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Date: Fri, 16 Mar 2018 18:47:20 +0100
From: Matlink <>
Subject: Re: Is john really using Narayanan and Shmatikov whitepaper?

Le 16 mars 2018 18:32:29 GMT+01:00, Matt Weir <> a écrit :
>As a note of caution, I'm 99% sure that Simon's presentation at
>Passwords12 was about advancements to JtR's Markov model that could be
>made vs. what's actually implemented, though the sections about
>nbparts, (slides 7-14), should apply.
>A good reference that I had mentioned to Matlink privately, but I
>figure I should post here for everyone else, is the JtR Wiki write-up
>on Markov mode:
>Side note, I had completely forgot about Simon's work to provide an
>accurate index function for JtR Markov that he detailed in his
>presentation which would be useful to the previous thread Matlink had
>brought up :)
>Alexander, talking about incremental, are you aware of any write-up
>for it behind it besides "look at the code?" Something like the JtR
>Wiki article for Incremental might help other researchers. In practice
>I've found Incremental is much more effective then Markov so I tend to
>steer people to it as well, but there's not much out there to
>understand what's going on under the hood. I know I've struggled with
>that, (and made mistakes describing it).
>On Fri, Mar 16, 2018 at 10:35 AM, Solar Designer <>
>> Hi,
>> On Fri, Mar 16, 2018 at 02:23:04PM +0100, Matlink wrote:
>>> I was wondering, for research purposes, how John was applying Markov
>>> chains for its markov mode.
>> I think the closest to documentation of Markov mode's internals is
>> presentation, by Simon who contributed this mode to jumbo:
>> I also want to say once again that if you do any research involving
>> JtR jumbo's Markov mode, please also include in your research JtR's
>> incremental mode, which pre-dates Markov mode and isn't named Markov
>> is also closely related.
>> Unfortunately, the Markov vs. incremental mode comparison in the
>> presentation uses JtR 1.7's incremental mode, whereas 1.8's should
>> perform better.
>> Alexander

Well I found the open wall wiki about Markov mode not detailed enough to be reproducible. Only the general concept is presented, alongside with how to use tools.
I would also be interested on some documentation about the incremental mode, to re-implement it.

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