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The list is pretty short though for 8 months. ossfuzz has found a lot more even with the fuzzers often not covering a lot of the code base. Manually paying peo
by bgwalter 9mo ago
The list is pretty short though for 8 months. ossfuzz has found a lot more even with the fuzzers often not covering a lot of the code base.
Manually paying people to write fuzzers by hand would yield a lot more and be less expensive than data centers and burning money, but who wants to pay people in 2026?
- hedgehog 9mo agoI can't speak to what exactly this team is doing but I haven't seen any evidence that with-robot finds less bugs than without-robot. I do have some experience in this area.
- tptacek 9mo agoBugs are not equivalently findable and different techniques surface different bugs. The direct comparison you're trying to draw here doesn't hold.
- bgwalter 9mo agoIt does not matter what purported categories buffer overflows are in when manual fuzzing finds 100 and "AI" finds 5. If Google gave open source projects $100,000 per year for a competent QA person, it would cost less than this "AI" money straw fire and produce better results. Maybe the QA person would also find the 5 "AI" detected bugs.
- tptacek 9mo agoThis would make sense if every memory corruption vulnerability was equivalently exploitable, which is of course not true. I think you'll find Google does in fact fuzz ffmpeg, though.
- bgwalter 9mo agoGoogle gives a pittance even for full ossfuzz integration. Which is why many projects just have the bare minimum fuzz tests. My original point was that even with these bare minimum tests ossfuzz has found way more than "AI" has.
- tptacek 9mo agoAnother weird assumption you've got here is that fuzzing outcomes scale linearly with funding, which, no. Further, the field of factory-scale fuzzing and triage is one Google security engineers basically invented, so it's especially odd to hold Google out as a bad actor here. At any rate, Google didn't employ "AI" to find this vulnerability, and Google fuzzing probably wouldn't have outcompeted these researchers for this particular bug (totally different methods of bugfinding), so it's really hard to find a coherent point you'd be making about "fuzzers", "AI", and "Google" here.
- hedgehog 9mo agoMy guess is the main "AI" contribution here is to automate some of the work around the actual fuzzing. Setting up the test environment and harness, reading the code + commit history + published vulns for similar projects, identifying likely trouble spots, gathering seed data, writing scripts to generate more seed data reaching the identified trouble spots, adding instrumentation to the target to detect conditions ASan etc don't, writing PoC code, writing draft patches... That's a lot of labor and the coding agents can do a mediocre job of all of it for the cost of compute.
- tptacek 9mo agoIf it's finding exploitable bugs prior factory-scale fuzzing of ffmpeg hasn't, seems like a pretty big win to me.
- hedgehog 9mo agoFor sure, and I think it expands the scope of what factory scale efforts can find. The big question of course being how to handle remediation because more bugs without more maintainer capacity is a recipe for tears.
- bgwalter 9mo ago[flagged]