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Six curl CVEs after OpenAI and Anthropic came back with zero
- anilgulecha 29d agoThat's bragging rights correctly earned, i think! As marketing-y as this post is, definitely something to keep an eye on.
- melvinroest 29d agoWow, this announcement is good content marketing. Don't get me wrong, it's interesting. But there is no technical discussion as to how they did it. It's simply: we did it and Mythos and Codex didn't. It's good to know that it's possible, but I'd have already expected it. Put a base model versus a base model + harness + whatever else, and yea, if you do it right then you have a better system to find vulnerabilities. > We then ran AISLE's autonomous AI system against curl. They don't even mention what models the use under the hood. It wouldn't surprise me if they are from Anthropic and OpenAI.
- drdrd 29d ago> what models the use under the hood Presumably their own, wouldn’t they?
- melvinroest 29d agoYou mean their own trained models, or do you think it's an open source model that they fine-tuned? If they use their own, I'd guess it's the latter.
- catlifeonmars 29d agoMaybe the model doesn’t matter, maybe you just need something minimally intelligent to seed the fuzzer, generate a test case, and rinse and repeat when the fuzzer gets stuck.
- vorticalbox 29d agoDefault to gpt 5.4 nano https://github.com/weareaisle/nano-analyzer/blob/main/scan.py#L43 https://github.com/weareaisle/nano-analyzer/blob/main/scan.p...
- tux3 29d agoThe homepage says something about AI guided fuzzing based on libfuzzer or AFL. Looks like they have the LLMs identify a bunch of interesting functions to test, generate some test harnesses, and then sort through the fuzzer findings at a high level, which sounds like a pretty good idea.
- melvinroest 29d agoThanks for figuring that out. Sort of sounds like AI programming programs to find vulnerabilities, of which fuzzing is one of the proven techniques to do it.
- bch 29d agoAlso sounds incredibly compute intensive.
- matherial 29d agoSetting a swarm of agents loose for hours to look for software vulnerabilities is far more compute-expensive than fuzzing. The industry has never thrown this kind of compute resources at pure fuzzing, in part because you can't get much VC money for that.
- lukeschlather 29d agoThis sounds like a swarm of agents with particular prompting that happens to guide the LLMs toward doing a lot of fuzzing, so it's not either/or; you're getting all the compute requirements of both.
- rcxdude 29d agoYou also quickly get into diminishing returns with fuzzing. Generally a bug is either going to be found relatively quickly with a given fuzzing approach or it's going to be nearly impossible to find. You're usually better coming up with more intelligent fuzzing approaches than you are just dumping compute into it.
- zamadatix 29d ago
- whizzter 29d agoTheir system can run with various models, they go into more details in this article. https://aisle.com/blog/system-over-model-zero-day-discovery-at-the-jagged-frontier https://aisle.com/blog/system-over-model-zero-day-discovery-...
- wky 29d agoIt wouldn’t surprise me if AISLE uses many different providers’ models, and what’s holding back OpenAI and Anthropic is only using first-party models. Just because OpenAI and Anthropic have arguably the strongest models overall doesn’t mean their models are the strongest at finding any given class of vulnerability or lead to follow.
- vorticalbox 29d agoIt defaults to gpt5.4 nano https://github.com/weareaisle/nano-analyzer/blob/main/scan.py#L43 https://github.com/weareaisle/nano-analyzer/blob/main/scan.p...
- bryanlarsen 29d agoA repo named "nano-analyzer" unsurprisingly uses gpt5.4 nano. I doubt their "pay them money" version uses nano.
- grumpy-swe-9000 29d agoI am pretty sure that the nano-analyzer is just a limited open source demo of their "System over Model" thesis from https://aisle.com/blog/system-over-model-zero-day-discovery-at-the-jagged-frontier https://aisle.com/blog/system-over-model-zero-day-discovery-..., not the main product.
- 1970-01-01 29d ago>All six are rated Low severity This says it all. Nothing important was missing. This is marketing hype.
- alephnerd 28d ago> Wow, this announcement is good content marketing. Why do you think companies hire PMMs?
- rwmj 29d agoWe had a few AISLE-generated security reports, and the signal to noise was reasonably good. The most notable bug/exploit their scanner found was: https://gitlab.com/nbdkit/libnbd/-/commit/e50bbd2681117c2dd8bb9f2b3f3105c7a9182f5a https://gitlab.com/nbdkit/libnbd/-/commit/e50bbd2681117c2dd8... The tool basically had to chain two exploits together to reach this. It also came up with a patch to fix which was fairly sensible (but I ended up editing it further for clarity).
- TechTechTech 29d agoGood marketing and definitive proof that local (read: on-prem & air-gapped) models with correct context and tools are good enough to perform on par and above SOTA cloud hosted solutions. We have seen this point many times before with different technologies. The first computers at university were big and expensive, same as this machine. Give it a few years and this functionality will be a commodity.
- Surac 29d agoMarketing Slop
- bluGill 29d agoOpenAI and Anthropic have both been studying CURL for a while though. Anything they found was already fixed. If you want to compare you need to start with something that none of studied. Somebody please take the source to a 2023 release of CURL (It shouldn't be hard to find one) - before all the current AI craze, and run all the tools on them to see what they find. Only then can we compare numbers. (and even then severity may come into place - all 6 are rated low impact)
- thih9 29d agoI guess this would also require models trained on pre-2023 data - or not trained on later curl code, changelogs, blog posts discussing curl security fixes, etc.
- goobreee 29d agoi 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)
- thih9 28d agoThat’s my point too.
- zamadatix 29d ago"How many total vulnerabilities can your tool alone identify?" and "How many unique vulnerabilities can your tool identify?" are both valid comparisons to make IMO.
- bluGill 29d agoBut that isn't what happened! Mythos has found issues in the past - which are now fixed (or so we should assume, I didn't verify but curl is very good about fixing issues). At most we can say the current version of mythos isn't better than the last version (a new version of mythos was just released, I'm not sure if that was even the one used in this scan)
- guptadagger 29d agoThis is an ad. I didn't learn anything from reading it.
- markasoftware 29d agoSince AISLE reported 29 issues but only 6 warranted a CVE, and all the found CVEs were "low" severity, this makes me wonder if AISLE simply is tuned for a higher false positive rate than the anthropic and openai tools (which may have found the same 6 issues and decided not to report them)
- goobreee 29d agoi 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-vulnerability/ 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
- fweimer 29d agoAs far as I understand it, the other efforts have not reported most of their findings to upstream developers, focusing on critical findings only. This is understandable because upstream interactions at scale are difficult.
- zamadatix 29d agoIn the case of big projects like curl the interaction seems a bit more complete. E.g. There are some other blog posts about how the engagements and reviews worked which go decently beyond a pre-filtered dump of high severity CVE claims appearing out of the blue.
- graemep 29d agoCurl seems to becoming one of the favourite things to demo AI finding vulns. Curl is going to end up incredibly secure.
- pixl97 29d agoThank goodness because curl is a load bearing structure to the backend of the internet.
- bluGill 29d agoCurl has a well earned reputation for high quality code. If you find something there it means you are good. There is a lot of software where finding a vulnerability mostly means you bothered to look and are not completely stupid. Nobody is going to be impressed if you find an issue with something that everybody already knows is poorly coded.
- mynameisash 29d ago> Curl has a well earned reputation for high quality code. SQLite also has a very good reputation. I vaguely recall hearing about one SQLite vulnerability discovered via AI, but I thought it turned out to be a nothingburger. A quick search turned up CVE-2025-6965[0,1], published on 2025-07-15, which affects SQLite < 3.50.2 (versions published before 2025-05-29[2]). I'm not much of a security nerd, but my naive reading of this implies that it was already known and fixed as of the time of the CVE; in other words, the AI discovery didn't seem particularly helpful (though one could argue that it did successfully discover a CVE). Has AI found many/any other vulnerabilities in SQLite? [0] https://cybersecuritynews.com/sqlite-0-day-vulnerability/ https://cybersecuritynews.com/sqlite-0-day-vulnerability/ [1] https://nvd.nist.gov/vuln/detail/cve-2025-6965 https://nvd.nist.gov/vuln/detail/cve-2025-6965 [2] https://sqlite.org/releaselog/3_50_2.html https://sqlite.org/releaselog/3_50_2.html
- bluGill 29d agoHard to say what AI has been used in SQLite unless someone is talking. My impression is the maintainer doesn't talk about this type of thing much, but maybe I'm wrong.
- _pdp_ 29d agoI like the looks of Aisle and what they stand for... That being said you cannot compare a model with a specialised harness. These are two completely different things. Am I missing something?
- goobreee 29d agoi 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 https://www.anthropic.com/research/mythos-preview
- tosti 29d agoOne does not "discover" a CVE like this. To discover a CVE would mean you searched for a particular piece of software and found it vulnerable according to the NVD. That's not a novel discovery by any means. What they did is they found bugs and that they were exploitable in certain edge cases. As the bugs turned out to be vulnerabilities, they were assigned a CVE in the NVD with low severity. IMHO Aisle stockedpiled too much in the marketing shelves.
- grumpy-swe-9000 29d agoWhat would the correct terminology actually be here I wonder?
- tosti 29d agoIn short, they found vulnerabilities and each have been assigned CVEs.
- jmartrican 29d agoThe gauntlet has been thrown. Will Anthropic or OpenAI pick it up?
- jmartrican 29d ago"your LLM is cool, but can it find vulns in curl"
- dec0dedab0de 29d agoGiven enough AIballs all bugs are shallow
- blmarket 29d agoI also have some secret recipe finding one class of bugs: https://github.com/tmux/tmux/issues?q=is%3Apr%20author%3Ablmarket%20state%3Aclosed https://github.com/tmux/tmux/issues?q=is%3Apr%20author%3Ablm... curious they're willing to run AISLE on tmux to find more than mine.
- janaagaard 29d agoVery unrelated to the content of the article, but that is a pretty weird ft ligature in the heading. It looks a letter from another alphabet. Which maybe makes this pretty cool after all.
- RamblingCTO 28d agoIt's a very unfortunate ligature imho because there is no distinction between f and t. Looks funky PS: the image in the background looks like a nod to David vs Goliath, love that detail