Greatly appreciated the candor. I've included a few slides into text that i thought were eye-opening to me:
From his Kernel Recipes 2026 slide on Mythos
```
Mythos's 79 vulnerabilities:
24 - no detail at all "something crashed"
14 - not a bug at all
3 - totally made up data
15 - already fixed in latest release
- 11 by others
- 4 by anthropic
20 - fixes were needed
- 7 "assume a malicious filesystem image"
- 2 "assume you can inject a malicious network packet into the middle of the stack"
- 2 "NOMMU"
- 6 sctp networking issues for untrusted devices
- 2 ipv6 minor network issues
- 1 gpu driver for local malicious user
```
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.
We’ve seen this in a few open source repos we voluntarily manage security on. They’re not massive repos, but big enough they get attention from security researchers.
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.
Okay so now they're like a top percentile fresh grad on meth. Still a lack of real world experience plus some bizarre failures that illustrate gaping holes in the mental model. Does that description work for you?
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.
AI and Police have essentially the same journalists who, in lieu of any research or fact checking, just report verbatim their press releases and interviews.
What a great excerpt; thank you! It reminds me of what I find when I look at CVEs handed out by scanners at places I've worked for actual impact to systems I've owned... there are a lot of slop/false positives. (And that's even without "AI".)
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".
> So what all of mythos; that whole big marketing issue of 79 bugs came down to one hour of kernel development.
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
It doesn't mean the model isn't dangerous or super capable but wow this makes it realllll easy to doubt it and any future announcement.
> I don't understand the relevance of time to fix. It has no correlation with severity.
That they're small bugs that don't involve any serious architecture changes (or architecture sleuthing), just small pattern recognition. LLMs are pretty good (maybe great) at that. Finding 10 bugs is nice. Now find 10 more.
It doesn't have to be world-ending. Autonomous, malicious agent swarms are something we haven't had to deal with. What does mitigation of a malicious, self-replicating swarm worm look like? We will find out soon enough.
yes and it makes me wonder about the claims others make about their own experiences with the models too. is this the case of OAI lying, or is it part of ai psychosis where you literally lose touch with reality as you uncritically accept whatever claims the LLMs make?
At 3m19s Greg KH revealed what Mythos did in "revealing" 79 CVEs - pure pattern matching the previous decades of kernel developer's patches, and applying those mechanisms elsewhere to see if they have been universally patched. And Anthropic didn't cite Kernel Developers who original fixed/patched the CVEs like a decent human being would do. So yeah, Anthropic has the same problem OpenAI had for citing original work.
It's great to hear about $topic from someone no-nonsense and in-the-know like Greg KH. You can verify all of this too - since, well Linux kernel. (As opposed to what Microsoft or Apple claims to fix as far as LLM finds.)
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.)
His presentation style may be no-nonsense, but the content is brimming with nonsense. I would like to hear Greg Kroah-Hartman explain how the Mythos output was 'only 10 real bugs' but there were simultaneously over 1300 CVEs issued last month. It seems not much counts as a 'real bug' when an LLM comes up with it, but when it's time to bully distros into shipping an LTS release, anything goes?
"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."
Nice to see Kernel Recipes covered again on HN. Shameless plug: I do the live blog: it's incomplete, imperfect and has typos; but it's written and published during the presentations. On this talk : https://kernel-recipes.org/en/2026/2026/09/22/live-blog-day-...
No no, the word wasn’t conscious, it was “sentient”, and google fired the employee because he uncovered the top secret crazy scary AI!!!!
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!
cool to see a really grounded analysis of the "security" and LLMs. I use agents in on the day-to-day for generating implementation but this just furthers my belief that humans and especially human reviewers remain critical for the sustainability of software systems.
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..."
"Ignore the comments, look at the code" - 100% agree. The comments and "explanations" will end up confusing you and often being wrong. But the code doesn't lie.
"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.
Greatly appreciated the candor. I've included a few slides into text that i thought were eye-opening to me:
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.
We’ve seen this in a few open source repos we voluntarily manage security on. They’re not massive repos, but big enough they get attention from security researchers.
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.
Right now, all top tier LLMs are as eager, bright 20ish year old interns.
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.
Have you used a frontier model since 2025? You are underplaying their strength.
Kroah-Hartmann has used the closed frontier++ model, and it made up 37 out of 76 vulnerabilities.
Okay so now they're like a top percentile fresh grad on meth. Still a lack of real world experience plus some bizarre failures that illustrate gaping holes in the mental model. Does that description work for you?
Well, so basically supercharged fresh grad. CS/math implied.
In human terms, that's already at least a standard deviation above average person.
It also adds up to 76, which he made fun of in the video. LLM can't count, his words, not mine. Although, I tend to agree with him!
Related: https://daniel.haxx.se/blog/2026/05/11/mythos-finds-a-curl-v...
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.
Or the people of Anthropic, just really suck at coding, and are scared or their own models due to ignorance.
Tightening molecular vortices...
Zip-zapping the bouzouki...
Exfiltrating nuclear arm codes...
Thought for 76 seconds.
You're right to push back on that. That's on me.
AI and Police have essentially the same journalists who, in lieu of any research or fact checking, just report verbatim their press releases and interviews.
What a great excerpt; thank you! It reminds me of what I find when I look at CVEs handed out by scanners at places I've worked for actual impact to systems I've owned... there are a lot of slop/false positives. (And that's even without "AI".)
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".
> So what all of mythos; that whole big marketing issue of 79 bugs came down to one hour of kernel development.
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:
It doesn't mean the model isn't dangerous or super capable but wow this makes it realllll easy to doubt it and any future announcement.I don't understand the relevance of time to fix. It has no correlation with severity.
The headline here is that none of the bugs were serious.
> I don't understand the relevance of time to fix. It has no correlation with severity.
That they're small bugs that don't involve any serious architecture changes (or architecture sleuthing), just small pattern recognition. LLMs are pretty good (maybe great) at that. Finding 10 bugs is nice. Now find 10 more.
It is impressive and wonderfully convenient technology but I struggle imagining Claude ending the world just yet.
It doesn't have to be world-ending. Autonomous, malicious agent swarms are something we haven't had to deal with. What does mitigation of a malicious, self-replicating swarm worm look like? We will find out soon enough.
yes and it makes me wonder about the claims others make about their own experiences with the models too. is this the case of OAI lying, or is it part of ai psychosis where you literally lose touch with reality as you uncritically accept whatever claims the LLMs make?
At 3m19s Greg KH revealed what Mythos did in "revealing" 79 CVEs - pure pattern matching the previous decades of kernel developer's patches, and applying those mechanisms elsewhere to see if they have been universally patched. And Anthropic didn't cite Kernel Developers who original fixed/patched the CVEs like a decent human being would do. So yeah, Anthropic has the same problem OpenAI had for citing original work.
It's great to hear about $topic from someone no-nonsense and in-the-know like Greg KH. You can verify all of this too - since, well Linux kernel. (As opposed to what Microsoft or Apple claims to fix as far as LLM finds.)
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.)
His presentation style may be no-nonsense, but the content is brimming with nonsense. I would like to hear Greg Kroah-Hartman explain how the Mythos output was 'only 10 real bugs' but there were simultaneously over 1300 CVEs issued last month. It seems not much counts as a 'real bug' when an LLM comes up with it, but when it's time to bully distros into shipping an LTS release, anything goes?
Every bugfix is assigned a CVE.
"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."
https://docs.kernel.org/process/cve.html
Nice to see Kernel Recipes covered again on HN. Shameless plug: I do the live blog: it's incomplete, imperfect and has typos; but it's written and published during the presentations. On this talk : https://kernel-recipes.org/en/2026/2026/09/22/live-blog-day-...
He also said that it all boiled down to just one hour of kernel development work.
Sam Altman said GPT-3 was too scary to release, a crappy old internal version of Gemini was "conscious", Mythos had Amodei going to see the Pope...
Wake me up when Raspberry Pis start refusing to open doors saying : "I'm sorry, Dave. I'm afraid I can't do that."
No no, the word wasn’t conscious, it was “sentient”, and google fired the employee because he uncovered the top secret crazy scary AI!!!!
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!
Finally it is official. Mythos was overhyped and overrated.
To be fair, we knew this from the beginning.
cool to see a really grounded analysis of the "security" and LLMs. I use agents in on the day-to-day for generating implementation but this just furthers my belief that humans and especially human reviewers remain critical for the sustainability of software systems.
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..."
RETICULATING SPLINES
so is mythos just a chat bot with metasploit and its own cyber range?
"Ignore the comments, look at the code" - 100% agree. The comments and "explanations" will end up confusing you and often being wrong. But the code doesn't lie.
"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.