Top Tweets for #xINT

Anthropic is (rightfully) generating a lot of attention for Mythos’s ability to find 0days, BUT the hard problem is not whether an LLM can recognize a bug when pointed at it; it is whether a system can find the right code to examine across a 9-million-line codebase, distinguish the one real vulnerability from the hundreds of theoretical weaknesses the model will flag along the way, and deliver output a developer can act on without wasting a week on false positives. This is something Xint has been doing since our wins at AIxCC and #ZeroDayCloud last year. We wanted to see if using publicly available models with the right scaffolding would reach the same performance as the latest limited-release frontier model under **real world conditions** In this research paper not only did we find all the same bugs highlighted in Anthropic’s report, but found an additional 12 mid- to high-severity vulnerabilities not included in their public disclosures. Check out the full report here: https://t.co/N0SfoyvMpk