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Repository: dropbox/zxcvbn
Branch: master
Commit: 67c4ece9efc4
Files: 35
Total size: 6.6 MB
Directory structure:
gitextract_dnygf_24/
├── .gitignore
├── .npmignore
├── .travis.yml
├── .zuul.yml
├── LICENSE.txt
├── README.md
├── bower.json
├── data/
│ ├── english_wikipedia.txt
│ ├── female_names.txt
│ ├── male_names.txt
│ ├── passwords.txt
│ ├── surnames.txt
│ └── us_tv_and_film.txt
├── data-scripts/
│ ├── build_frequency_lists.py
│ ├── build_keyboard_adjacency_graphs.py
│ ├── count_us_census.py
│ ├── count_wikipedia.py
│ ├── count_wiktionary.py
│ └── count_xato.coffee
├── demo/
│ ├── demo.coffee
│ ├── index.html
│ ├── jquery.js
│ ├── mustache.js
│ └── require.js
├── dist/
│ └── zxcvbn.js
├── package.json
├── src/
│ ├── adjacency_graphs.coffee
│ ├── feedback.coffee
│ ├── frequency_lists.coffee
│ ├── main.coffee
│ ├── matching.coffee
│ ├── scoring.coffee
│ └── time_estimates.coffee
└── test/
├── test-matching.coffee
└── test-scoring.coffee
================================================
FILE CONTENTS
================================================
================================================
FILE: .gitignore
================================================
*.js
!zxcvbn*.js
!demo/jquery.js
!demo/require.js
!demo/mustache.js
node_modules
lib
*~
*.swp
*.swo
tmux-*.log
================================================
FILE: .npmignore
================================================
.git
.gitignore
bower.json
data
data-scripts
demo
test
================================================
FILE: .travis.yml
================================================
sudo: false
language: node_js
node_js:
- node
script: npm run test
================================================
FILE: .zuul.yml
================================================
ui: tape
browsers:
- name: chrome
version: [36, -2..latest]
- name: safari
version: -2..latest
- name: firefox
version: -2..latest
- name: ie
version: 9..latest
- name: opera
version: -1..latest
- name: android
version: -2..latest
browserify:
- transform: coffeeify
- options:
extensions:
- .coffee
================================================
FILE: LICENSE.txt
================================================
Copyright (c) 2012-2016 Dan Wheeler and Dropbox, Inc.
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
================================================
FILE: README.md
================================================
```
_________________________________________________/\/\___________________
_/\/\/\/\/\__/\/\__/\/\____/\/\/\/\__/\/\__/\/\__/\/\________/\/\/\/\___
_____/\/\______/\/\/\____/\/\________/\/\__/\/\__/\/\/\/\____/\/\__/\/\_
___/\/\________/\/\/\____/\/\__________/\/\/\____/\/\__/\/\__/\/\__/\/\_
_/\/\/\/\/\__/\/\__/\/\____/\/\/\/\______/\______/\/\/\/\____/\/\__/\/\_
________________________________________________________________________
```
[](https://travis-ci.org/dropbox/zxcvbn)
[](https://saucelabs.com/u/dropbox-zxcvbn)
`zxcvbn` is a password strength estimator inspired by password crackers. Through pattern matching and conservative estimation, it recognizes and weighs 30k common passwords, common names and surnames according to US census data, popular English words from Wikipedia and US television and movies, and other common patterns like dates, repeats (`aaa`), sequences (`abcd`), keyboard patterns (`qwertyuiop`), and l33t speak.
Consider using zxcvbn as an algorithmic alternative to password composition policy — it is more secure, flexible, and usable when sites require a minimal complexity score in place of annoying rules like "passwords must contain three of {lower, upper, numbers, symbols}".
* __More secure__: policies often fail both ways, allowing weak passwords (`P@ssword1`) and disallowing strong passwords.
* __More flexible__: zxcvbn allows many password styles to flourish so long as it detects sufficient complexity — passphrases are rated highly given enough uncommon words, keyboard patterns are ranked based on length and number of turns, and capitalization adds more complexity when it's unpredictaBle.
* __More usable__: zxcvbn is designed to power simple, rule-free interfaces that give instant feedback. In addition to strength estimation, zxcvbn includes minimal, targeted verbal feedback that can help guide users towards less guessable passwords.
For further detail and motivation, please refer to the USENIX Security '16 [paper and presentation](https://www.usenix.org/conference/usenixsecurity16/technical-sessions/presentation/wheeler).
At Dropbox we use zxcvbn ([Release notes](https://github.com/dropbox/zxcvbn/releases)) on our web, desktop, iOS and Android clients. If JavaScript doesn't work for you, others have graciously ported the library to these languages:
* [`zxcvbn-python`](https://github.com/dwolfhub/zxcvbn-python) (Python)
* [`zxcvbn-cpp`](https://github.com/rianhunter/zxcvbn-cpp) (C/C++/Python/JS)
* [`zxcvbn-c`](https://github.com/tsyrogit/zxcvbn-c) (C/C++)
* [`zxcvbn-rs`](https://github.com/shssoichiro/zxcvbn-rs) (Rust)
* [`zxcvbn-go`](https://github.com/nbutton23/zxcvbn-go) (Go)
* [`zxcvbn4j`](https://github.com/nulab/zxcvbn4j) (Java)
* [`nbvcxz`](https://github.com/GoSimpleLLC/nbvcxz) (Java)
* [`zxcvbn-ruby`](https://github.com/envato/zxcvbn-ruby) (Ruby)
* [`zxcvbn-js`](https://github.com/bitzesty/zxcvbn-js) (Ruby [via ExecJS])
* [`zxcvbn-ios`](https://github.com/dropbox/zxcvbn-ios) (Objective-C)
* [`zxcvbn-cs`](https://github.com/mickford/zxcvbn-cs) (C#/.NET)
* [`szxcvbn`](https://github.com/tekul/szxcvbn) (Scala)
* [`zxcvbn-php`](https://github.com/bjeavons/zxcvbn-php) (PHP)
* [`zxcvbn-api`](https://github.com/wcjr/zxcvbn-api) (REST)
* [`ocaml-zxcvbn`](https://github.com/cryptosense/ocaml-zxcvbn) (OCaml bindings for `zxcvbn-c`)
Integrations with other frameworks:
* [`angular-zxcvbn`](https://github.com/ghostbar/angular-zxcvbn) (AngularJS)
# Installation
zxcvbn detects and supports CommonJS (node, browserify) and AMD (RequireJS). In the absence of those, it adds a single function `zxcvbn()` to the global namespace.
## Bower
Install [`node`](https://nodejs.org/download/) and [`bower`](http://bower.io/) if you haven't already.
Get `zxcvbn`:
``` shell
cd /path/to/project/root
bower install zxcvbn
```
Add this script to your `index.html`:
``` html
<script src="bower_components/zxcvbn/dist/zxcvbn.js">
</script>
```
To make sure it loaded properly, open in a browser and type `zxcvbn('Tr0ub4dour&3')` into the console.
To pull in updates and bug fixes:
``` shell
bower update zxcvbn
```
## Node / npm / MeteorJS
zxcvbn works identically on the server.
``` shell
$ npm install zxcvbn
$ node
> var zxcvbn = require('zxcvbn');
> zxcvbn('Tr0ub4dour&3');
```
## RequireJS
Add [`zxcvbn.js`](https://raw.githubusercontent.com/dropbox/zxcvbn/master/dist/zxcvbn.js) to your project (using bower, npm or direct download) and import as usual:
``` javascript
requirejs(["relpath/to/zxcvbn"], function (zxcvbn) {
console.log(zxcvbn('Tr0ub4dour&3'));
});
```
## Browserify / Webpack
If you're using `npm` and have `require('zxcvbn')` somewhere in your code, browserify and webpack should just work.
``` shell
$ npm install zxcvbn
$ echo "console.log(require('zxcvbn'))" > mymodule.js
$ browserify mymodule.js > browserify_bundle.js
$ webpack mymodule.js webpack_bundle.js
```
But we recommend against bundling zxcvbn via tools like browserify and webpack, for three reasons:
* Minified and gzipped, zxcvbn is still several hundred kilobytes. (Significantly grows bundle size.)
* Most sites will only need zxcvbn on a few pages (registration, password reset).
* Most sites won't need `zxcvbn()` immediately upon page load; since `zxcvbn()` is typically called in response to user events like filling in a password, there's ample time to fetch `zxcvbn.js` after initial html/css/js loads and renders.
See the [performance](#perf) section below for tips on loading zxcvbn stand-alone.
Tangentially, if you want to build your own standalone, consider tweaking the browserify pipeline used to generate `dist/zxcvbn.js`:
``` shell
$ browserify --debug --standalone zxcvbn \
-t coffeeify --extension='.coffee' \
-t uglifyify \
src/main.coffee | exorcist dist/zxcvbn.js.map >| dist/zxcvbn.js
```
* `--debug` adds an inline source map to the bundle. `exorcist` pulls it out into `dist/zxcvbn.js.map`.
* `--standalone zxcvbn` exports a global `zxcvbn` when CommonJS/AMD isn't detected.
* `-t coffeeify --extension='.coffee'` compiles `.coffee` to `.js` before bundling. This is convenient as it allows `.js` modules to import from `.coffee` modules and vice-versa. Instead of this transform, one could also compile everything to `.js` first (`npm run prepublish`) and point `browserify` to `lib` instead of `src`.
* `-t uglifyify` minifies the bundle through UglifyJS, maintaining proper source mapping.
## Manual installation
Download [zxcvbn.js](https://raw.githubusercontent.com/dropbox/zxcvbn/master/dist/zxcvbn.js).
Add to your .html:
``` html
<script type="text/javascript" src="path/to/zxcvbn.js"></script>
```
# Usage
[try zxcvbn interactively](https://lowe.github.io/tryzxcvbn/) to see these docs in action.
``` javascript
zxcvbn(password, user_inputs=[])
```
`zxcvbn()` takes one required argument, a password, and returns a result object with several properties:
``` coffee
result.guesses # estimated guesses needed to crack password
result.guesses_log10 # order of magnitude of result.guesses
result.crack_times_seconds # dictionary of back-of-the-envelope crack time
# estimations, in seconds, based on a few scenarios:
{
# online attack on a service that ratelimits password auth attempts.
online_throttling_100_per_hour
# online attack on a service that doesn't ratelimit,
# or where an attacker has outsmarted ratelimiting.
online_no_throttling_10_per_second
# offline attack. assumes multiple attackers,
# proper user-unique salting, and a slow hash function
# w/ moderate work factor, such as bcrypt, scrypt, PBKDF2.
offline_slow_hashing_1e4_per_second
# offline attack with user-unique salting but a fast hash
# function like SHA-1, SHA-256 or MD5. A wide range of
# reasonable numbers anywhere from one billion - one trillion
# guesses per second, depending on number of cores and machines.
# ballparking at 10B/sec.
offline_fast_hashing_1e10_per_second
}
result.crack_times_display # same keys as result.crack_times_seconds,
# with friendlier display string values:
# "less than a second", "3 hours", "centuries", etc.
result.score # Integer from 0-4 (useful for implementing a strength bar)
0 # too guessable: risky password. (guesses < 10^3)
1 # very guessable: protection from throttled online attacks. (guesses < 10^6)
2 # somewhat guessable: protection from unthrottled online attacks. (guesses < 10^8)
3 # safely unguessable: moderate protection from offline slow-hash scenario. (guesses < 10^10)
4 # very unguessable: strong protection from offline slow-hash scenario. (guesses >= 10^10)
result.feedback # verbal feedback to help choose better passwords. set when score <= 2.
result.feedback.warning # explains what's wrong, eg. 'this is a top-10 common password'.
# not always set -- sometimes an empty string
result.feedback.suggestions # a possibly-empty list of suggestions to help choose a less
# guessable password. eg. 'Add another word or two'
result.sequence # the list of patterns that zxcvbn based the
# guess calculation on.
result.calc_time # how long it took zxcvbn to calculate an answer,
# in milliseconds.
````
The optional `user_inputs` argument is an array of strings that zxcvbn will treat as an extra dictionary. This can be whatever list of strings you like, but is meant for user inputs from other fields of the form, like name and email. That way a password that includes a user's personal information can be heavily penalized. This list is also good for site-specific vocabulary — Acme Brick Co. might want to include ['acme', 'brick', 'acmebrick', etc].
# <a name="perf"></a>Performance
## runtime latency
zxcvbn operates below human perception of delay for most input: ~5-20ms for ~25 char passwords on modern browsers/CPUs, ~100ms for passwords around 100 characters. To bound runtime latency for really long passwords, consider sending `zxcvbn()` only the first 100 characters or so of user input.
## script load latency
`zxcvbn.js` bundled and minified is about 400kB gzipped or 820kB uncompressed, most of which is dictionaries. Consider these tips if you're noticing page load latency on your site.
* Make sure your server is configured to compress static assets for browsers that support it. ([nginx tutorial](https://rtcamp.com/tutorials/nginx/enable-gzip/), [Apache/IIS tutorial](http://betterexplained.com/articles/how-to-optimize-your-site-with-gzip-compression/).)
Then try one of these alternatives:
1. Put your `<script src="zxcvbn.js">` tag at the end of your html, just before the closing `</body>` tag. This ensures your page loads and renders before the browser fetches and loads `zxcvbn.js`. The downside with this approach is `zxcvbn()` becomes available later than had it been included in `<head>` — not an issue on most signup pages where users are filling out other fields first.
2. If you're using RequireJS, try loading `zxcvbn.js` separately from your main bundle. Something to watch out for: if `zxcvbn.js` is required inside a keyboard handler waiting for user input, the entire script might be loaded only after the user presses their first key, creating nasty latency. Avoid this by calling your handler once upon page load, independent of user input, such that the `requirejs()` call runs earlier.
3. Use the HTML5 [`async`](http://www.w3schools.com/tags/att_script_async.asp) script attribute. Downside: [doesn't work](http://caniuse.com/#feat=script-async) in IE7-9 or Opera Mini.
4. Include an inline `<script>` in `<head>` that asynchronously loads `zxcvbn.js` in the background. Advantage over (3): it works in older browsers.
``` javascript
// cross-browser asynchronous script loading for zxcvbn.
// adapted from http://friendlybit.com/js/lazy-loading-asyncronous-javascript/
(function() {
var ZXCVBN_SRC = 'path/to/zxcvbn.js';
var async_load = function() {
var first, s;
s = document.createElement('script');
s.src = ZXCVBN_SRC;
s.type = 'text/javascript';
s.async = true;
first = document.getElementsByTagName('script')[0];
return first.parentNode.insertBefore(s, first);
};
if (window.attachEvent != null) {
window.attachEvent('onload', async_load);
} else {
window.addEventListener('load', async_load, false);
}
}).call(this);
```
# Development
Bug reports and pull requests welcome!
``` shell
git clone https://github.com/dropbox/zxcvbn.git
```
zxcvbn is built with CoffeeScript, browserify, and uglify-js. CoffeeScript source lives in `src`, which gets compiled, bundled and minified into `dist/zxcvbn.js`.
``` shell
npm run build # builds dist/zxcvbn.js
npm run watch # same, but quickly rebuilds as changes are made in src.
```
For debugging, both `build` and `watch` output an external source map `dist/zxcvbn.js.map` that points back to the original CoffeeScript code.
Two source files, `adjacency_graphs.coffee` and `frequency_lists.coffee`, are generated by python scripts in `data-scripts` that read raw data from the `data` directory.
For node developers, in addition to `dist`, the zxcvbn `npm` module includes a `lib` directory (hidden from git) that includes one compiled `.js` and `.js.map` file for every `.coffee` in `src`. See `prepublish` in `package.json` to learn more.
# Acknowledgments
[Dropbox](https://dropbox.com) for supporting open source!
Mark Burnett for releasing his 10M password corpus and for his 2005 book, [Perfect Passwords: Selection, Protection, Authentication](http://www.amazon.com/Perfect-Passwords-Selection-Protection-Authentication/dp/1597490415).
Wiktionary contributors for building a [frequency list of English words](http://en.wiktionary.org/wiki/Wiktionary:Frequency_lists) as used in television and movies.
Researchers at Concordia University for [studying password estimation rigorously](http://www.concordia.ca/cunews/main/stories/2015/03/25/does-your-password-pass-muster.html) and recommending zxcvbn.
And [xkcd](https://xkcd.com/936/) for the inspiration :+1::horse::battery::heart:
================================================
FILE: bower.json
================================================
{
"name": "zxcvbn",
"description": "realistic password strength estimation",
"main": "dist/zxcvbn.js",
"keywords": [
"password",
"passphrase",
"strength",
"quality",
"estimation",
"estimate",
"meter",
"pattern",
"matcher",
"security",
"authentication",
"cracking",
"scoring",
"entropy",
"bruteforce"
],
"ignore": [
"/.*",
"*.json",
"node_modules",
"data",
"data-scripts",
"demo",
"lib",
"src",
"test"
]
}
================================================
FILE: data/english_wikipedia.txt
================================================
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momentum 1
gitextract_dnygf_24/
├── .gitignore
├── .npmignore
├── .travis.yml
├── .zuul.yml
├── LICENSE.txt
├── README.md
├── bower.json
├── data/
│ ├── english_wikipedia.txt
│ ├── female_names.txt
│ ├── male_names.txt
│ ├── passwords.txt
│ ├── surnames.txt
│ └── us_tv_and_film.txt
├── data-scripts/
│ ├── build_frequency_lists.py
│ ├── build_keyboard_adjacency_graphs.py
│ ├── count_us_census.py
│ ├── count_wikipedia.py
│ ├── count_wiktionary.py
│ └── count_xato.coffee
├── demo/
│ ├── demo.coffee
│ ├── index.html
│ ├── jquery.js
│ ├── mustache.js
│ └── require.js
├── dist/
│ └── zxcvbn.js
├── package.json
├── src/
│ ├── adjacency_graphs.coffee
│ ├── feedback.coffee
│ ├── frequency_lists.coffee
│ ├── main.coffee
│ ├── matching.coffee
│ ├── scoring.coffee
│ └── time_estimates.coffee
└── test/
├── test-matching.coffee
└── test-scoring.coffee
SYMBOL INDEX (98 symbols across 9 files)
FILE: data-scripts/build_frequency_lists.py
function usage (line 9) | def usage():
function parse_frequency_lists (line 41) | def parse_frequency_lists(data_dir):
function is_rare_and_short (line 62) | def is_rare_and_short(token, rank):
function has_comma_or_double_quote (line 65) | def has_comma_or_double_quote(token, rank, lst_name):
function filter_frequency_lists (line 74) | def filter_frequency_lists(freq_lists):
function to_kv (line 119) | def to_kv(lst, lst_name):
function main (line 123) | def main():
FILE: data-scripts/build_keyboard_adjacency_graphs.py
function usage (line 5) | def usage():
function get_slanted_adjacent_coords (line 43) | def get_slanted_adjacent_coords(x, y):
function get_aligned_adjacent_coords (line 52) | def get_aligned_adjacent_coords(x, y):
function build_graph (line 58) | def build_graph(layout_str, slanted):
FILE: data-scripts/count_us_census.py
function usage (line 5) | def usage():
function main (line 23) | def main(input_filename, output_filename):
FILE: data-scripts/count_wikipedia.py
function usage (line 14) | def usage():
class TopTokenCounter (line 59) | class TopTokenCounter(object):
method __init__ (line 60) | def __init__(self):
method add_tokens (line 65) | def add_tokens(self, tokens, split_hyphens=True):
method add_token (line 74) | def add_token(self, token):
method should_include (line 86) | def should_include(self, token):
method normalize (line 103) | def normalize(self, token):
method batch_prune (line 106) | def batch_prune(self):
method pre_sort_prune (line 111) | def pre_sort_prune(self):
method get_sorted_pairs (line 120) | def get_sorted_pairs(self):
method get_ts (line 123) | def get_ts(self):
method get_stats (line 126) | def get_stats(self):
function main (line 130) | def main(input_dir_str, output_filename):
FILE: data-scripts/count_wiktionary.py
function usage (line 10) | def usage():
function parse_wiki_tokens (line 29) | def parse_wiki_tokens(html_doc_str):
function normalize (line 61) | def normalize(token):
function main (line 64) | def main(wiktionary_html_root, output_filename):
FILE: demo/jquery.js
function jQuerySub (line 871) | function jQuerySub( selector, context ) {
function doScrollCheck (line 937) | function doScrollCheck() {
function createFlags (line 964) | function createFlags( flags ) {
function resolveFunc (line 1296) | function resolveFunc( i ) {
function progressFunc (line 1304) | function progressFunc( i ) {
function dataAttr (line 1931) | function dataAttr( elem, key, data ) {
function isEmptyDataObject (line 1962) | function isEmptyDataObject( obj ) {
function handleQueueMarkDefer (line 1980) | function handleQueueMarkDefer( elem, type, src ) {
function resolve (line 2133) | function resolve() {
function returnFalse (line 3465) | function returnFalse() {
function returnTrue (line 3468) | function returnTrue() {
function dirNodeCheck (line 5168) | function dirNodeCheck( dir, cur, doneName, checkSet, nodeCheck, isXML ) {
function dirCheck (line 5201) | function dirCheck( dir, cur, doneName, checkSet, nodeCheck, isXML ) {
function isDisconnected (line 5474) | function isDisconnected( node ) {
function winnow (line 5591) | function winnow( elements, qualifier, keep ) {
function createSafeFragment (line 5628) | function createSafeFragment( document ) {
function root (line 5992) | function root( elem, cur ) {
function cloneCopyEvent (line 5999) | function cloneCopyEvent( src, dest ) {
function cloneFixAttributes (line 6027) | function cloneFixAttributes( src, dest ) {
function getAll (line 6163) | function getAll( elem ) {
function fixDefaultChecked (line 6176) | function fixDefaultChecked( elem ) {
function findInputs (line 6182) | function findInputs( elem ) {
function shimCloneNode (line 6193) | function shimCloneNode( elem ) {
function evalScript (line 6425) | function evalScript( i, elem ) {
function getWH (line 6767) | function getWH( elem, name, extra ) {
function addToPrefiltersOrTransports (line 6895) | function addToPrefiltersOrTransports( structure ) {
function inspectPrefiltersOrTransports (line 6931) | function inspectPrefiltersOrTransports( structure, options, originalOpti...
function ajaxExtend (line 6973) | function ajaxExtend( target, src ) {
function done (line 7315) | function done( status, nativeStatusText, responses, headers ) {
function buildParams (line 7630) | function buildParams( prefix, obj, traditional, add ) {
function ajaxHandleResponses (line 7680) | function ajaxHandleResponses( s, jqXHR, responses ) {
function ajaxConvert (line 7745) | function ajaxConvert( s, response ) {
function createStandardXHR (line 8011) | function createStandardXHR() {
function createActiveXHR (line 8017) | function createActiveXHR() {
function doAnimation (line 8349) | function doAnimation() {
function stopQueue (line 8492) | function stopQueue( elem, data, index ) {
function createFxNow (line 8534) | function createFxNow() {
function clearFxNow (line 8539) | function clearFxNow() {
function genFx (line 8544) | function genFx( type, num ) {
function t (line 8659) | function t( gotoEnd ) {
function defaultDisplay (line 8851) | function defaultDisplay( nodeName ) {
function getWindow (line 9160) | function getWindow( elem ) {
FILE: demo/mustache.js
function isWhitespace (line 57) | function isWhitespace(string) {
function escapeHTML (line 92) | function escapeHTML(string) {
function debug (line 102) | function debug(e, template, line, file) {
function lookup (line 127) | function lookup(name, stack, defaultValue) {
function renderSection (line 170) | function renderSection(name, stack, callback, inverted) {
function parse (line 218) | function parse(template, options) {
function _compile (line 471) | function _compile(template, options) {
function clearCache (line 498) | function clearCache() {
function compile (line 511) | function compile(template, options) {
function render (line 532) | function render(template, view, partials) {
FILE: demo/require.js
function isFunction (line 41) | function isFunction(it) {
function isArray (line 45) | function isArray(it) {
function each (line 53) | function each(ary, func) {
function eachReverse (line 68) | function eachReverse(ary, func) {
function hasProp (line 79) | function hasProp(obj, prop) {
function getOwn (line 83) | function getOwn(obj, prop) {
function eachProp (line 92) | function eachProp(obj, func) {
function mixin (line 107) | function mixin(target, source, force, deepStringMixin) {
function bind (line 130) | function bind(obj, fn) {
function scripts (line 136) | function scripts() {
function defaultOnError (line 140) | function defaultOnError(err) {
function getGlobal (line 146) | function getGlobal(value) {
function makeError (line 165) | function makeError(id, msg, err, requireModules) {
function newContext (line 197) | function newContext(contextName) {
function getInteractiveScript (line 1942) | function getInteractiveScript() {
FILE: dist/zxcvbn.js
function s (line 1) | function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&re...
Condensed preview — 35 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (7,277K chars).
[
{
"path": ".gitignore",
"chars": 111,
"preview": "*.js\n!zxcvbn*.js\n!demo/jquery.js\n!demo/require.js\n!demo/mustache.js\nnode_modules\nlib\n*~\n*.swp\n*.swo\ntmux-*.log\n"
},
{
"path": ".npmignore",
"chars": 56,
"preview": ".git\n.gitignore\nbower.json\ndata\ndata-scripts\ndemo\ntest\n\n"
},
{
"path": ".travis.yml",
"chars": 69,
"preview": "sudo: false\nlanguage: node_js\nnode_js:\n - node\nscript: npm run test\n"
},
{
"path": ".zuul.yml",
"chars": 381,
"preview": "ui: tape\nbrowsers:\n - name: chrome\n version: [36, -2..latest]\n - name: safari\n version: -2..latest\n -"
},
{
"path": "LICENSE.txt",
"chars": 1078,
"preview": "Copyright (c) 2012-2016 Dan Wheeler and Dropbox, Inc.\n\nPermission is hereby granted, free of charge, to any person obtai"
},
{
"path": "README.md",
"chars": 14368,
"preview": "```\n_________________________________________________/\\/\\___________________\n_/\\/\\/\\/\\/\\__/\\/\\__/\\/\\____/\\/\\/\\/\\__/\\/\\__"
},
{
"path": "bower.json",
"chars": 629,
"preview": "{\n \"name\": \"zxcvbn\",\n \"description\": \"realistic password strength estimation\",\n \"main\": \"dist/zxcvbn.js\",\n \""
},
{
"path": "data/english_wikipedia.txt",
"chars": 2362171,
"preview": "the 124933855\nof 59700086\nand 51078530\nin 50589567\nto "
},
{
"path": "data/female_names.txt",
"chars": 30042,
"preview": "mary\npatricia\nlinda\nbarbara\nelizabeth\njennifer\nmaria\nsusan\nmargaret\ndorothy\nlisa\nnancy\nkaren\nbetty\nhelen\nsandra\ndonna\nca"
},
{
"path": "data/male_names.txt",
"chars": 8193,
"preview": "james\njohn\nrobert\nmichael\nwilliam\ndavid\nrichard\ncharles\njoseph\nthomas\nchristopher\ndaniel\npaul\nmark\ndonald\ngeorge\nkenneth"
},
{
"path": "data/passwords.txt",
"chars": 898311,
"preview": "123456 55893\npassword 20785\n12345678 13582\nqwerty 13230\n123456789 11696\n12345 "
},
{
"path": "data/surnames.txt",
"chars": 695422,
"preview": "smith\njohnson\nwilliams\njones\nbrown\ndavis\nmiller\nwilson\nmoore\ntaylor\nanderson\nthomas\njackson\nwhite\nharris\nmartin\nthompson"
},
{
"path": "data/us_tv_and_film.txt",
"chars": 861544,
"preview": "you 1222421\ni 1052546\nto 823661\nthe 770161\na "
},
{
"path": "data-scripts/build_frequency_lists.py",
"chars": 5704,
"preview": "#!/usr/bin/python\nimport os\nimport sys\nimport time\nimport codecs\n\nfrom operator import itemgetter\n\ndef usage():\n retu"
},
{
"path": "data-scripts/build_keyboard_adjacency_graphs.py",
"chars": 4051,
"preview": "#!/usr/bin/python\nimport sys\nimport simplejson\n\ndef usage():\n return '''\nconstructs adjacency_graphs.coffee from QWER"
},
{
"path": "data-scripts/count_us_census.py",
"chars": 913,
"preview": "#!/usr/bin/python\nimport sys\nimport codecs\n\ndef usage():\n return '''\nThis script converts surname/name data from the "
},
{
"path": "data-scripts/count_wikipedia.py",
"chars": 5605,
"preview": "#!/usr/bin/python\n\nimport sys\nimport os\nimport re\nimport codecs\nimport operator\nimport datetime\nimport nltk\nimport warni"
},
{
"path": "data-scripts/count_wiktionary.py",
"chars": 2670,
"preview": "#!/usr/bin/python\n\nimport os\nimport sys\nimport codecs\nimport operator\n\nfrom unidecode import unidecode\n\ndef usage():\n "
},
{
"path": "data-scripts/count_xato.coffee",
"chars": 4263,
"preview": "matching = require '../lib/matching'\nscoring = require '../lib/scoring'\n\nfs = require 'fs'\nbyline = require 'byline'\nspr"
},
{
"path": "demo/demo.coffee",
"chars": 6430,
"preview": "\ntest_passwords = '''\nzxcvbn\nqwER43@!\nTr0ub4dour&3\ncorrecthorsebatterystaple\ncoRrecth0rseba++ery9.23.2007staple$\n\np@sswo"
},
{
"path": "demo/index.html",
"chars": 1136,
"preview": "<html>\n <head>\n <title>zxcvbn tests</title>\n\n <script type=\"text/javascript\" src=\"jquery.js\">\n </script>\n <"
},
{
"path": "demo/jquery.js",
"chars": 248235,
"preview": "/*!\n * jQuery JavaScript Library v1.7.1\n * http://jquery.com/\n *\n * Copyright 2011, John Resig\n * Dual licensed under th"
},
{
"path": "demo/mustache.js",
"chars": 14513,
"preview": "/*!\n * mustache.js - Logic-less {{mustache}} templates with JavaScript\n * http://github.com/janl/mustache.js\n */\nvar Mus"
},
{
"path": "demo/require.js",
"chars": 83715,
"preview": "/** vim: et:ts=4:sw=4:sts=4\n * @license RequireJS 2.1.18 Copyright (c) 2010-2015, The Dojo Foundation All Rights Reserve"
},
{
"path": "dist/zxcvbn.js",
"chars": 821792,
"preview": "(function(f){if(typeof exports===\"object\"&&typeof module!==\"undefined\"){module.exports=f()}else if(typeof define===\"func"
},
{
"path": "package.json",
"chars": 1570,
"preview": "{\n \"name\": \"zxcvbn\",\n \"version\": \"4.4.2\",\n \"description\": \"realistic password strength estimation\",\n \"author\": \"Dan "
},
{
"path": "src/adjacency_graphs.coffee",
"chars": 9814,
"preview": "# generated by scripts/build_keyboard_adjacency_graphs.py\nadjacency_graphs = \n qwerty: {\"!\": [\"`~\", null, null, \"2@\", \""
},
{
"path": "src/feedback.coffee",
"chars": 3866,
"preview": "scoring = require('./scoring')\n\nfeedback =\n default_feedback:\n warning: ''\n suggestions: [\n \"Use a few words"
},
{
"path": "src/frequency_lists.coffee",
"chars": 792967,
"preview": "# generated by build_frequency_lists.py\nfrequency_lists = \n passwords: \"123456,password,12345678,qwerty,123456789,12345"
},
{
"path": "src/main.coffee",
"chars": 899,
"preview": "matching = require './matching'\nscoring = require './scoring'\ntime_estimates = require './time_estimates'\nfeedback = req"
},
{
"path": "src/matching.coffee",
"chars": 20883,
"preview": "frequency_lists = require('./frequency_lists')\nadjacency_graphs = require('./adjacency_graphs')\nscoring = require('./sco"
},
{
"path": "src/scoring.coffee",
"chars": 14583,
"preview": "adjacency_graphs = require('./adjacency_graphs')\n\n# on qwerty, 'g' has degree 6, being adjacent to 'ftyhbv'. '\\' has deg"
},
{
"path": "src/time_estimates.coffee",
"chars": 2204,
"preview": "time_estimates =\n estimate_attack_times: (guesses) ->\n crack_times_seconds =\n online_throttling_100_per_hour: g"
},
{
"path": "test/test-matching.coffee",
"chars": 19059,
"preview": "test = require 'tape'\nmatching = require '../src/matching'\nadjacency_graphs = require '../src/adjacency_graphs'\n\n# takes"
},
{
"path": "test/test-scoring.coffee",
"chars": 12544,
"preview": "test = require 'tape'\nscoring = require '../src/scoring'\nmatching = require '../src/matching'\n\nlog2 = scoring.log2\nlog10"
}
]
About this extraction
This page contains the full source code of the dropbox/zxcvbn GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 35 files (6.6 MB), approximately 1.7M tokens, and a symbol index with 98 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.