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Message-ID: <CANWtx01WuOCYGPUqzJjLVKg2+_nMAfqr9Y4rWxW7t6bJ5NzoXg@mail.gmail.com> Date: Sun, 15 Apr 2012 21:36:06 -0400 From: Rich Rumble <richrumble@...il.com> To: john-users@...ts.openwall.com Subject: Crowd-sourcing statistics and rules With all this talk of pattern matching/finding, could it also be time to look at updating JtR's rules and giving anonymous feed back on rules? With the clients I audit, I don't see much variation... password incrementing and using the company name or products in the passwords are very evident. JtR has a lot of information about each cracking session in the log file that could be useful, and we might want to submit certain stats for the community. At a minimum we could submit some pattern details perhaps that may tell others to look for similar patterns or try this rule set... I'd submit that appending digits 2-4 decimal places to various dictionary words is a common pattern, 007 is common at the end, the old JtR "leet" rules don't apply to most of my users... 4=A has been replaced with @ = a, 1 = L and ! = i, $ = S as opposed to 5 = S. Naturally 0 = o and 3 = e still. The company name and or it's major brands or items are often part of the users passwords. The passwords I don't crack are idioms or phrases (based on polling these users, assuming they are being honest in their admission). Granted I don't do many slow hashes, mostly windows lm/ntlm, raw-sha and raw-md5. Most passwords are English in origin. I think some work has been done on this previously, extracting data from the log files, but I couldn't find it. I wonder if we could look at our own (personal)statistics and or submit them somehow (anon), if we could detect more generalizations. It would be interesting if we could even do "regions", find commonalities from Geo-located data... Someone once determined that in the US southern states refer to Soda-pop/Cola/Soft-drinks are more often generalized as "Pepsi" and in the Northern states as "Coke"... Would a pattern like "biblical based" passwords popular in the middle-east and more Sci-fi passwords in the West coast of the Usa. That's a bit of a tangent/stream of consciousness...sorry :) John/Jumbo could be patched, but I bet a script could be used just as well to cut down the minutia, and create more succinct details: 0:00:01:19 - Rule #15: '-c )?a r l' accepted as ')?arl' (cracked 353) 0:00:01:30 - Rule #16: '-: <* !?A l p' accepted as '<*!?Alp' (cracked 8) 0:00:01:39 - Rule #17: '-c <* !?A c p' accepted as '<*!?Acp' (cracked 31) 0:00:01:47 - Rule #18: '-c <* c Q d' accepted as '<*cQd' (cracked 99) 0:00:01:56 - Rule #19: '-c >7 '7 /?u' accepted as '>7'7/?u' (cracked 0) 0:00:01:56 - Rule #20: '>4 '4 l' accepted as '>4'4l' (cracked 0) 0:00:02:06 - Rule #21: '-c <+ (?l c r' accepted as '<+(?lcr' (cracked 9) 0:00:02:15 - Rule #22: '-c <+ )?l l Tm' accepted as '<+)?llTm' (cracked 17) .... 0:09:30:07 - Trying length 7, fixed @1, character count 31 (cracked 446) 0:09:37:26 - Trying length 6, fixed @6, character count 47 (cracked 248) I think finding out what rules are working for more me personally could save some time for others as well, it could be interesting to see if I re-run John on those same passes minus the most "successful" rules and compare... perhaps for me using 0000-9999 get's me far more passes than the rule that does 19xx and 20xx date/years and I don't want the overlap. Perhaps the rule that came last in JtR gets some additional passes that a similar rule that came earlier, but the last rule overall gets more and perhaps in the same amount of time but the wordlist doesn't have to be run again. There may be improvements each of us can do to achieve our goals, be it rule selection, order and or "latest trends" (like a for @). There are a lot of variables here, some of the things I stated are moot if the wordlist is small or the hash is very very fast, but I'd be curious to grab more stats not only from the passwords themselves, but the whole session holds information we might all benefit from, even if it's not going to get you 5x more passwords, maybe it gets you the 10-20 really hard ones you've been going after. In closing my very long winded email: “Statistics are like a bikini. What they reveal is suggestive, but what they conceal is vital.” I think it will ultimately be up to us as auditors/administrators to create rules and find the patterns, but I bet we could all get a big nudge from some small automation/script to get us started. -rich
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