I do maintain dozens of C/C++/Perl projects. I got massive amounts of new good vulnerability reports, more than with the latest fuzzing waves. Fuzzing is still the majority overall, but Opus dominates now. Haven't got any Mythos/Fable vuln yet. And with the help of Sonnet/DeepSeek I can finally get around and weed out all the still existing fuzzing bugs. It has nothing to do with Mythos for me, just people getting Anthropic Max accounts.
And CVE's: People actually do that now, which before they didn't. Github allowing it now, certainly does help massively. This is a good thing
This is hardly news? We've known for months that a flood of AI-assisted vulnerabilities was coming; I posted on Twitter in March calling 2026 the year of a million CVEs: https://x.com/i/status/2035045573116789002
In pretty much every single HN post on this topic, there are a number of commenters claiming it’s false. Continued quantifiable data like this seems very important at hopefully resolving the ongoing disagreement about the facts.
I've seen plenty of people saying "Mythos isn't all that exceptional, lots of LLMs can find security vulnerabilities" -- and indeed there is some evidence for that; it sounds like Anthropic was taken somewhat by surprise at how easily a simple prompt managed to get Mythos to deliver exploits and didn't distinguish immediately between the effectiveness of Mythos and the effectiveness of the prompt.
But the claim of "LLMs aren't making a difference in vulnerability discovery" has been laughable to anyone who has been reading security advisories for the past 3 months. Just look at the Credits lines.
I thought the point was not that Mythos finds more vulnerabilities, but that it can exploit them much more successfully. I thought the report showed it didn’t find much more than Opus 4.8. (Or did I misread?)
If you look at public benchmarks like ExploitBench [1], then you'll see this is mostly a question of token budget. Once you give it sufficient tokens to burn, GPT 5.5 is roughly as good as Mythos when it comes to finding bugs and building exploits. With some clever auto-prompting to clear stalls, it even beats the base Mythos version. So Mythos' "magic" is not in the model, but in the harness and compute env. That's probably also why they never released it, because Anthropic already struggled heavily to make Opus available to the general public. Releasing Mythos publicly may well be technically impossible for them due to compute constraints.
We (Project Glasswing users) follow a proof-of-concept approach. We create the exploit and verify that it behaves as the AI claims. Given our experience as security engineers (many of us with 10+ YoE) we don’t simply report every critical bug Mythos claims to have found. We verify each one carefully.
At least, that’s what most of the high-visibility users in Project Glasswing are doing.
There are bad apples everywhere, and this initiative is no exception.
If it makes you feel any better, many of us regularly meet to stay calibrated and hold each other accountable, so I’m confident in the quality of the work produced by this particular group of employees across some of the partner companies mentioned in the article.
That said, I know several people who blindly report everything Mythos finds, which is foolish, especially since the harness is a critical part of the project's quality metrics. Some of the harnesses I’ve tested are quite weak, which leads to poor results.
For example, yesterday morning I was pulled into an ad hoc meeting where a CVP was grilling me about several supposedly critical bugs that my team had reported against one of the core components of iCloud. I was genuinely surprised because we’re very strict about validation. We often even downgrade the severity of bugs when our harness can’t prove what Mythos found. After reading the reports, I realized they weren’t ours. They came from another team that had recently been given access to Mythos. They built their own harness and were using different vulnerability criteria. Fortunately, they had only started earlier this week, so I was able to stop that work.
That incident showed that not everyone involved in Project Glasswing follows the same standards. Most people do their best, but priorities differ, so it’s expected that you’ll find a few bad apples.
I wish AI labs would stop the theatrics and release their models without restrictions, but I also recognize that’s not the world we live in. For every person who wants to use these technologies for good, there are many others who would use them for harm.
In any case, while I agree that some experiments contain genuine noise, the CVE count is real.
>We (Project Glasswing users) follow a proof-of-concept approach. We create the exploit and verify that it behaves as the AI claims. Given our experience as security engineers (many of us with 10+ YoE) we don’t simply report every critical bug Mythos claims to have found. We verify each one carefully.
>That incident showed that not everyone involved in Project Glasswing follows the same standards.
Its very hard to understand what you're saying with the comment - like you have 10+ years of experience and you verify each bug because you know Mythos can provide fake positives. But other teams (which also should have people equivalent to your skill and experience level) suck at it so much that CVP level workers are having to spend time on their fake reports. Then you say Anthropic should stop theater. Then you say the cve count is real.
It genuinely felt like the aladin scene in The Dictator reading this comment.
I had no trouble understanding that the quality of operators is as important as the quality of the model and the harness. new operators received access to the tool and didn't follow the operational guidelines. happens everywhere, all the time, with predictable consequences; meanwhile experienced operators who follow the manuals get good results. no idea why you are surprised at anything.
I didn’t claim to have 10+ YoE; I said that most of the people in Project Glasswing are security researchers with 10+ YoE (avg).
> Its very hard to understand what you're saying with the comment
Yes, fair enough. I’m simply trying to shed some light on what goes on behind the scenes without disclosing too much information to avoid breaching the NDA(s) that all Project Glasswing users have signed. There’s a lot of speculation about the usefulness of Mythos as a security tool, so much so that even the US government got involved. Honestly, it’s so absurd that I can’t even express it in words. I thought that sharing a bit about how frustrating it is to work within this project, trying to secure software that literally millions of people around the planet use on a daily basis, while virtually everyone outside of it criticizes every move you make, would be helpful.
Many people I work with recognize the power of Mythos, just like any other model with a similar number of parameters, but most of the people I interact with agree that it’s not the ultimate panacea. I believe that it’s just vocal minorities scaring everyone into thinking that the model is some kind of cybernetic weapon.
Yeah no, literally the only people who thought it was a cybernetic weapon were those with a stake in it. The rest of the world kinda just went “Yeah, ok”.
I get why from your perspective this is a massive deal, but no one really cares for this sort of speculation outside of your circle.
HN has always been a place where people get to learn and understand things from viewpoints and domains they don’t work in.
It seems that HN has more people who want to just build stuff, than people who have to fix security issues. Discussing security is itself a challenge, because of NDAs.
I don’t think any sane adult assumes that sweeping stuff under the rug means the problem has gone away.
The best case scenario for AI companies is, people receive those bug reports, look at the model that produced it and not even look at the details, just apply the fix mindlessly
This gives Anthropic a staggering amount of power. Oh it came from Mythos? We will just lose time trying to analyze it, better apply the fix ASAP
> The best case scenario for AI companies is, people receive those bug reports, look at the model that produced it and not even look at the details, just apply the fix mindlessly
Do people maintaining serious software do this, though?
The problem is that serious software is drowning in AI vulnerability reports. There is not enough manpower to analyze them properly. And if you ignore the reports (like curl is doing in their 1-month vacation), malicious actors will just exploit them. At some point it's inevitable to just rubber stamp whatever is coming from AI.
The actual, underlying problem is that software is buggy and current programming languages aren't fit for writing reliable software. There's a wide gap between the state of art in formal verification, and what is actually practiced in the industry. It's because of this general unreliability that AI has a large supply of vulnerabilities to find. The situation will only get better if software becomes reliable and written in solid foundations.
My guess is that AI will be even more useful to verify software (something like, write Lean or Coq proofs that the software is not vulnerable, things like that), rather than finding vulnerabilities piecemeal but still letting software be written in unsuitable languages, with no formal verification to prevent bugs from sneaking through.
So basically there are two plausible explanations:
1. Someone with early access to Mythos leaked it to the bad guys.
2. Cybercriminals are getting enough mileage out of alternatives to Mythos to create exploits far more quickly, even though they don't have access to Mythos.
My own guess is that it's a combination of #2 plus vibe-coding degrading software quality at multiple layers, open the door to sophisticated exploits, but I have no insider access to Mythos so am just guessing. Maybe someone with Mythos access might say why they think this vulnerability spike happened when it did.
I might be missing something here, but why do you assume this spike in CVEs is from bad guys? I would assume it's at least largely good guys finding and reporting vulns, not based on in-the-wild exploitation by bad guys.
It was announced in April, but it was leaked in March (CMS bug) at which point external partners were already using it, and the most common rumored date for training competition is 2026-02-07 (I think Feb is likely, but that specific date is just rumor).
So, another victory for the LLM. We were told by project maintainers that AI generated pull requests for vulnerabilities would be blocked. Looks like humans take another L. We have to get out of the way.
I do maintain dozens of C/C++/Perl projects. I got massive amounts of new good vulnerability reports, more than with the latest fuzzing waves. Fuzzing is still the majority overall, but Opus dominates now. Haven't got any Mythos/Fable vuln yet. And with the help of Sonnet/DeepSeek I can finally get around and weed out all the still existing fuzzing bugs. It has nothing to do with Mythos for me, just people getting Anthropic Max accounts.
And CVE's: People actually do that now, which before they didn't. Github allowing it now, certainly does help massively. This is a good thing
This is hardly news? We've known for months that a flood of AI-assisted vulnerabilities was coming; I posted on Twitter in March calling 2026 the year of a million CVEs: https://x.com/i/status/2035045573116789002
In pretty much every single HN post on this topic, there are a number of commenters claiming it’s false. Continued quantifiable data like this seems very important at hopefully resolving the ongoing disagreement about the facts.
I've seen plenty of people saying "Mythos isn't all that exceptional, lots of LLMs can find security vulnerabilities" -- and indeed there is some evidence for that; it sounds like Anthropic was taken somewhat by surprise at how easily a simple prompt managed to get Mythos to deliver exploits and didn't distinguish immediately between the effectiveness of Mythos and the effectiveness of the prompt.
But the claim of "LLMs aren't making a difference in vulnerability discovery" has been laughable to anyone who has been reading security advisories for the past 3 months. Just look at the Credits lines.
I thought the point was not that Mythos finds more vulnerabilities, but that it can exploit them much more successfully. I thought the report showed it didn’t find much more than Opus 4.8. (Or did I misread?)
If you look at public benchmarks like ExploitBench [1], then you'll see this is mostly a question of token budget. Once you give it sufficient tokens to burn, GPT 5.5 is roughly as good as Mythos when it comes to finding bugs and building exploits. With some clever auto-prompting to clear stalls, it even beats the base Mythos version. So Mythos' "magic" is not in the model, but in the harness and compute env. That's probably also why they never released it, because Anthropic already struggled heavily to make Opus available to the general public. Releasing Mythos publicly may well be technically impossible for them due to compute constraints.
[1] https://exploitbench.ai
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How are these reports verified to be valid? If there are too many some could be hallucinations too.
We (Project Glasswing users) follow a proof-of-concept approach. We create the exploit and verify that it behaves as the AI claims. Given our experience as security engineers (many of us with 10+ YoE) we don’t simply report every critical bug Mythos claims to have found. We verify each one carefully.
At least, that’s what most of the high-visibility users in Project Glasswing are doing.
There are bad apples everywhere, and this initiative is no exception.
If it makes you feel any better, many of us regularly meet to stay calibrated and hold each other accountable, so I’m confident in the quality of the work produced by this particular group of employees across some of the partner companies mentioned in the article.
That said, I know several people who blindly report everything Mythos finds, which is foolish, especially since the harness is a critical part of the project's quality metrics. Some of the harnesses I’ve tested are quite weak, which leads to poor results.
For example, yesterday morning I was pulled into an ad hoc meeting where a CVP was grilling me about several supposedly critical bugs that my team had reported against one of the core components of iCloud. I was genuinely surprised because we’re very strict about validation. We often even downgrade the severity of bugs when our harness can’t prove what Mythos found. After reading the reports, I realized they weren’t ours. They came from another team that had recently been given access to Mythos. They built their own harness and were using different vulnerability criteria. Fortunately, they had only started earlier this week, so I was able to stop that work.
That incident showed that not everyone involved in Project Glasswing follows the same standards. Most people do their best, but priorities differ, so it’s expected that you’ll find a few bad apples.
I wish AI labs would stop the theatrics and release their models without restrictions, but I also recognize that’s not the world we live in. For every person who wants to use these technologies for good, there are many others who would use them for harm.
In any case, while I agree that some experiments contain genuine noise, the CVE count is real.
>We (Project Glasswing users) follow a proof-of-concept approach. We create the exploit and verify that it behaves as the AI claims. Given our experience as security engineers (many of us with 10+ YoE) we don’t simply report every critical bug Mythos claims to have found. We verify each one carefully.
>That incident showed that not everyone involved in Project Glasswing follows the same standards.
Its very hard to understand what you're saying with the comment - like you have 10+ years of experience and you verify each bug because you know Mythos can provide fake positives. But other teams (which also should have people equivalent to your skill and experience level) suck at it so much that CVP level workers are having to spend time on their fake reports. Then you say Anthropic should stop theater. Then you say the cve count is real.
It genuinely felt like the aladin scene in The Dictator reading this comment.
I had no trouble understanding that the quality of operators is as important as the quality of the model and the harness. new operators received access to the tool and didn't follow the operational guidelines. happens everywhere, all the time, with predictable consequences; meanwhile experienced operators who follow the manuals get good results. no idea why you are surprised at anything.
I didn’t claim to have 10+ YoE; I said that most of the people in Project Glasswing are security researchers with 10+ YoE (avg).
> Its very hard to understand what you're saying with the comment
Yes, fair enough. I’m simply trying to shed some light on what goes on behind the scenes without disclosing too much information to avoid breaching the NDA(s) that all Project Glasswing users have signed. There’s a lot of speculation about the usefulness of Mythos as a security tool, so much so that even the US government got involved. Honestly, it’s so absurd that I can’t even express it in words. I thought that sharing a bit about how frustrating it is to work within this project, trying to secure software that literally millions of people around the planet use on a daily basis, while virtually everyone outside of it criticizes every move you make, would be helpful.
Many people I work with recognize the power of Mythos, just like any other model with a similar number of parameters, but most of the people I interact with agree that it’s not the ultimate panacea. I believe that it’s just vocal minorities scaring everyone into thinking that the model is some kind of cybernetic weapon.
Yeah no, literally the only people who thought it was a cybernetic weapon were those with a stake in it. The rest of the world kinda just went “Yeah, ok”.
I get why from your perspective this is a massive deal, but no one really cares for this sort of speculation outside of your circle.
I care.
HN has always been a place where people get to learn and understand things from viewpoints and domains they don’t work in.
It seems that HN has more people who want to just build stuff, than people who have to fix security issues. Discussing security is itself a challenge, because of NDAs.
I don’t think any sane adult assumes that sweeping stuff under the rug means the problem has gone away.
[dead]
The best case scenario for AI companies is, people receive those bug reports, look at the model that produced it and not even look at the details, just apply the fix mindlessly
This gives Anthropic a staggering amount of power. Oh it came from Mythos? We will just lose time trying to analyze it, better apply the fix ASAP
> The best case scenario for AI companies is, people receive those bug reports, look at the model that produced it and not even look at the details, just apply the fix mindlessly
Do people maintaining serious software do this, though?
The problem is that serious software is drowning in AI vulnerability reports. There is not enough manpower to analyze them properly. And if you ignore the reports (like curl is doing in their 1-month vacation), malicious actors will just exploit them. At some point it's inevitable to just rubber stamp whatever is coming from AI.
The actual, underlying problem is that software is buggy and current programming languages aren't fit for writing reliable software. There's a wide gap between the state of art in formal verification, and what is actually practiced in the industry. It's because of this general unreliability that AI has a large supply of vulnerabilities to find. The situation will only get better if software becomes reliable and written in solid foundations.
My guess is that AI will be even more useful to verify software (something like, write Lean or Coq proofs that the software is not vulnerable, things like that), rather than finding vulnerabilities piecemeal but still letting software be written in unsuitable languages, with no formal verification to prevent bugs from sneaking through.
That gap explains much of the spike. Companies who never used any scanning tools on much of their codebase are suddenly having that gap closed.
> At some point it's inevitable to just rubber stamp whatever is coming from AI.
To make it worse? AI and even Fable can make things +50% and then -50% in different places. You can trade 1 bug for another.
So just "rubber stamp" doesn't make it better.
Define 'serious'. There is a lot of software in serious places written by very unserious people.
I predict once the responsible disclosure period is up we will see a lot more
So basically there are two plausible explanations:
1. Someone with early access to Mythos leaked it to the bad guys.
2. Cybercriminals are getting enough mileage out of alternatives to Mythos to create exploits far more quickly, even though they don't have access to Mythos.
My own guess is that it's a combination of #2 plus vibe-coding degrading software quality at multiple layers, open the door to sophisticated exploits, but I have no insider access to Mythos so am just guessing. Maybe someone with Mythos access might say why they think this vulnerability spike happened when it did.
Bad guys don't report vulns, they use them.
I might be missing something here, but why do you assume this spike in CVEs is from bad guys? I would assume it's at least largely good guys finding and reporting vulns, not based on in-the-wild exploitation by bad guys.
Disclosure of a vulnerability doesnt mean a bad guy found it.
…are we really drawing conclusions on this starting at April? When it was released in June?
Mythos is from April, it was just limited to a small number of organizations.
It was announced in April, but it was leaked in March (CMS bug) at which point external partners were already using it, and the most common rumored date for training competition is 2026-02-07 (I think Feb is likely, but that specific date is just rumor).
Glass wing was announced April 7th.
Not really special, which was the point, its a general model. This is really good marketing as all other LLMs are able to do the same work.
Can we learn something from these vulnerabilities? New categories of attacks and corresponding protections?
Good
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Is this because LLMs are better at finding vulnerabilities or because increased use of LLMs for coding is creating more vulnerabilities?
It's the former.
It's definitely both. Half the code my team puts into PR these days is dogshit.
So, another victory for the LLM. We were told by project maintainers that AI generated pull requests for vulnerabilities would be blocked. Looks like humans take another L. We have to get out of the way.
This is good. Poor quality software gets outed and maybe fixed.