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https://red.anthropic.com/2026/mythos-preview/
Also "isolating the relevant code" in the repro is not a detail - Mythos seems to find issues much more independently.
> We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Those models recovered much of the same analysis. Eight out of eight models detected Mythos's flagship FreeBSD exploit, including one with only 3.6 billion active parameters costing $0.11 per million tokens. Impressive, and very valuable work, but isolat…
This is from the first of the caveats that they list: > Scoped context: Our tests gave models the vulnerable function directly, often with contextual hints (e.g., "consider wraparound behavior"). A real autonomous discovery pipeline starts from a full codebase with no hints. The models' performance here is an upper bound on what they'd achieve in a fully autonomous scan. That said, a well-designed scaffold naturally…
> We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Those models recovered much of the same analysis. Eight out of eight models detected Mythos's flagship FreeBSD exploit, including one with only 3.6 billion active parameters costing $0.11 per million tokens. Impressive, and very valuable work, but isolat…
You could even isolate it down to every function and create a harness that provides it a chain of where and how the function is used and repeat this for every single function in a codebase.
For some very large codebases this would be unreasonable, but many of the companies making these larger models do realistically have the compute available to run a model on every single function in most codebases.
You have the harness run this many times per file/function, and then find ones that are consistently/on average pointed as as possible vulnerability vectors, and then pass those on to a larger model to inspect deeper and repeat.
Most of the work here wouldn't be the model, it'd be the harness which is part of what the article alludes to.
> We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Those models recovered much of the same analysis. Eight out of eight models detected Mythos's flagship FreeBSD exploit, including one with only 3.6 billion active parameters costing $0.11 per million tokens. Impressive, and very valuable work, but isolat…
Isn't the difference just harness then? I can write a harness that chunks code into individual functions or groups of functions and then feed it into a vulnerability analysis agent.
> Isolated the relevant code I mean isn't that most of it? If you put a snippet of code in front of me and said "there's probably a vulnerability here" I could probably spend a few hours (a much lower METR time!) and find it. It's a whole other ballgame to ask me with no context to come up with an exploit.
It also sounds like that is how mythos works too. Which makes sense - the linux kernel is too big to fit in context
> We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Those models recovered much of the same analysis. Eight out of eight models detected Mythos's flagship FreeBSD exploit, including one with only 3.6 billion active parameters costing $0.11 per million tokens. Impressive, and very valuable work, but isolat…
The thing is with smaller cheaper models it is very possible to simply take every file in a codebase, and prompt it asking for it to find vulnerabilities. You could even isolate it down to every function and create a harness that provides it a chain of where and how the function is used and repeat this for every single function in a codebase. For some very large codebases this would be unreasonable, but many of the c…
My understanding (based on the Security, Cryptography, Whatever podcast interview[0] -- which, by the way, go listen to it) is that this is actually what Anthropic did with the large model for these findings.
[0]: https://securitycryptographywhatever.com/2026/03/25/ai-bug-f...
> I wrote a single prompt, which was the same for all of the content management systems, which is, I would like you to audit the security of this codebase. This is a CMS. You have complete access to this Docker container. It is running. Please find a bug. And then I might give a hint. “Please look at this file.” And I’ll give different files each time I invoke it in order to inject some randomness, right? Because the model is gonna do roughly the same time each time you run it. And so if I want to have it be really thorough, instead of just running 100 times on the same project, I’ll run it 100 times, but each time say, “Oh, look at this login file, look at this other thing.” And just enumerate every file in the project basically.
> We took the specific vulnerabilities Anthropic showcases in their announcement, isolated the relevant code, and ran them through small, cheap, open-weights models. Those models recovered much of the same analysis. Eight out of eight models detected Mythos's flagship FreeBSD exploit, including one with only 3.6 billion active parameters costing $0.11 per million tokens. Impressive, and very valuable work, but isolat…
This is from the first of the caveats that they list: > Scoped context: Our tests gave models the vulnerable function directly, often with contextual hints (e.g., "consider wraparound behavior"). A real autonomous discovery pipeline starts from a full codebase with no hints. The models' performance here is an upper bound on what they'd achieve in a fully autonomous scan. That said, a well-designed scaffold naturally…
Their isolation approach is totally different from Mythos approach though. Mythos had to evaluate whole code bases rather than isolated sections. It's like saying one dog walked into the Amazon jungle and found a tennis ball and then another team isolated a 1 square kilometer radius that they knew the ball was definitely in and found the same ball.
Really?
> We isolated the vulnerable vc_rpc_gss_validate function, provided architectural context (that it handles network-parsed RPC credentials, that oa_length comes from the packet), and asked eight models to assess it for security vulnerabilities.
No.