If you're someone at OpenAI or Anthropic and you truly believe what you're making could destroy the world, this is the kind of thing that isn't doing you any favors when it comes to convincing the public. The dissonance here is stark:
- widely proclaiming that your new model is so dangerous it needs to be released only to select people, for safety
- widely proclaiming the model easily found 79 bugs in linux, except that GKH says it took 1 hour to fix all of them because most weren't bugs and the rest were almost all completely trivial, unimportant, and/or not severe
The headline here is that none of the bugs were serious.
so is mythos just a chat bot with metasploit and its own cyber range?
Mythos may not be great today but it is not far fetched to imagine bug discovery, analysis and fixes can be made much quicker, accurate and even newly possible with specialized models trained on say Linux kernel specifics - with codemap/coding standards/threat models, good and bad coding patterns, tools to validate etc. an LLM can be much more relentless than humans and if it has the help to be accurate it will be worth the electricity burned. Oh and another model trained on triage data to validate the first one's findings would be good.
(I think Microsoft is doing this internally - different models trained internally alongside Mythos - there was some talk about it on the tubes, don't recall where exactly.)
"the CVE assignment team is overly cautious and assign CVE numbers to any bugfix that they identify. This explains the seemingly large number of CVEs that are issued by the Linux kernel team."
Wake me up when Raspberry Pis start refusing to open doors saying : "I'm sorry, Dave. I'm afraid I can't do that."
It’s all just pr stunts, fear spread fast and it’s very effective in marketing and spreading the word, which is effective, when I talk to some normal people they immediately bring the scary AI cyber attacks, kinda good as now all are willing to fund the industry!
also, lol at "The bots are dumb - they want to please you line". LLMs have pretty much ruined technical collaboration between contributors. I get tilted every time an discussion has "but my claude said this..."
"NEVER upload any non-public information" - He's talking about how if you give Claude/GPT some secret info (like research, credentials, etc), it will train on it and give the same info to someone else. This is 100% the case for the free and consumer versions of these models, which is what most people use. For Enterprise plans they're not supposed to be doing this, but it's possible they will screw up and do it anyway.
From his Kernel Recipes 2026 slide on Mythos
```
```GHK called this "10 'real' bugfixes", which to me sounds like there's a wild hype machine around these companies and uncritical parroting of every press release they make that falls apart when you engage the affected real experts.
Most of the real low hanging fruit was picked up by humans years ago. When doing automated scanning, the majority of stuff is overly-verbose nonsense which takes hours of expert human labour to understand, test, and discard.
Reading through a Claude generated false positive is absolutely excruciating, because it is absolutely determined that what it’s found is justified. Often you’ll receive very long accompanying “proof of concept” code which demonstrates absolutely wild scenarios. It’s especially frustrating when you’re volunteering your time for a project, and a well-meaning contributor submits the report without the technical nous to understand why you’re rejecting it.
Very gung ho, full of energy, loads of book learning, no real world experience or understanding of why things are as they are.
Leave them to their own devices at your peril. Trust nothing they do.
Yet directly guide them, monitor everything they do, some value emerges.
Mythos turned out to be exactly the marketing stunt it smelled like.
There are others like AISLE who seem to be a bit more successful in finding actual issues using LLMs in some shape or form though, whatever they do differently. Chances are high the secret sauce is not so much about the model being exceptionally powerful which would be bad news for the frontier labs.
Zip-zapping the bouzouki...
Exfiltrating nuclear arm codes...
Thought for 76 seconds.
You're right to push back on that. That's on me.
That said, I remember trying to weigh the hype at the time of the announcement reading/skimming the papers Anthropic published, recognizing that bugcount alone wasn't super-relevant but also remember being impressed by an NFS bug and a kernel bug that struck me as relevant at the time. So where did that NFS issue show up in GKH's list you showed so nicely above?
It turns out, AFAICT, it's not on his list, but the reasons are perhaps interesting to others so I will post here. It turns out there were two NFS issues this past year conflated a bit in my memory:
* The Linux CVE-2026-31402 NFS heap overflow that could allow unauthenticated memory reads over the network isn't in that list of 79, presumably because it was found by Claude Code, not Mythos months earlier. (I am guessing it's not his "malicious network packet into the middle of the stack" and is a stronger attack being a remote attack.)
* And the CVE-2026-4747 NFS stack buffer overflow that allowed gaining full unauthenticated remote root access didn't show up in GKH's list of 79 because despite being Mythos-caught, it wasn't Linux, it was FreeBSD.
I guess this does match my memory now that I think about it, that there weren't any smoking Linux guns caught by Mythos.
* (I guess there was also a longstanding 27-year old OpenBSD TCP SACK-handling stack integer overflow than enabled remote crashes / Denial of Service found by Mythos.)
There is definitely Mythos hype, but just because it hit the BSD code base more than the GKH-managed Linux code base doesn't mean it was inappropriate to raise eyebrows from Mythos, in particular since "attacks only get better".