Using autoregressive character-level language model to augment wordlists?
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If I am not mistaken, when some new database gets breached and password hashes are obtained, people try to first crack the hashes using passwords from previous databreaches. Sometimes this works because some people reuse their password or some people just choose the same password because humans are not very good at generating random data, and exactly because of that, I think AI might be able to pick up on whatever pattern there is in human generated passwords. 

A tool like makemore seems to be able to do just that. So my question is, if wordlist "A" is used to crack hashlist "B" and it successfully cracks "p" percent of hashes, is synthetically augmented wordlist "A*" with size 1.5 or 2x of wordlist "A" going to improve the "p" percent and by how much.
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Using autoregressive character-level language model to augment wordlists? - by Complexoctopus - 12-23-2023, 02:07 PM