AI Cybersecurity After Mythos: The Jagged Frontier
evelinag
12 points
7 comments
April 09, 2026
Related Discussions
Found 5 related stories in 112.8ms across 8,358 title embeddings via pgvector HNSW
- Small models also found the vulnerabilities that Mythos found dominicq · 961 pts · April 11, 2026 · 73% similar
- Mythos is the best cybersecurity news in a decade littlexsparkee · 42 pts · May 06, 2026 · 71% similar
- AI Is Tipping the Scales Toward Hackers After Mythos Release thywis · 14 pts · April 11, 2026 · 68% similar
- Mythos Falls into the Wrong Hands etothet · 11 pts · April 22, 2026 · 63% similar
- After dissing Anthropic for limiting Mythos, OpenAI restricts access to Cyber gbourne1 · 139 pts · May 01, 2026 · 63% similar
Discussion Highlights (3 comments)
baq
> TL;DR: We tested Anthropic Mythos's showcase vulnerabilities on small, cheap, open-weights models. They recovered much of the same analysis. AI cybersecurity capability is very jagged: it doesn't scale smoothly with model size, and the moat is the system into which deep security expertise is built, not the model itself. Mythos validates the approach but it does not settle it yet. Notably, Kimi K2 and GPT-OSS-120b do quite well when provided with the isolated context. Article seems to be heavily LLM-assisted, but the content itself is good.
1970-01-01
I'm awaiting general release so I can root and jailbreak some old Android/iphones. If it succeeds, I'm a fan. If it fails, then it's obviously not a leap, it's another step.
tao_oat
> Our tests gave models the vulnerable function directly, often with contextual hints (e.g., "consider wraparound behavior"). "Often with contextual hints" is doing some heavy lifting here, IMO. I agree with the article's premise -- you don't need Mythos to use AI to find novel, complex vulnerabilities -- but these results as presented are somewhat misleading.