From int $13 to distributed object clouds

[Dave Aitel <dave () immunityinc com>]

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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 :>
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