[WEB SECURITY] Artificial Intelligence vs. Human Intelligence on finite amounts of possible outcomes
tasos.laskos at gmail.com
Tue Feb 1 14:46:14 EST 2011
On 01/02/11 19:20, Andres Riancho wrote:
>> I'd like to note at this point that I'm a strong proponent of fixing the
>> root of the problem instead of adding filtering layers on top of it but
>> let's ignore this for argument's sake as well.
>> * We have a finite amount of entities that assert the existence of issues
>> -- we'll call these "modules".
>> * We have a finite amount of outcomes for each of the modules; usually a
>> binary result (either true/vulnerable or false/safe)
>> but in some cases with a twist about the certainty of a result (i.e. a
>> notice that an issue may require manual verification).
>> And here comes my point:
>> Do we really need AI? Wouldn't simple rules that check for unusual
>> results and give appropriate notice suffice and be a better and more
>> efficient way to handle this?
> In some cases you need AI, or need lots of signatures (either works).
> For example, if you're trying to find SQL injections based on error
> messages, a module that has 10 signatures is worse than one that has
> 100. But I'm sure that the module with 100 signatures doesn't cover
> all possible DBMS errors. On the other side, a web application
> penetration tester that sees a rendered HTML response can identify a
> SQL error even if its not something he has seen in the past (its not
> in the expert's signature DB). That's where AI might be handy.
That's not what I meant exactly.
My thoughts were mostly towards interpretation of the results after the
Something akin to adding the following to the report:
Judging by the results of the scan and request timeouts the site seems
to have been stressed to its limits.
This shouldn't have happened and it means that you are susceptible to
DoS attack quite easily.
The web application's cookies are uniformly vulnerable across the web
Consider adding a centralized point of sanitization.
I know that this comes close to taking the user by the hand (which I've
never really liked)
but I really think that such a system could work and save us time while
we're performing a pentest by
incorporating an expert's maverick experience, insights and
interpretation to an otherwise soulless process.
Something far superior to any AI.
>> A possible implementation I have in mind is to pre-tag a module when it's
>> added to the system.
>> The tags would specify key elements of the behavior of a module and will
>> later be used in the decision making process (based on rules).
>> For instance, in the example I mentioned at the beginning of this e-mail,
>> the system would check how many of the results have the "timing_attack" tag
>> and if that number was above a preset threshold it would remove the results
>> from the scan report or flag them accordingly.
>> And possibly take into account environment statistics to make a more
>> well-rounded decision (like average response times etc).
> That makes sense... somehow... but I would rather fix the cause of the
> timing attack bug.
That's why I said not to focus on that particular scenario as I'm not
talking about avoiding
false positives or (just) improving the accuracy of modules but to use
our that information to our advantage.
>> What do you guys thing?
> AI for web application scanning has been on my mind since I started
> with w3af, but I really haven't found a problem for which I would say:
> "The best / faster / easier to develop way to solve this is AI". Maybe
> if we hit our heads hard enough, we can find something where AI is
> applied and then state: "w3af/arachni , the only web app scanner with
> AI" ? :)
Same here, and I'd rather avoid it too; that's why I presented this
thought of mine as a more fitting alternative to such a situation.
I usually try to avoid unnecessary complexity like the plague.
>> Tasos L.
>> PS. I guess that this could be perceived as pre-trained expert system but
>> not really.
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