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Message-ID: <98675fff-6f9a-3f71-0eab-b0a5c605e502@matlink.fr>
Date: Tue, 13 Feb 2018 16:44:03 +0100
From: Matlink <matlink@...link.fr>
To: john-users@...ts.openwall.com
Subject: Re: Markov Sampling
> The pre-defined --external=Parallel mode will do what you ask for.
> You'll just need to customize the "node" and "total" numbers in its
> init() in john.conf.
Well, I guess it's only 'not printing' generated candidates? Does it
really speed up the process, since generating a password candidate is
more costly than printing it?
Concretely, is --markov --stdout --external=Parallel with node 1/100,
100 times faster than with node 1/1?
> However, note that "every 10th" doesn't necessarily produce a
> representative sample: the underlying cracking mode (in this case,
> Markov) might happen to have some periodicity in its output, and one of
> its period lengths might just happen to be a multiple of 10 or whatever.
> So ideally you'd want to randomize the order (if the order somehow
> doesn't matter for your research) over a larger number of candidate
> passwords - say, pass a million of them through GNU coreutils' shuf(1) -
> and then take every 10th out of that randomized list.
>
My issue is that I can't get the whole output because it is too costly
for me to gather them due to UNIX pipe. I would like to my
john --stdout --markov --sample=100 | my_sublime_post-process
be somewhat 100 times faster than
john --stdout --markov --sample=1 | my_sublime_post-process
Your solution requires to get the whole output of john and then
post-process it, but I can't find a satisfiable way to get its whole
output (since john is really fast to generate candidates).
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