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Are you certain about that? Anthropic has a team of security engineers "validating" the LLM output, and then they have been passing on their "validated" outputs to third-party security researchers to "confirm" them.
Tellingly, they don't say how many false positives have to be filtered through in order to find the correct vulnerabilities with working exploits, but I imagine that if all those security researchers were tasked with auditing the same codebases, they would probably find the same (or more) vulnerabilities without the shotgun guessing of an LLM to guide them.
You need to remember that these claims are being made by a company that has enormous financial incentive to make everyone believe that this model is a huge breakthrough.
I have no inside knowledge on this particular work, but their previous work on the OSS-fuzz targets and on Firefox were all excellent quality bug reports.
Seriously. Look them up.
They were all reproducible ways to trigger faults in ASan builds. That’s by definition memory corruption. We can argue about whether all of them are exploitable, but a) they need to get fixed regardless b) we know that even tiny memory corruptions can often be leveraged into a compromise given enough effort.
The question isnt how good the results are, its whether you can achieve the same quality for the money without an llm.
The stories of the bsd bug say they spent $20k on compute alone (and who knows if thats before or after VC subsidies). Then they had so many reports they need to pay some of the top experts to triage which ones were real.
And the result? no remote code execution, no data theft. A remote crash. Its a real bug that can cause problems but its not actually an exploit.
The sad thing is there really could be something new and useful in ai model security, people are seeing good results by automating the reproduction step, but the presentation of it as too dangerous to release and a massive change just sound like pure marketing.
Most likely its just too expensive to do this unless youre a vc funded op with its own compute and want a pr campaign to stop people thinking about how shit the source code you just accidentally released is.
Obviously Antropic has no incentive to keep the token counts low. My understanding of their strategy is that they are betting on models getting better faster than what would justify the effort needed to squeeze more value per dollar out of them. Obviously I have no data to contradict them, but I would be surprised if that’s the case in the long term and for everyone.
My guess is that the costs can be reduced substantially, but that’s only going to happen once these tools get into the hands of your average security researcher.
Yes of course they were. Professional security researchers tend to produce professional, high quality reports.