Password research often requires modelling password distributions from a password leak. (I have to rewrite similar code for at least four times for different projects.) Hence, this module!
In this module I plan to add those models, such as n-gram and PCFG. In current version it supports,
n-gram or Markovian password model- Weir et al. PCFG, and
- simple histogram of the passwords.
$ pip install git+https://github.com/rchatterjee/pwmodels.gitfrom pwmodel import NGramPw, PcfgPw, HistPw
pwm = NGramPw(pwfilename='/Users/badger/passwords/myspace-withcount.tar.bz2', n=4)
print pwm.prob('passwords123')1.0.0
- Add a function to enable the models to churn out passwords in decreasing order of their probability
- Add better pcfg model, especially updated with keyboard sequence, and repeating characters, more natural way of spliting the password than just based on continuous sequence of letters, digits and symbols.
n-gram model is pretty slow now, because it has to comppute the sum of frequency of all the passwords that start withSTART(which is all).