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DEPRECATION WARNING
This package has been moved! Please install using pip install zxcvbn.
zxcvbn-python
A realistic password strength estimator.
This is a Python implementation of the library created by the team at Dropbox. The original library, written for JavaScript, can be found here.
While there may be other Python ports available, this one is the most up to date and is recommended by the original developers of zxcvbn at this time.
Features
Tested in Python versions 2.6-2.7, 3.3-3.6
Accepts user data to be added to the dictionaries that are tested against (name, birthdate, etc)
Gives a score to the password, from 0 (terrible) to 4 (great)
Provides feedback on the password and ways to improve it
Returns time estimates on how long it would take to guess the password in different situations
Installation
Install the package using pip: pip install zxcvbn-python
Usage
Pass a password as the first parameter, and a list of user-provided inputs as the user_inputs parameter (optional).
from zxcvbn import zxcvbn
results = zxcvbn('JohnSmith123', user_inputs=['John', 'Smith'])
print(results)
Output:
{ 'password': 'JohnSmith123', 'score': 2, 'guesses': 2567800, 'guesses_log10': 6.409561194521849, 'calc_time': datetime.timedelta(0, 0, 5204) 'feedback': { 'warning': '', 'suggestions': [ 'Add another word or two. Uncommon words are better.', "Capitalization doesn't help very much" ] }, 'crack_times_display': { 'offline_fast_hashing_1e10_per_second': 'less than a second' 'offline_slow_hashing_1e4_per_second': '4 minutes', 'online_no_throttling_10_per_second': '3 days', 'online_throttling_100_per_hour': '3 years', }, 'crack_times_seconds': { 'offline_fast_hashing_1e10_per_second': 0.00025678, 'offline_slow_hashing_1e4_per_second': 256.78 'online_no_throttling_10_per_second': 256780.0, 'online_throttling_100_per_hour': 92440800.0, }, 'sequence': [{ 'matched_word': 'john', 'rank': 2, 'pattern': 'dictionary', 'reversed': False, 'token': 'John', 'l33t': False, 'uppercase_variations': 2, 'i': 0, 'guesses': 50, 'l33t_variations': 1, 'dictionary_name': 'male_names', 'base_guesses': 2, 'guesses_log10': 1.6989700043360185, 'j': 3 }, { 'matched_word': 'smith123', 'rank': 12789, 'pattern': 'dictionary', 'reversed': False, 'token': 'Smith123', 'l33t': False, 'uppercase_variations': 2, 'i': 4, 'guesses': 25578, 'l33t_variations': 1, 'dictionary_name': 'passwords', 'base_guesses': 12789, 'guesses_log10': 4.407866583030775, 'j': 11 }], }
Custom Ranked Dictionaries
In order to support more languages or just add password dictionaries of your own, there is a helper function you may use.
from zxcvbn.matching import add_frequency_lists
add_frequency_lists({
'my_list': ['foo', 'bar'],
'another_list': ['baz']
})
These lists will be added to the current ones, but you can also overwrite the current ones if you wish. The lists you add should be in order of how common the word is used with the most common words appearing first.
CLI
You an also use zxcvbn from the command line:
echo 'password' | zxcvbn --user-input <user-input> | jq
You can also execute the zxcvbn module:
echo 'password' | python -m zxcvbn --user-input <user-input> | jq
Contribute
Report an Issue: https://github.com/dwolfhub/zxcvbn-python/issues
Submit a Pull Request: https://github.com/dwolfhub/zxcvbn-python/pulls
License
The project is licensed under the MIT license.
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