A while ago I posted a blog entry called “challenging conventional wisdom on AV signatures (Part 1 of 2)”. There, I argued that the fundamental problem with traditional AV byte signatures is the of lack of information asymmetry: The defender and the attacker both have access to the same information, and the attacker can run a potentially infinite number of test-runs to make sure he can reliably bypass all of defensive measures the defender has taken.
The important thing to take away from that blog post is that the problem with AV signatures is not inherent to “signatures” – it is a matter of information symmetry.
Now, how can one change this situation? Is there a clever way to make traditional byte signatures useful again? Can we somehow introduce information asymmetry in a productive manner?
To investigate this, we have to remember another blog post where I described some of our results on generating “smart” signatures (this appears to be AV lingo for signatures that are not checksum-based, but which consist of bytes and wildcards). The summary of this blog post is more or less: “With the algorithms underpinning VxClass, we can not only automatically cluster malicious software into groups, we can also generate signatures for each group automatically. And one signature will match the entire group.”
There was one small bit of information missing in that post that will make this post interesting: We can usually generate dozens, if not hundreds, of different signatures for the same cluster of malware. These signatures match, by construction, on all samples of a particular cluster, but they have nothing in common – they match on different bits of the code.
Where does this leave us? Well, it leaves us with a pretty cool system that we call VxClass for Financials (although it is possible to substitute ‘Financials’ with other large verticals that are often victims of targeted attacks). The system works as follows:
- Different financial institutions each get a user account on a centralized VxClass server
- Users upload malicious software that they have recovered (using tools such as Memoryze) from their own systems
- Users are anonymous by default
- Users can see how malware they upload clusters; they can also see how similar their malware is to malware other users uploaded
- Users can only download their own malware, not the malware of other users
- For each cluster, users can generate a personalized detection signature that no other user will ever see
Why is this cool ? Well, for one thing, every user profits from uploading to the system — the more samples are present in one cluster, the better the predictive power of the signatures. At the same time, users do not have to share any confidential information with each other — they are encouraged to, but they do not have to. Finally, even if some users of the system are sloppy and leak their signatures to the attacker, they only endanger themselves – everybody else has their own signatures, and will thus not be affected by this signature leak. This is important – normally, when I share methods of detection with others, I risk losing them. Not here.
We are starting an evaluation/beta program of the system in the next 1-2 weeks — at the moment, targeted at the financial sector. If you happen to find this interesting, are working for a financial institution and want to participate in our test drive, please contact us at email@example.com !