Small models also found the vulnerabilities that Mythos found

https://aisle.com/blog/ai-cybersecurity-after-mythos-the-jagged-frontier

AI Cybersecurity After Mythos: The Jagged Frontier

Why the moat is the system, not the model

AISLE

If you cut out the vulnerable code from Heartbleed and just put it in front of a C programmer, they will immediately flag it. It's obvious. But it took Neel Mehta to discover it. What's difficult about finding vulnerabilities isn't properly identifying whether code is mishandling buffers or holding references after freeing something; it's spotting that in the context of a large, complex program, and working out how attacker-controlled data hits that code.

It's weird that Aisle wrote this.

If it’s obvious when you look close, then automate looking close. Seems simple to write tools that spider thru a code base, finding logical groupings and feeding them into an LLM with prompts like “there is a vulnerability in this code, find it”.

The thesis is, the tooling is what matters - the tools (what they call the harness) can turn a dumb llm into a smart llm.

Right, but they didn't actually test that, did they?