Re: From int $13 to distributed object clouds

[Jon Passki <jon.passki () hursk com>]

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On Dec 22, 2006, at 03:06 , Brian Azzopardi wrote:

> > They need to be grouped intelligently
>
> Can't you group IPs intelligently and then farm out the groups to be
> handled in parallel?

If I'm not hitting on the hookah too hard and understand what Dave's  
talking about , partitioning the universe of our hosts will occur  
more than once.  This is different than parallelism with one-time  
partitioning, ran until completion on a host.  The parallelism,  
methinks, would have to be dynamic and flexible (perhaps  
intelligent :-).  For example, assuming a zero-knowledge beginning,  
there's no way to start grouping IP's/targets/assets until something  
is learned, besides the asset identifier.  If you group as soon as  
something is known, such as subnet location of externally-facing IP  
addresses, and then want to regroup later on, such as subnet location  
of internally-facing IP addresses, all the hosts performing the  
parallelism potentially need to reshuffle their groups.


> > Some IP addresses are the same machine, and we need to know that
> 10.0.1.1 and 10.0.2.1 are the same machine
>
> You can do that as a post-process (assuming you don't do the  
> intelligent
> grouping first).

What's the point of messing with 1.1 if you already have it under the  
identity of 2.1?  If the goal is to perform as little action as  
possible (e.g. to be covert, to quickly gather data, and/or to reduce  
data analysis and post-grouping), then this is a wasted action. It  
just becomes a balance between the cost of reaching this goal and the  
cost of violating this goal.  Going w/ the concept above of  
regrouping and reshuffling the parallelism, one would want to perform  
the least amount of overlapping tests across all assets or groups of  
assets.  Since, if you reshuffle later, it would be ideal to combine  
disjointed sets versus identical sets.  Again, there's a cost in  
doing this...

> >  intelligent parallelism handled by a language
>
> What do you understand by intelligent parallelism? Is Occam  
> intelligent
> enough? Do you prefer implicit parallelism?
>
> Just for the record, I am working (slowly) on an new language that has
> parallelism as fundamental part of the language, rather than tacked on
> to it via threads like Python/C++/etc.
>
>
> Brian
>
>
>
> -----Original Message-----
> From: dailydave-bounces () lists immunitysec com
> [mailto:dailydave-bounces () lists immunitysec com] On Behalf Of Dave  
> Aitel
> Sent: Friday, December 22, 2006 4:43 AM
> To: dailydave () lists immunitysec com
> Subject: [Dailydave] From int $13 to distributed object clouds
>
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> The question you have to ask yourself when dealing with, as Sinan  
> would
> call it, "NP Complete Stuff" (aka, anything academic and wanky) is  
> "How
> is this going to help me hack something". Lately I've been, in the  
> back
> of my head, obsessed with distributed object languages. But how can I
> explain that having your language abstract not just memory management,
> but also parallelism, is going to help you break into more computers
> faster and better?
>
> The problem set is easy to understand: scanning a range of IP  
> addresses
> for exploitable vulnerabilities and then exploiting them.
> People look at that and say "Easy to parallelize. Just split it up  
> based
> on IP range.". They'd be wrong - IP addresses are connected to each
> other in many ways. They need to be grouped intelligently, and deep
> down, we're breaking into machines, not IP addresses. Some IP  
> addresses
> are the same machine, and we need to know that 10.0.1.1 and
> 10.0.2.1 are the same machine even if they've been split up across
> scanning processes which reside on different computing clouds. We also
> need to use information gained from hacking 10.0.1.1 against 10.0.2.1.
>
> Something in my right brain is telling me parallelism is the next big
> step for something like CANVAS. Not simple "split it up into bite size
> pieces", but intelligent parallelism handled by a language that is as
> much like Python as possible, but time abstract. Possibly the easier
> next step is built-in data-mining and CRM. When we do open source data
> collection on a target, I need somewhere to enter that in that can  
> reuse
> that information automatically. And when I own 10,000 machines, I need
> to be able to mine that cloud for the information I'm interested in,
> covertly.
>
> Of course, in the meantime it's shellcode shellcode shellcode. No  
> hacker
> ever truly gets away from that. Even here in Aotearoa there's an  
> int $13
> waiting...
>
> - -dave
>
> P.S. Congrats to NFR :>

[snip]

Jon

Obvia conspicimus, nubem pellente Mathesi.

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