i think a key missing part is that an LLM on its own can't find vulnerabilities, so it's always an AI + harness. even mythos, when used for finding zero-days, is using an actually surprisingly heavy handed and expensive scaffold. they literally make it run in parallel on ±all files and ask "what's wrong with this?". here from the mythos technical blog post [1]:

> To increase efficiency, instead of processing literally every file for each software project that we evaluate, we first ask Claude to rank how likely each file in the project is to have interesting bugs on a scale of 1 to 5. A file ranked “1” has nothing at all that could contain a vulnerability (for instance, it might just define some constants). Conversely, a file ranked “5” might take raw data from the Internet and parse it, or it might handle user authentication. We start Claude on the files most likely to have bugs and go down the list in order of priority.

So they process it in parallel, but AI-rank them based on vuln-likelihood first = exhaustive search with a heuristic filtering first

[1] https://www.anthropic.com/research/mythos-preview

i don't think this is correct. if you look at this article by the curl founder daniel stenberg (https://daniel.haxx.se/blog/2026/05/11/mythos-finds-a-curl-v...), he talks about how he previously ran Mythos on curl and that it found 5 issues: 1 turned out to be a low severity CVE, 3 were false positives, and 1 just a bug. So a) Mythos detects low severity CVEs too, and b) it is fairly noisy

i don't think this is doable fairly. as they say in the blog post, the only fair way to is to look for new, previously undiscovered zero-days, otherwise you always risk the model has in some way been trained on the vulnerabilities. looking for legit new stuff is the only way to prevent leakage (even accidental one)

That’s my point too.

I think you might be misunderstanding this? This is, from my understanding, what went down:

1. curl was scanned by many different things, including AISLE, and many bugs were fixed <- all this was in the past 2. curl a week ago was scanned again my Mythos and Codex Security, and both of them said: 0 issues found 3. the same curl was scanned by AISLE a day later, resulting in ~29 reports (based on the blog post and mastodon posts from Daniel Stenberg) 4. of these 29, 6 cleared the bar and got CVEs in curl 5. these 6 CVEs were just announced as fixed in curl 8.22.0 today, together with 4 more CVEs that were detected by other people prior to point 2. of this list

so imho it was head-to-head, the very same codebase => it's a legit comparison

Curl has been scanned by mythos and several other AI tools several times over the past year already. Mythos found nothing this round, but when it was first released it found issues which have been fixed - and several other AIs had already scanned curl for issues which had been fixed by then.

We can say that this is a useful tool, but is it better or worse than the others - there is no way to make that conclusion.

Edit, wait, are you claiming that asile was already used and those issues fixed, and it still found more. That is valid, but it only says that asile is better by enough that is worth an upgrade, while the others probably are not. It is not valid in comparing to other tools. (assuming this is true, I've never heard of asile before this)

I don't understand your objection. If tool A says "job is done" and tool B says "found N additional tasks that need doing" how does the history matter? B is turning up things that A isn't thus B is performing better. They both had access to the same inputs here.

I suppose it's interesting to wonder if B would have turned up issue X which A previously found. But that seems largely academic to me. There is a code base right now with N known issues (thanks to B) and A is saying everything is good. It seems like that's all that should matter here.

The "Better" is where I have an issue. There isn't enough information here to say one is better than the other. Both are useful tools is clear.