Guess calculator framework
The guess calculator framework was designed to help researchers evaluate the strength of password sets against offline attackers. It uses an automated, machine-learning approach that processes a training corpus of passwords to learn a simple PCFG that can generate new passwords. This PCFG is then queried to extract probabilities for passwords, and a lookup table is constructed that represents bundles of passwords in sorted order. A 2 TB lookup table can correspond to over 700 trillion guesses, or more or less depending on the complexity of the learned grammar and the desired accuracy of the evaluation.
Please note that this code was written for research purposes for a specific hardware configuration and was not designed with portability in mind.
This work is derived from tools provided by Matt Weir at https://sites.google.com/site/reusablesec/Home/password-cracking-tools/probablistic_cracker and published at:
Weir, M., Aggarwal, S., Medeiros, B. d., and Glodek, B. Password cracking using probabilistic context-free grammars. In Proceedings of the 2009 IEEE Symposium on Security and Privacy, IEEE (2009), 391–405.
Please refer to the INSTALL.md, USAGE.md, FAQ.md, and LICENSE files for more information.