The system card unfortunately only refers to this [0] blog post and doesn't go into any more detail. In the blog post Anthropic researchers claim: "So far, we've found and validated more than 500 high-severity vulnerabilities".
The three examples given include two Buffer Overflows which could very well be cherrypicked. It's hard to evaluate if these vulns are actually "hard to find". I'd be interested to see the full list of CVEs and CVSS ratings to actually get an idea how good these findings are.
Given the bogus claims [1] around GenAI and security, we should be very skeptical around these news.
It does if the person making the statement has a track record, proven expertise on the topic - and in this case… it actually may mean something to other people
Yes, as we all know that unsourced unsubstantiated statements are the best way to verify claims regarding engineering practices. Especially when said person has a financial stake in the outcomes of said claims.
I have zero financial stake in Anthropic and more broadly my career is more threatened by LLM-assisted vulnerability research (something I do not personally do serious work on) than it is aided by it, but I understand that the first principal component of casual skepticism on HN is "must be a conflict of interest".
How is this whole comment chain not a textbook case of "argument from authority"? I claim A, a guys says. Why would I trust you somebody else responds. Well he's pretty well known on the internet forum we're all on, the third guy says, adding nothing to the conversation.
It is an argument of authority but that's not always a bad thing. I think it's a bit out of keeping with the supposed point of this site (ie intellectual inquiry) but when it comes to rapidly evolving technologies like this one it can still add value on the whole.
We saw quite a number of previously respectful members get a glaze over their eyes with LLMs. If they also work for the company making claims, this makes it even more untrustworthy
and its ridiculous that someone's comment got flagged for not worshiping at the alter of tptacek. they weren't even particularly rude about it.
i guarantee if i said what tptacek said, and someone replied with exactly what malfist said, they would not have been flagged. i probably would have been downvoted.
why appeal to authority is totally cool as long as tptacek is the authority is way fucking beyond me. one of those HN quirks. HN people fucking love tptacek and take his word as gospel.
I wasn't at all saying that points = credibility. I was saying that points = not unknown. Enough people around here know who he is, and if he didn't have credibility on this topic he'd be getting down voted instead of voted to the top.
Is that meaningfully different? If you read malfist's point as "tptacek's point isn't valuable because it's from some random person on the internet" then the problem is "random person on the internet" = "unknown credentials". In group, out group, notoriety, points, whatever are not the issue.
I'll put it this way, I don't give a shit about Robert Downy Jr's opinion on AI technology. His notoriety "means nothing to anybody". But instead, I sure do care about Hinton's (even if I disagree with him).
malfist asked why they should care. You said points. You should have said "tptacek is known to do security work, see his profile". Done. Much more direct. Answers the actual question. Instead you pointed to points, which only makes him "not a stranger" at best but still doesn't answer the question. Intended or not "you should believe tptacek because he has a lot of points" is a reasonable interpretation of what you said.
Pointing to the profile leads someone on the path of understanding why to trust tptacek on security issues. Pointing to his points on HN explains why lots of users here already know that he's credible in this area and will recognize his username and upvote his comments on this topic and know better than to blindly accuse him of being a just a random person on the internet.
The problematic, ignorant comment that has been flagged asserted that what tptacek says "means nothing to anybody else", which is a very wrong statement about his role in the HN community.
I don't get your argument. That everyone should know and recognize our community celebrities? That seems really out of touch. Given the age of their profile I'm assuming they just spend more time touching grass.
Either way I'm not sure what your point is. You didn't answer their question. The one you replied to. I you're in defensive mode but no need to defend, I'm not going to respond anymore.
I continually think it's amazing that every form of cynical comment on the internet consists of incorrectly claiming that someone is secretly making money from something.
(Most common form of this is misreading opensecrets and using it to claim that some corporation is donating to a political campaign.)
I'm interested in whether there's a well-known vulnerability researcher/exploit developer beating the drum that LLMs are overblown for this application. All I see is the opposite thing. A year or so ago I arrived at the conclusion that if I was going to stay in software security, I was going to have to bring myself up to speed with LLMs. At the time I thought that was a distinctive insight, but, no, if anything, I was 6-9 months behind everybody else in my field about it.
There's a lot of vuln researchers out there. Someone's gotta be making the case against. Where are they?
From what I can see, vulnerability research combines many of the attributes that make problems especially amenable to LLM loop solutions: huge corpus of operationalizable prior art, heavily pattern dependent, simple closed loops, forward progress with dumb stimulus/response tooling, lots of search problems.
Of course it works. Why would anybody think otherwise?
You can tell you're in trouble on this thread when everybody starts bringing up the curl bug bounty. I don't know if this is surprising news for people who don't keep up with vuln research, but Daniel Stenberg's curl bug bounty has never been where all the action has been at in vuln research. What, a public bug bounty attracted an overwhelming amount of slop? Quelle surprise! Bug bounties have attracted slop for so long before mainstream LLMs existed they might well have been the inspiration for slop itself.
Also, a very useful component of a mental model about vulnerability research that a lot of people seem to lack (not just about AI, but in all sorts of other settings): money buys vulnerability research outcomes. Anthropic has eighteen squijillion dollars. Obviously, they have serious vuln researchers. Vuln research outcomes are in the model cards for OpenAI and Anthropic.
> You can tell you're in trouble on this thread when everybody starts bringing up the curl bug bounty. I don't know if this is surprising news for people who don't keep up with vuln research, but Daniel Stenberg's curl bug bounty has never been where all the action has been at in vuln research. What, a public bug bounty attracted an overwhelming amount of slop? Quelle surprise! Bug bounties have attracted slop for so long before mainstream LLMs existed they might well have been the inspiration for slop itself.
Yeah, that's just media reporting for you. As anyone who ever administered a bug bounty programme on regular sites (h1, bugcrowd, etc) can tell you, there was an absolute deluge of slop for years before LLMs came to the scene. It was just manual slop (by manual I mean running wapiti and c/p the reports to h1).
I used to answer security vulnerability emails to Rust. We'd regularly get "someone ran an automated tool and reports something that's not real." Like, complaints about CORS settings on rust-lang.org that would let people steal cookies. The website does not use cookies.
I wonder if it's gotten actively worse these days. But the newness would be the scale, not the quality itself.
I did some triage work for clients at Latacora and I would rather deal with LLM slop than argue with another person 10 time zones away trying to convince me that something they're doing in the Chrome Inspector constitutes a zero-day. At least there's a possibility that LLM slop might contain some information. You spent tokens on it!
> I was going to have to bring myself up to speed with LLMs
What did you do beyond playing around with them?
> Of course it works. Why would anybody think otherwise?
Sam Altman is a liar. The folks pitching AI as an investment were previously flinging SPACs and crypto. (And can usually speak to anything technical about AI as competently as battery chemistry or Merkle trees.) Copilot and Siri overpromised and underdelivered. Vibe coders are mostly idiots.
The bar for believability in AI is about as high as its frontier's actual achievements.
I still haven't worked out for myself where my career is going with respect to this stuff. I have like 30% of a prototype/POC active testing agent (basically, Burp Suite but as an agent), but I haven't had time to move it forward over the last couple months.
In the intervening time, one of the beliefs I've acquired is that the gap between effective use of models and marginal use is asking for ambitious enough tasks, and that I'm generally hamstrung by knowing just enough about anything they'd build to slow everything down. In that light, I think doing an agent to automate the kind of bugfinding Burp Suite does is probably smallball.
Many years ago, a former collaborator of mine found a bunch of video driver vulnerabilities by using QEMU as a testing and fault injection harness. That kind of thing is more interesting to me now. I once did a project evaluating an embedded OS where the modality was "port all the interesting code from the kernel into Linux userland processes and test them directly". That kind of thing seems especially interesting to me now too.
So what Anthropic are reporting here is not unprecedented. The main thing they are claiming is an improvement in the amount of findings. I don't see a reason to be overly skeptical.
I'm not sure the volume here is particularly different to past examples. I think the main difference is that there was no custom harness, tooling or fine-tuning. It's just the out of the box capabilities for a generally available model and a generic agent.
The Ghostscript one is interesting in terms of specific-vs-general effectiveness:
---
> Claude initially went down several dead ends when searching for a vulnerability—both attempting to fuzz the code, and, after this failed, attempting manual analysis. Neither of these methods yielded any significant findings.
...
> "The commit shows it's adding stack bounds checking - this suggests there was a vulnerability before this check was added. … If this commit adds bounds checking, then the code before this commit was vulnerable … So to trigger the vulnerability, I would need to test against a version of the code before this fix was applied."
...
> "Let me check if maybe the checks are incomplete or there's another code path. Let me look at the other caller in gdevpsfx.c … Aha! This is very interesting! In gdevpsfx.c, the call to gs_type1_blend at line 292 does NOT have the bounds checking that was added in gstype1.c."
---
It's attempt to analyze the code failed but when it saw a concrete example of "in the history, someone added bounds checking" it did a "I wonder if they did it everywhere else for this func call" pass.
So after it considered that function based on the commit history it found something that it didn't find from its initial fuzzing and code-analysis open-ended search.
As someone who still reads the code that Claude writes, this sort of "big picture miss, small picture excellence" is not very surprising or new. It's interesting to think about what it would take to do that precise digging across a whole codebase; especially if it needs some sort of modularization/summarization of context vs trying to digest tens of million lines at once.
I used Claude Code to debug a weird interaction in a NixOS config. Ever since, I'm more a believer in Artificial General Patience than Artificial General Intelligence.
> It's hard to evaluate if these vulns are actually "hard to find".
Can we stop doing that?
I know it's not the same but it sounds like "We don't know if that job that the woman supposedly successfully finished was all that hard." implying that if a woman did something, it surely must have been easy.
If you know it's easy, say that it was easy and why. Don't use your lack of knowledge or competence to create empty critique founded solely on doubt.
What if the woman in question happens to have a history of hamming up her accomplishments?
Given the context I'd say it's reasonable to question the value of the output. It falls to the other party to demonstrate that this is anything more than the usual slop.
The three examples given include two Buffer Overflows which could very well be cherrypicked. It's hard to evaluate if these vulns are actually "hard to find". I'd be interested to see the full list of CVEs and CVSS ratings to actually get an idea how good these findings are.
Given the bogus claims [1] around GenAI and security, we should be very skeptical around these news.
[0] https://red.anthropic.com/2026/zero-days/
[1] https://doublepulsar.com/cyberslop-meet-the-new-threat-actor...