)\n bin_char.append(0x00)\n\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_utf16le_bin_p.tmp')\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(bin_text)\n assert os.path.isfile(file_path)\n read_lines = Util.read_file(file_path)\n test_lines = Util.decode_bytes(bin_text)\n assert 0 < len(read_lines)\n assert read_lines == test_lines\n\n def test_util_read_utf16le_txt_p(self):\n unicode_text = \"\"\n n = 65536\n while 0 < n:\n try:\n unicode_char = chr(random.randint(0, 0x10FFFF))\n encoded_bin = unicode_char.encode('utf-16-le')\n utf16_char = encoded_bin.decode('utf-16-le')\n if unicode_char != utf16_char:\n # print(f\"Wrong refurbish:{unicode_char} {encoded_bin} {utf16_char}\")\n continue\n except UnicodeError:\n continue\n # the byte sequence is correct for UTF-16-LE and is added to data\n unicode_text += unicode_char\n n -= 1\n if 0 == n % 32:\n unicode_text += '\\n'\n\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_utf16le_bin_p.tmp')\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(bytes([0xff, 0xfe])) # BOM LE\n tmp_file.write(unicode_text.encode('utf-16-le'))\n assert os.path.isfile(file_path)\n read_lines = Util.read_file(file_path)\n test_lines = Util.decode_bytes(bytes([0xff, 0xfe]) + unicode_text.encode('utf-16-le'))\n assert 0 < len(read_lines)\n assert read_lines == test_lines\n\n def test_util_read_utf16be_txt_p(self):\n unicode_text = \"\"\n n = 65536\n while 0 < n:\n try:\n unicode_char = chr(random.randint(0, 0x10FFFF))\n encoded_bin = unicode_char.encode('utf-16-be')\n utf16_char = encoded_bin.decode('utf-16-be')\n if unicode_char != utf16_char:\n # print (f\"Wrong refurbish:{unicode_char} {encoded_bin} {utf16_char}\")\n continue\n except UnicodeError:\n continue\n # the byte sequence is correct for UTF-16-BE and is added to data\n unicode_text += unicode_char\n n -= 1\n if 0 == n % 32:\n unicode_text += '\\n'\n\n with tempfile.TemporaryDirectory() as tmp_dir:\n assert os.path.isdir(tmp_dir)\n file_path = os.path.join(tmp_dir, 'test_util_read_utf16le_bin_p.tmp')\n with open(file_path, \"wb\") as tmp_file:\n tmp_file.write(bytes([0xfe, 0xff])) # BOM BE\n tmp_file.write(unicode_text.encode('utf-16-be'))\n assert os.path.isfile(file_path)\n read_lines = Util.read_file(file_path, ['utf-16-be', 'undefined'])\n test_bytes = bytes([0xfe, 0xff]) + unicode_text.encode('utf-16-be')\n test_lines = Util.decode_bytes(test_bytes, ['utf-16-be', 'undefined'])\n assert 0 < len(read_lines)\n assert read_lines == test_lines\n\n def test_decode_text_n(self):\n self.assertIsNone(Util.decode_text(None))\n self.assertEqual('', Util.decode_text(b''))\n\n def test_decode_text_p(self):\n self.assertEqual('BE', Util.decode_text(b'\\0B\\0E'))\n self.assertEqual('LE', Util.decode_text(b'L\\0E\\0'))\n self.assertEqual('BE', Util.decode_text(b'\\xFE\\xFF\\0B\\0E'))\n self.assertEqual('LE', Util.decode_text(b'\\xFF\\xFEL\\0E\\0'))\n data = AZ_STRING.encode(\"utf_16\")\n self.assertTrue(data.startswith(b'\\xFF') or data.startswith(b'\\xFE'), data) # platform dependent\n self.assertEqual(AZ_STRING, Util.decode_text(data))\n\n def test_is_binary_n(self):\n with self.assertRaises(AttributeError):\n self.assertFalse(Util.is_binary(None))\n self.assertFalse(Util.is_binary(b''))\n self.assertFalse(Util.is_binary(self.DEUTSCH_PANGRAM.encode(UTF_8)))\n self.assertFalse(Util.is_binary(b\"\\x7Ffew unprintable letters\\x00\"))\n self.assertFalse(Util.is_binary(self.KOREAN_PANGRAM.encode(UTF_8)))\n # some binaries may be false negatives\n self.assertFalse(Util.is_binary(b'!' * MAX_LINE_LENGTH + b\"\\0\\0\\0\\0\"))\n\n def test_is_binary_p(self):\n # two zeroes sequence is a marker of a binary\n self.assertTrue(Util.is_binary(b\"\\0\\0\"))\n self.assertTrue(Util.is_binary(b\"X3\\0\\0\"))\n # unsupported encoding has 3 zeroes\n self.assertTrue(Util.is_binary(AZ_STRING.encode(\"utf_32\")))\n self.assertTrue(Util.is_binary(AZ_STRING.encode(\"utf_32_le\")))\n self.assertTrue(Util.is_binary(AZ_STRING.encode(\"utf_32_be\")))\n\n def test_is_latin1_n(self):\n # standard UTF-16 encoding is not recognized as Latin1\n self.assertFalse(Util.is_latin1(self.DEUTSCH_PANGRAM.encode(UTF_16_LE)))\n # standard UTF-8 encoding is not recognized as Latin1 for Hangul\n self.assertFalse(Util.is_latin1(self.KOREAN_PANGRAM.encode(UTF_8)))\n # random data should be not recognized as Latin1\n self.assertFalse(Util.is_latin1(random.randbytes(MAX_LINE_LENGTH)))\n\n def test_is_latin1_p(self):\n # standard UTF-8 encoding is recognized as Latin1 even with null-terminator\n self.assertTrue(Util.is_latin1((self.DEUTSCH_PANGRAM + '\\0').encode(UTF_8)))\n # obsolete encoding may be recognized as Latin1\n self.assertTrue(Util.is_latin1(self.KOREAN_PANGRAM.encode(\"euc_kr\")))\n # 0x1B ESCAPE code in log\n self.assertTrue(Util.is_latin1(b\"\u001b[94mPASSWORD\u001b[0m\u001b[92m=\u001b[0m\u001b[93m2IWJD88FH4Y\u001b[0m;\"))\n\n def test_is_ascii_entropy_validate_p(self):\n self.assertTrue(Util.is_ascii_entropy_validate(b''))\n self.assertTrue(Util.is_ascii_entropy_validate(AZ_DATA))\n # remove all spaces to make a variable name\n az_data = AZ_DATA.replace(b' ', b'') # 35 bytes\n self.assertTrue(Util.is_ascii_entropy_validate(az_data))\n hangul_pangram_data = self.KOREAN_PANGRAM.encode(UTF_8)\n self.assertTrue(Util.is_ascii_entropy_validate(hangul_pangram_data))\n hanja_data = \"漢字能力檢定試驗\".encode(UTF_8)\n self.assertEqual(24, len(hanja_data))\n self.assertTrue(Util.is_ascii_entropy_validate(hanja_data))\n\n def test_is_ascii_entropy_validate_n(self):\n various_lang_data = \"수도 首都 Hauptstadt\".encode(UTF_8)\n self.assertEqual(24, len(various_lang_data))\n self.assertFalse(Util.is_ascii_entropy_validate(various_lang_data))\n decoded_like_base64 = Util.decode_base64(f\"{AZ_STRING}=\")\n self.assertFalse(Util.is_ascii_entropy_validate(decoded_like_base64))\n for random_data_len in range(16, 40):\n data = random.randbytes(random_data_len)\n # VERY RARELY IT MIGHT FAIL\n self.assertFalse(Util.is_ascii_entropy_validate(data), data)\n\n def test_read_bin_file_n(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n self.assertTrue(os.path.isdir(tmp_dir))\n file_path = os.path.join(tmp_dir, 'test_read_data_p')\n with open(file_path, \"wb\") as f:\n f.write(AZ_DATA)\n data = Util.read_data(file_path)\n self.assertEqual(AZ_DATA, data)\n\n def test_read_data_n(self):\n self.assertIsNone(Util.read_data(os.path.join(\"not\", \"existed\", \"path\")))\n\n @given(strategies.text())\n def test_split_text_n(self, text):\n self.assertLessEqual(0, len(Util.split_text(text)))\n\n def test_get_xml_data_p(self):\n target_path = str(SAMPLES_PATH / \"xml_password.xml\")\n xml_lines = Util.read_data(target_path).decode().splitlines(True)\n result = Util.get_xml_from_lines(xml_lines)\n self.assertEqual(\n (\n [\n \"Countries : \", #\n \"Country : \", #\n \"City : Seoul\", #\n \"password : cackle!\", #\n \"Country : \", #\n \"City : Kyiv\", #\n \"password : peace_for_ukraine\", #\n \"password : Password for authorization\\n\"\n \" BAIT: bace4d59-fa7e-beef-cafe-9129474bcd81\", #\n ],\n [2, 3, 4, 5, 7, 8, 9, 11]),\n result)\n\n def test_get_xml_data_n(self):\n target_path = str(SAMPLES_PATH / \"bad.xml\")\n lines = Util.read_file(target_path)\n with self.assertRaises(XMLSyntaxError):\n Util.get_xml_from_lines(lines)\n\n def test_json_load_p(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n self.assertTrue(os.path.isdir(tmp_dir))\n file_path = os.path.join(tmp_dir, __name__)\n with open(file_path, \"wb\") as f:\n f.write(b'{}')\n data = Util.json_load(file_path)\n self.assertIsInstance(data, dict)\n\n with open(file_path, \"wb\") as f:\n f.write(b'[]')\n data = Util.json_load(file_path)\n self.assertIsInstance(data, list)\n\n with open(file_path, \"wb\") as f:\n f.write(b'\"' + AZ_DATA + b'\"')\n data = Util.json_load(file_path)\n self.assertIsInstance(data, str)\n self.assertEqual(AZ_STRING, data)\n\n rand_int = random.randint(-100, 100)\n with open(file_path, \"wb\") as f:\n f.write(str(rand_int).encode())\n data = Util.json_load(file_path)\n self.assertIsInstance(data, int)\n self.assertEqual(rand_int, data)\n\n rand_float = rand_int / 3.14\n with open(file_path, \"wb\") as f:\n f.write(str(rand_float).encode())\n data = Util.json_load(file_path)\n self.assertIsInstance(data, float)\n self.assertEqual(rand_float, data)\n\n with open(file_path, \"wb\") as f:\n f.write(b'true')\n data = Util.json_load(file_path)\n self.assertIsInstance(data, bool)\n self.assertTrue(data)\n\n with open(file_path, \"wb\") as f:\n f.write(b'null')\n data = Util.json_load(file_path)\n self.assertIsNone(data)\n\n def test_json_load_n(self):\n self.assertIsNone(Util.json_load(\"not_existed_path\"))\n with tempfile.TemporaryDirectory() as tmp_dir:\n self.assertTrue(os.path.isdir(tmp_dir))\n file_path = os.path.join(tmp_dir, __name__)\n with open(file_path, \"wb\") as f:\n f.write(AZ_DATA)\n self.assertIsNone(Util.json_load(file_path))\n\n def test_json_dump_p(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n self.assertTrue(os.path.isdir(tmp_dir))\n file_path = os.path.join(tmp_dir, __name__)\n rand_int = random.randint(-1000000, 1000000)\n test_dict = {\"dummy_int\": rand_int, \"dummy_str\": AZ_STRING}\n Util.json_dump(test_dict, file_path=file_path, indent=None)\n with open(file_path, \"rb\") as f:\n self.assertEqual(\n b'{\"dummy_int\": ' + str(rand_int).encode(DEFAULT_ENCODING) + b', \"dummy_str\": \"' + AZ_DATA + b'\"}',\n f.read())\n Util.json_dump(test_dict, file_path=file_path, encoding='utf-16', indent=None)\n with open(file_path, \"rb\") as f:\n read_data = f.read()\n expected_data = \\\n b'\\xff\\xfe{\\x00\"\\x00d\\x00u\\x00m\\x00m\\x00y\\x00_\\x00i\\x00n\\x00t\\x00\"\\x00:\\x00 \\x00' \\\n + str(rand_int).encode('utf-16')[2:] + \\\n b',\\x00 \\x00\"\\x00d\\x00u\\x00m\\x00m\\x00y\\x00_\\x00s\\x00t\\x00r\\x00\"\\x00:\\x00 \\x00' \\\n b'\"\\x00T\\x00h\\x00e\\x00 \\x00q\\x00u\\x00i\\x00c\\x00k\\x00 \\x00b\\x00r\\x00o\\x00w\\x00n\\x00 \\x00' \\\n b'f\\x00o\\x00x\\x00 \\x00j\\x00u\\x00m\\x00p\\x00s\\x00 \\x00o\\x00v\\x00e\\x00r\\x00 \\x00t\\x00h\\x00e\\x00 ' \\\n b'\\x00l\\x00a\\x00z\\x00y\\x00 \\x00d\\x00o\\x00g\\x00\"\\x00}\\x00'\n self.assertEqual(expected_data, read_data)\n expected_text = f'{{\"dummy_int\": {rand_int}, \"dummy_str\": \"{AZ_STRING}\"}}'\n read_text = read_data.decode(encoding='utf-16')\n self.assertEqual(expected_text, read_text)\n\n def test_json_dump_n(self):\n with tempfile.TemporaryDirectory() as tmp_dir:\n self.assertTrue(os.path.isdir(tmp_dir))\n file_path = os.path.join(tmp_dir, __name__)\n test_bytes = AZ_DATA\n Util.json_dump(test_bytes, file_path=file_path, encoding=DEFAULT_ENCODING)\n with open(file_path, \"rb\") as f:\n self.assertEqual(0, len(f.read()))\n\n def test_parse_py_p(self):\n result = Util.parse_python(\"\"\"password = \\\n \"Hello\" \\\n ' World!'\"\"\")\n self.assertIsInstance(result, list)\n self.assertListEqual([\"password = 'Hello World!'\"], result)\n\n def test_parse_py_n(self):\n # empty\n self.assertFalse(Util.parse_python(\"\"))\n # wrong syntax\n with self.assertRaises(SyntaxError):\n Util.parse_python(\"\"\"\"Hello World!\"\"\"\")\n with self.assertRaises(SyntaxError):\n Util.parse_python(\"\"\"{'wrong': ': '\"\\.\" is syntax warning'}\"\"\")\n\n def test_decode_base64_p(self):\n self.assertTrue(Util.parse_python(\"\"\"regexa=r'\\.'\"\"\"))\n self.assertEqual(AZ_DATA, Util.decode_base64(\"VGhlIHF1aWNrIGJyb3duIGZveCBqdW1wcyBvdmVyIHRoZSBsYXp5IGRvZw==\"))\n self.assertEqual(b\"\\xFF\\xFF\\xFF\", Util.decode_base64(\"////\"))\n self.assertEqual(b\"\\xFB\\xEF\\xBE\", Util.decode_base64(\"++++\"))\n self.assertEqual(b\"\\xFF\\xFF\\xFF\", Util.decode_base64(\"____\", urlsafe_detect=True))\n self.assertEqual(b\"\\xFB\\xEF\\xBE\", Util.decode_base64(\"----\", urlsafe_detect=True))\n self.assertEqual(b\"\\xFF\\xFE\", Util.decode_base64(\"//4\", padding_safe=True))\n self.assertEqual(b\"\\xFF\\xFE\", Util.decode_base64(\"__4\", padding_safe=True, urlsafe_detect=True))\n self.assertEqual(b\"kibana\", Util.decode_base64(\"a2liYW5h=\", padding_safe=True))\n\n def test_decode_base64_n(self):\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"VGhlIHF1aWNrIGJyb3duIGZveCBqdW1wcyBvdmVyIHRoZSBsYXp5IGRvZw\")\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"-_+_-\", padding_safe=True, urlsafe_detect=True)\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"/** ! */\", urlsafe_detect=True)\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"-----BEGIN+++++\", urlsafe_detect=True)\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"____\")\n with self.assertRaises(binascii.Error):\n Util.decode_base64(\"----\")\n\n def test_get_chunks_n(self):\n self.assertGreater(MAX_LINE_LENGTH, CHUNK_SIZE)\n self.assertGreater(CHUNK_SIZE, OVERLAP_SIZE)\n self.assertGreater(CHUNK_STEP_SIZE, OVERLAP_SIZE)\n # wrong cases which should not appear due line length is checked before\n self.assertListEqual([(0, CHUNK_SIZE)], Util.get_chunks(0))\n self.assertListEqual([(0, CHUNK_SIZE)], Util.get_chunks(42))\n self.assertListEqual([(0, CHUNK_SIZE)], Util.get_chunks(CHUNK_STEP_SIZE))\n self.assertListEqual([(0, CHUNK_SIZE), (CHUNK_STEP_SIZE, CHUNK_SIZE)], Util.get_chunks(CHUNK_SIZE))\n self.assertListEqual([(0, CHUNK_SIZE), (CHUNK_STEP_SIZE, MAX_LINE_LENGTH)], Util.get_chunks(MAX_LINE_LENGTH))\n with self.assertRaises(Exception):\n Util.get_chunks(None)\n\n def test_get_chunks_p(self):\n line_length = 42 + MAX_LINE_LENGTH\n self.assertListEqual( #\n [ #\n (0, CHUNK_SIZE), #\n (CHUNK_STEP_SIZE, line_length), #\n ], #\n Util.get_chunks(line_length))\n line_length = 2 * MAX_LINE_LENGTH\n self.assertListEqual( #\n [ #\n (0, CHUNK_SIZE), #\n (1 * CHUNK_STEP_SIZE, CHUNK_SIZE + CHUNK_STEP_SIZE), #\n (2 * CHUNK_STEP_SIZE, CHUNK_SIZE + 2 * CHUNK_STEP_SIZE), #\n (3 * CHUNK_STEP_SIZE, line_length), #\n ], #\n Util.get_chunks(line_length))\n line_length = 3 * MAX_LINE_LENGTH + 42\n self.assertListEqual( #\n [ #\n (0, CHUNK_SIZE), #\n (1 * CHUNK_STEP_SIZE, CHUNK_SIZE + CHUNK_STEP_SIZE), #\n (2 * CHUNK_STEP_SIZE, CHUNK_SIZE + 2 * CHUNK_STEP_SIZE), #\n (3 * CHUNK_STEP_SIZE, CHUNK_SIZE + 3 * CHUNK_STEP_SIZE), #\n (4 * CHUNK_STEP_SIZE, CHUNK_SIZE + 4 * CHUNK_STEP_SIZE), #\n (5 * CHUNK_STEP_SIZE, CHUNK_SIZE + 5 * CHUNK_STEP_SIZE), #\n (6 * CHUNK_STEP_SIZE, line_length), #\n ], #\n Util.get_chunks(line_length))\n\n def test_get_chunks_coverage_n(self):\n line_len = MAX_LINE_LENGTH\n while 7 * MAX_LINE_LENGTH > line_len:\n line_len += random.randint(1, OVERLAP_SIZE)\n data = bytearray(line_len)\n chunks = Util.get_chunks(line_len)\n for start, end in chunks:\n for i in range(start, end):\n data[i] += 1\n self.assertNotIn(0, data)\n # overlapped items should be passed not more than twice\n self.assertGreaterEqual(2, max(data))\n\n def test_subtext_n(self):\n self.assertEqual(\"\", Util.subtext(\"\", 0, 0))\n self.assertEqual(\"\", Util.subtext(' ' * 42, 0, 0))\n\n def test_subtext_p(self):\n self.assertEqual(100, len(string.printable))\n self.assertEqual(\"0123456789abcdefghij\", Util.subtext(string.printable, 10, 10))\n self.assertEqual(\"0123456789abcdefghij\", Util.subtext(string.printable, 9, 10))\n self.assertEqual(\")*+,-./:;<=>?@[\\\\]^_`\", Util.subtext(string.printable, 80, 10))\n self.assertEqual(\"-./:;<=>?@[\\\\]^_`{|}~\", Util.subtext(string.printable, 84, 10))\n self.assertEqual(\"-./:;<=>?@[\\\\]^_`{|}~\", Util.subtext(string.printable, 95, 10))\n self.assertEqual(\"var=value0123456789;\", Util.subtext(\" var=value0123456789; \", 35, 10))\n self.assertEqual(AZ_STRING, Util.subtext(AZ_STRING, len(AZ_STRING) >> 1, 1 + len(AZ_STRING) >> 1))\n self.assertEqual(\"x jump\", Util.subtext(AZ_STRING, len(AZ_STRING) >> 1, 3))\n self.assertEqual(\"ox jumps\", Util.subtext(AZ_STRING, len(AZ_STRING) >> 1, 4))\n self.assertEqual(\"fox jumps\", Util.subtext(AZ_STRING, len(AZ_STRING) >> 1, 5))\n self.assertEqual(\"fox jumps ov\", Util.subtext(AZ_STRING, len(AZ_STRING) >> 1, 6))\n self.assertEqual(\"The quick\", Util.subtext(AZ_STRING, 0, 5))\n self.assertEqual(\"The quick\", Util.subtext(AZ_STRING, 3, 5))\n self.assertEqual(\"fox jumps\", Util.subtext(AZ_STRING, AZ_STRING.find(\"jumps\"), 5))\n self.assertEqual(\"e lazy dog\", Util.subtext(AZ_STRING, len(AZ_STRING) - 2, 5))\n self.assertEqual(\"the lazy dog\", Util.subtext(AZ_STRING, len(AZ_STRING) - 2, 6))\n self.assertEqual(AZ_STRING[:39], Util.subtext(AZ_STRING, 15, 20))\n self.assertEqual(AZ_STRING[-40:], Util.subtext(AZ_STRING, 33, 20))\n\n def test_get_excel_column_name_n(self):\n self.assertFalse(Util.get_excel_column_name(None))\n self.assertFalse(Util.get_excel_column_name(-1))\n self.assertFalse(Util.get_excel_column_name(3.14))\n\n def test_get_excel_column_name_p(self):\n self.assertEqual(\"A\", Util.get_excel_column_name(0))\n self.assertEqual(\"AQ\", Util.get_excel_column_name(42))\n self.assertEqual(\"CS\", Util.get_excel_column_name(96))\n self.assertEqual(\"AAA\", Util.get_excel_column_name(702))\n self.assertEqual(\"XFD\", Util.get_excel_column_name(16383))\n self.assertEqual(\"FXSHRXX\", Util.get_excel_column_name(MAXINT))\n\n def test_load_pk_n(self):\n self.assertIsNone(Util.load_pk(None, None))\n self.assertIsNone(Util.load_pk(b'', None))\n self.assertIsNone(Util.load_pk(b'', b''))\n self.assertIsNone(Util.load_pk(AZ_DATA, None))\n self.assertIsNone(Util.load_pk(AZ_DATA, b''))\n\n def test_load_pk_p(self):\n pkcs1der = Util.decode_base64(self.PKCS1)\n self.assertEqual(\"c12d4fd541ccd981066ad72d953a3e0d\", hashlib.md5(pkcs1der).hexdigest())\n pkcs1pk = Util.load_pk(pkcs1der, None)\n self.assertIsNotNone(pkcs1pk)\n\n pkcs8der = Util.decode_base64(self.PKCS8)\n pkcs8pk = Util.load_pk(pkcs8der, None)\n self.assertIsNotNone(pkcs8pk)\n\n pkcs8changeme = Util.decode_base64(self.PKCS8_CHANGEME)\n pkcs8pk_changeme = Util.load_pk(pkcs8changeme, b'changeme')\n self.assertIsNotNone(pkcs8pk_changeme)\n\n pkcs12der = Util.decode_base64(self.PKCS12)\n pkcs12pk = Util.load_pk(pkcs12der, None)\n self.assertIsNotNone(pkcs12pk)\n\n pkcs12changeme = Util.decode_base64(self.PKCS12_CHANGEME)\n pkcs12pk_changeme = Util.load_pk(pkcs12changeme, b'changeme')\n self.assertIsNotNone(pkcs12pk_changeme)\n\n def test_check_pk_n(self):\n self.assertFalse(Util.check_pk(None))\n\n def test_check_pk_p(self):\n pkcs1der = Util.decode_base64(self.PKCS1)\n self.assertTrue(Util.check_pk(Util.load_pk(pkcs1der)))\n" } ]