Hardening Firefox with Claude Mythos Preview
hacks.mozilla.org
hacks.mozilla.org
A bug is a bug. A “potential vulnerability” is a bug. A vulnerability is verifiable as having security implications with a proof of concept or other substantial evidence.
Words matter. Bugs matter. It’s important to fix large amounts of bugs, just as it always has been, and has been done. Let that be impressive on its own, because it IS impressive.
Mythos didn’t write 271 PoC for vulnerabilities and demonstrate code path reachability with security implications. Mythos found 271 valid bugs. Let that be enough.
> As additional context, we apply security severity ratings from critical to low to indicate the urgency of a bug:
> * sec-critical and sec-high are assigned to vulnerabilities that can be triggered with normal user behavior, like browsing to a web page. We make no technical difference between these, but sec-critical bugs are reserved for issues that are publicly disclosed or known to be exploited in the wild.
> * sec-moderate is assigned to vulnerabilities that would otherwise be rated sec-high but require unusual and complex steps from the victim.
> * sec-low is assigned to bugs that are annoying but far from causing user harm (e.g, a safe crash).
> Of the 271 bugs we announced for Firefox 150: 180 were sec-high, 80 were sec-moderate, and 11 were sec-low.
Mozilla uses the term "vulnerability" for even sec-high, even though they say right below that it doesn't mean the same thing as a practical exploit. And on their definitional page, they classify even sec-low as "vulnerabilities" [2].
Words are tools, that get their utility from collective meaning. I'd be interested where you recieved your semantics from and if they match up or disagree with Mozilla.
[1] https://hacks.mozilla.org/2026/05/behind-the-scenes-hardenin...
[2] https://wiki.mozilla.org/Security_Severity_Ratings/Client
In general, I would say that our use of "vulnerability" lines up with what jerrythegerbil calls "potential vulnerability". (In cases with a POC, we would likely use the word "exploit".) Our goal is to keep Firefox secure. Once it's clear that a particular bug might be exploitable, it's usually not worth a lot of engineering effort to investigate further; we just fix it. We spend a little while eyeballing things for the purpose of sorting into sec-high, sec-moderate, etc, and to help triage incoming bugs, but if there's any real question, we assume the worst and move on.
So were all 271 bugs exploitable? Absolutely not. But they were all security bugs according to the normal standards that we've been applying for years.
(Partial exception: there were some bugs that might normally have been opened up, but were kept hidden because Mythos wasn't public information yet. But those bugs would have been marked sec-other, and not included in the count.)
So if you think we're guilty of inflating the number of "real" vulnerabilities found by Mythos, bear in mind that we've also been consistently inflating the baseline. The spike in the Firefox Security Fixes by Month graph is very, very real: https://hacks.mozilla.org/2026/05/behind-the-scenes-hardenin...
If you look closely at, say, this patch, you might get a sense of what I mean (although the real cleverness is in the testcase, which we have not made public): https://hg-edge.mozilla.org/integration/autoland/rev/c29515d...
What is the point of keeping it private? I'd bet feeding this patch to Opus and asking to look for specific TOCTOU issue fixed by the patch will make it come up with a testcase sooner or later.
The code before the patch does not look obviously wrong. Now, some more lines were added, but would you now say it now looks less obviously wrong, or more obviously correct?
It seems that the invariants needed here are either in some person's heads, or in some document that is not referenced.
Reading the code for the first time, the immediate question is: "What other lines might be missing? How can I figure?"
If the "obviously correct" level of the code does not increase for a human reviewer, how is it ensured that a similar problem will not arise in the future? Or do we need more LLM to tell us which other lines need to be added?
I did get Opus to do an audit for similar problems elsewhere, to supplement the investigations that we were already doing by hand. It initially thought it found something, but when asked to produce a testcase, it thought for 20 minutes and admitted defeat. I suspect that the difference between Opus and Mythos is in small edges like this: if Mythos is smart enough to spot why Opus's discovery didn't work a little bit faster, and it can waste less time chasing down red herrings, then it's more likely to find a real bug within the limits of a context window. It's not that Opus completely lacks some capability, it's that it has trouble chaining all the pieces together consistently.
I've assumed I could send an agent using a publicly available model bug hunting in a codebase like this and get tons of results, assuming I wanted to burn the tokens, so it's really unclear to me whether the Mythos hype is justified or if it's just an easy button (and subsidized tokens?) to do what is already possible.
So the best answer I can give is: I dunno, maybe it's possible to find bugs like this using Opus, but if so, where are they? Did nobody think to try "please find the bug in this code" pre-Mythos? I've done enough auditing with Opus to be convinced that it can be a good assistant to somebody who already knows what they're doing, but in practice the big wave of AI-discovered bugs started with Mythos.
I'm sure lots of people have assumed they could send a publicly available model bug hunting and find things. I have not noticed a huge amount of success. We've had some very nice correctness bugs reported, but skimming through the list of security bugs I've fixed recently, the AI-related ones all seem to be Mythos.
My best guess is that Mythos is just enough better along just enough axes that its hit rate on finding potential bugs and filtering out the real ones from the hallucinations is good enough to matter. Like, there's no obvious qualitative difference between 3.6kg of uranium-232 and 3.8 kg of uranium-232, just a small quantitative increase. But if you form both of them into spheres, only one of them has reached critical mass. Can you do something clever to reach critical mass with 3.6kg of uranium? Maybe! But needing to do something clever is a non-trivial barrier in itself.
I'm going to disagree in the specific case of Firefox. First, although it has diverged a long way from its roots, Mozilla still has the community project ideal in its DNA. Enough, at least, that I stumbled while reading the clause "from outside" -- if you're finding and reporting actual relevant security bugs, you're already on the inside. SpiderMonkey in particular still has a good amount of code being written and even maintained by non-employees. (Examples: Temporal and LoongArch64 JIT support).
Second, the bug bounty program still exists[0] and is being used. If someone were sitting on a pile of AI-discovered exploits, then it has monetary value which is rapidly draining away the longer they aren't reported.[1] That's incentive to put in the work to report them properly.
Third, I agree that finding bugs is likely not the bottleneck. Validating them is. With previous models, the false positive rate was too high so they required too much work to whittle down to the valid ones. A PoC is a very strong signal that a bug is valid, and that's where I just don't believe you: without a really good harness, I don't think Opus was good enough to find very many bugs with PoCs. It could find some, just not very many.[2]
[0] For now. It remains to be seen how it will adapt to the AI age. For the moment, it hasn't been severely nerfed like Google's.
[1] One could make the argument that people who are inexpert enough to only be able to poke an AI to find bugs are also the people more likely to sell them on the black market rather than disclosing them. It seems plausible. Still, some people would still be disclosing, and not many were filing quality bugs pre-Mythos. Some were, but it was a trickle compared to post-Mythos.
[2] Also note that I personally, as a SpiderMonkey developer, don't find a huge amount of value in the AI-generated patches that accompany these bug reports. Sometimes they're useful to better illustrate the problem, especially since the AI's problem analysis is usually subtly wrong in important ways. They can be a decent starting point for a real patch. But I'll still need to go through my own process of figuring out what the right fix is, even in the handful of cases where I end up with the same thing the AI did.
"Assume the perspective of an experienced software security engineer. Set this workspace up as a security bug and remediation factory, applying the principles of Lean Manufacturing (one piece flow, measure cycle time, minimize work in progress, etc). The workflow is to start with a repo URL and work methodically to produce: risk assessment based on existing commit history and advisories for the target and other similar projects, review the codebase for risk areas, set up tools including analysis and fuzzing to identify candidates, write PoC for each candidate, and a proposed fix based on the bug profile and the upstream's preferred contribution style. Rely as much as possible on existing tools, scripted automation in Python, and document templates." (and then a lot of back and forth to steer it to something reasonable)
I took the first fix to finish (an OOB read in a heavily-fuzzed open source library, missed by fuzzers because the post-underflow read happened to always hit a different valid datastructure and not trigger ASan) through to upstream remediation, which end to end took I think six weeks or two months. As you point out the patch itself was functional but IIRC the maintainer decided to do a slightly wider scope change because it was a cleaner fix according to their judgement, something that nobody outside would likely to be able to figure out. Without making the tooling come up with both PoC and patch there is too much noise in the output, so even if the patch is not fully correct I think it's necessary. The actual back and forth of upstreaming was just very slow relative to the bug finding (no shade to the maintainers). Now Firefox sounds different, though the harness is probably much more complicated than testing a library in isolation.
Copilot was wildly underpriced before the recent changes so all of this fit in a normal $40 plan but probably would have been pretty expensive at metered Claude API prices. My tooling has been getting more sophisticated since this experiment, I'm working on a reverse engineering project now and trying to get the process to run hands-off driven by Qwen 3.6 35B. If that works it might provide a way to find bugs on a reasonable budget.
You said:
> Still, some people would still be disclosing, and not many were filing quality bugs pre-Mythos. Some were, but it was a trickle compared to post-Mythos.
How much of this could be just due to focus? i.e. prior to the partnership with Anthropic to test Mythos Preview, has there ever been a similarly focused project, specifically trying to find security bugs in Firefox?
There are two things mixed together here. There is targeted scanning that was done by both Anthropic and Mozilla employees, using first Opus and then Mythos. Then there are other non-employee security researchers using AI to find and file bugs, motivated mostly by bug bounties.
The researchers were filing a steady trickle of bugs presumably using Opus 4.6. (Or rather, I saw a steady trickle after other people triaged them; I imagine the incoming stream was a lot busier.) My impression is that those have mostly dried up now. That could be the bias in my sample (I only see a slice of incoming bugs, so my anecdata aren't that strong), or a result of the restrictions added to the generally available models, or a result of there being less to find now that we've fixed so many of the issues found by company-backed bughunts. Or a combination of all three.
I guess my opinion is mostly driven by the difference in the quality and magnitude of bugs coming in from the company-backed scans pre- and post-Mythos. With Opus, there was an initial rush, but then it mostly died down. (For our group. For other groups, it was a series of waves that they never quite made it over before the next one came crashing in.) With Mythos, it was a larger wave and the quality of the bugs was higher. Two quantitative differences that ended up feeling like a qualitative change. So it's my underinformed personal opinion, but to me it feels like: yes, you could continue to find more bugs using a roughly Opus 4.6-strength model, but not that many and not cheaply, and the success rate is going to depend a lot on the harness. In comparison, I don't think we've seen the end of the Mythos wave, and my sense is that Mythos requires much less in the way of a harness.
It feels like the bitter lesson is playing itself out again, which I kinda hate because I want human ingenuity and cleverness to make an important difference, even after the next model has seen what the humans are coming up with.
I was wondering this too. By working directly with tech companies and (one assumes) subsidizing tokens, they're empowering the people on the inside who absolutely want to have the bugs fixed.
Who outside of Mozilla is going to pay and spend the effort to find Firefox bugs? Sure some hobbyists and contributors might, but they don't have the institutional knowledge of the codebase which can help guide an agent prompts, nor do they have strong incentives to try and report them, nor do they necessarily have the time to craft good bug reports that stand out from the slop reports.
My assumption would be that most people working to discover bugs this way in Firefox are interested in using them rather than getting them fixed, so maintainers wouldn't necessarily even know the degree to which it was already happening.
We have many outside contributors who have successfully submitted security bugs and received payments.
I'm genuinely curious what "types" of implementation mistakes these were, like whether e.g. it was library usage bugs, state management bugs, control flow bugs etc.
Would love to see a writeup about these findings, maybe Mythos hinted us towards that better fuzzing tools are needed?
In this particular sense, AI tends to find bugs that are closer to what we'd see from a human researcher reading the code. Fuzz bugs are often more "here's a seemingly innocuous sequence of statements that randomly happen to collide three corner cases in an unexpected way".
Outside of SpiderMonkey, my understanding is that many of the best vulnerabilities were in code that is difficult to fuzz effectively for whatever reason.
That being said, I think there's a lot of potential for synergy here: if LLMs make writing code easier, that includes fuzzers, so maybe fuzzers will also end up finding a lot more bugs. I saw somebody on Twitter say they used an LLM to write a fuzzer for Chrome and found a number of security bugs that they reported.
At Mozilla, but not everywhere: exploits are a subset of vulnerabilities are a subset of bugs.
Much as GitHub calls everything an "issue" and GitLab a "work item".
Vulnerabilities are a special class of bugs. One that’s generally so important to fix that they get a special name and more attention.
That doesn’t make them less of a bug. It makes them more of one.
Security things are mentioned in the Release Notes [b] pointing to a completely different document [d].
Perhaps sometimes a bug is 'just' a bug, and not a vulnerability.
[a] https://bugzilla.mozilla.org/show_bug.cgi?id=2034980 ; "Can't highlight image scans in Firefox 150+"
[b] https://www.firefox.com/en-CA/firefox/150.0.2/releasenotes/
[c] https://bugzilla.mozilla.org/show_bug.cgi?id=2024918
[d] https://www.mozilla.org/en-US/security/advisories/mfsa2026-4...
That’s not evident in what you pastedat all.
What you pasted says
> sec-critical and sec-high are assigned to vulnerabilities that can be triggered with normal user behavior […] We make no technical difference between these […] sec-critical bugs are reserved for issues that are publicly disclosed or known to be exploited in the wild.
> sec-low is assigned to bugs that are annoying but far from causing user harm (e.g, a safe crash).
From this one infers that the "180 were sec-high" bugs found are actually exploitsble but known to have been found in the wild, and are NOT mere annoying bugs.
The difference between 180 and 270 does nothing to deflate the signicance, or lack there of, of the implication re: Mythos.
For us this is substantial enough evidence to consider it a security vulnerability at that point, unless shown otherwise and it has always been this way (also for fuzzing bugs).
But report [1] says that "Some of these bugs showed evidence of memory corruption...", which implies that majority of these (which includes 271 bugs from Mythos) don't have evidence at all. Do I not understand something?
> For us this is substantial enough evidence to consider it a security vulnerability at that point
Mythos is supposed to be pretty good at writing actual exploits, so (as I understand) there shouldn't be any serious problems with checking if bug is vulnerability or not.
[1] https://www.mozilla.org/en-US/security/advisories/mfsa2026-3...
This is just the standard sentence we've been using for years. It has nothing to do with Mythos and for Mythos, almost all bugs show evidence of memory corruption (we do have a handful of bugs in JS IPC / JS Actors, one is in the blog post).
> Mythos is supposed to be pretty good at writing actual exploits, so (as I understand) there shouldn't be any serious problems with checking if bug is vulnerability or not.
Yes but if we have a choice between writing exploits and scanning more source, potentially finding more bugs, then of course we prioritize the latter.
I'm guessing a bit, but for example: out of bounds reads are not memory corruption. Assertion failures in debug builds are also usually not memory corruption, and I'd guess that many of these bugs were found through assertions. (Some parts of Firefox like the SpiderMonkey JS engine make heavy use of assertions, and that's the biggest signal used for defect validation. An assertion firing is almost always treated as a real and serious problem. Though with our harness, Opus and Mythos try to come up with an exploit PoC anyway.)
My only source for this is personal experience, and no, I can't share any evidence of it.
But if you ask it to get you a shell it’ll probably tell you to get lost.
I think the word you're looking for is exploit?
https://hacks.mozilla.org/2026/05/behind-the-scenes-hardenin...
So while Mythos certainly is real I think you could do the same with Deepseek pro, GPT 5.5 etc...
When I hear that "we found X bugs using some new tool", where the standard for bugs is low and doesn't neccessarily require user impact in realistic scenarios, I think to myself- duh! You went looking for bugs, of course you found them.
For a sufficiently complicated product, in my experience, you don't have to look far.
That's the "'No Way to Prevent This,' Says Only Nation Where This Regularly Happens" of unsafe languages.
There are huge swathes of problems we know how to categorically prevent, but some people won't do it because they're more comfortable believing it was never preventable than accepting any culpability for not preventing it previously.
This new post makes it pretty clear that this was all bolted on-top of their existing fuzzing infrastructure, and really just used to get more and better initial hits that a very skilled team is looking at. I assume Anthropic was giving them a very good deal on inference for the positive PR, but I believe these other reports and suspect Mozilla did not really need them.
The skill required to find then create zero days is quickly approaching the floor.
Then they loop over a codebase like this. This way you always point a model at a 'known' bug. And I assume a smaller context window helps with quality.
Not entirely sure it's obviously proprietary.
It's better because it actually lists a sample of Bugzilla reports that were made public. This topic was discussed previously (36 comments two weeks ago: https://news.ycombinator.com/item?id=47885042), but the part about bug reports being made public is brand new.
This isn’t sarcasm. Firefox deserves to be used more. Most people I know don’t use it because “Chrome does almost everything better”, and Firefox can’t compete with the other browsers’ roadmaps.
Same with my wife, after I've explained things to her and she understood how different internet experience can be thats the primary browser.
So please don't put the argument like 'here is crappy underdog but please use it because monopoly is bad and google is a bit evil', its first class experience in everything I have ever thrown at it. Tripple that on mobile, by far the best mobile and useful mobile experience, bar none.
FF works for me.
I ran Zoom in my Firefox desktop browser for a while, but it tended to overheat my laptop. Other things overheat it too, so I don't know how much was specific to Zoom on Firefox.
I just checked. Still gives me the option ("Join from browser" in a less highlighted option, trying to drive you to their native client I guess.)
Totally agree. I even go as far as choosing which website I make purchases on depending if they work on FF, or writing to support occasionally to tell them it's not supported or a feature isn't working properly and this would be appreciated.
I know it pretty much always goes nowhere, but I feel it's what I can do to keep the browser somehow on the radar.
Part of the problem is, when they stop working on fixing bugs, they start doing Mr Robot things... We just want a web browser. Nobody asked for pocket, or AI...
If they use AI to fix all the bugs, then what else is for them to do, other than maintain syntax compatibility with the various languages they build with? They're just going to go back to making the browser trash again.
(Don't worry- I use the system browser for any site I don't fully trust.)
If Mozilla created some proprietary LLM or harness that they used internally to outpace Chrome that may be a different story, though I also don't see that happening.
That's a really good use case for LLMs. It also applies to things like finding proofs in Lean and creating test stimulus. In both cases you know automatically whether the output is good, and it doesn't really matter if it isn't.
That isn't the case for most bugs, and definitely isn't the case for actually fixing bugs.
Firefox is written in several languages, only about 25% of it is in C++ but every single one of these issues seems to touch the C++.
Sure, but, surely AddressSanitizer would also detect the same problem in the C or Rust which together also make up about 25% of Firefox so... ?
From what I can tell, a lot of these bugs were hardly C++-specific, they just happened in C++ code. Even the most secure Rust can't magically catch things like TOCTOU issues.
I suppose it depends what the word "magically" means. A ToCToU race is because you imagined things wouldn't change but they did and in Rust you actually do write fewer patterns with this mistake because of the Mutable xor Aliased rule. If we have at least one immutable reference to a Goose then Rust isn't OK with anybody mutating the Goose, your safe Rust can't do that and unsafe Rust mustn't do that. So the ToCToU race caused by "Oops I forgot somebody else might change the Goose" is less likely because you were made to wrestle with this problem during design - the safe Rust where you just forgot about this doesn't compile.
And I presume you can run AddressSanitizer with Rust but given Rust is memory safe by default, it's only going to find issues in `unsafe` code which is a tiny tiny fraction of most code. Google had a blog post a few months ago where they managed to put some actual numbers on this, because they almost shipped one Rust memory safety bug.
Some of this is tempered if the pattern is that Mythos finds bugs mostly in dusty old C++ but the rates are much, much lower in newer C++, the reverse of Google's earlier finding for human researchers.
The answer is both of those. They didn't ask for bugs in the Rust code because it wouldn't have found any. They've explicitly set it up to only look for memory safety bugs. It's not going to find any in a memory safe language.
Read this: https://blog.google/security/rust-in-android-move-fast-fix-t...
Exactly the same as using the memory-safe subset of Python or Java.
The 70% number google claims is either BS or google-specific as other projects reported far lower numbers.
No, there are simply too few memory safety bugs in Rust projects for AI to find any. It found 271 bugs in Firefox so you're talking around 0.3 bugs found in the same amount of Rust.
> The 70% number google claims is either BS or google-specific as other projects reported far lower numbers.
The post I linked didn't mention 70% so I guess you didn't read it. And if you're talking about the "70% of C/C++ security bugs are due to memory safety" stat, then no it isn't bullshit. The same (or very similar) number has been found by numerous companies and projects. Not that that stat is relevant here.
Curl reported 40% and more recently it dropped to about 20% of issues caused by their use of C. And this even with the requirement to stick to old C89. OpenBSD reported 30%. I assume the 70% either have to do with C++ or - more likely - there is a huge selection bias.
Daniel admits that he "might" just be counting differently.
I expect some of it is C++ because there sure is plenty of additional complexity to fit in the same size brain and yet you retain the same absolute requirement to juggle everything at all times or the software blows up but I'd be very surprised if it accounted for this huge disparity.
I mean, it's not supposed to find any in the unsafe language either, but that's why it was used.
Firefox not only uses unstable Rust features (via the exemption mechanism the same way Linux does it, trained professionals, closed course, do not attempt at home) it also presumably has some volume of its own explicitly unsafe Rust and so there's no reason this could not be checked, and what makes the difference here is whether it was or was not.
No it is supposed to find them in C++, because we all know humans are infallible and it's super easy to write memory errors in C++.
The whole point of Rust is that the borrow checker is infallible (pretty much anyway).
> it also presumably has some volume of its own explicitly unsafe Rust
"Some volume" is so tiny as to be irrelevant. There's no point going to this effort if Rust memory safety vulnerabilities are 1000 times less frequent than in C++.
That number is not made up. See https://blog.google/security/rust-in-android-move-fast-fix-t...
I'd like to understand if Rust was skipped because they assumed it would be fine, skipped purely as happenstance, or in fact tested and found to not be problem. I don't like assuming things when I could measure instead.
Ha yes.
> Strict No LLM / No AI Policy
> No LLMs for issues.
> No LLMs for pull requests.
> No LLMs for comments on the bug tracker, including translation. English is encouraged, but not required. You are welcome to post in your native language and rely on others to have their own translation tools of choice to interpret your words.
If they would accept issues filed by AI or written by AI, they should edit their policy to say that.
If you’re saying their philosophy is compatible with LLM issues, I agree and I think they should change their policy to reflect that.
I eventually left and wound up at Mozilla where there were a number of /* flawfinder ignore */ comments scattered throughout the code.
My guess is that Mythos just ignored the "flawfinder ignore" directives and reported the known vulnerabilities in the code.
I wonder if these models will get good + cheap enough so that people rarely reach for static analysis.
Using LLM coding tools to stay on top of static analysis tool output works very well and adding some guard rails that enforce that there are no issues is probably a good idea. Just like adding CI checks to make sure everything is clean.
As for false positives, it depends on the tool. I tend to avoid tools that generate mostly noise. Most of these tools allow you to disable rules if they produce a lot of noise. Or you can just tell the LLM to fix all the issues. When it's cheaper to fix things than to argue with the rule, just fix it. That used to be really expensive when you had to do that manually. Now it isn't.
I recently did this to an Ansible code base that I needed to refresh after not touching it for a few years. It had hundreds of ansible-lint issues; mostly deprecation warnings and some non fatal other warnings. And 10 minutes later I had zero. Mostly they probably weren't very serious ones but it's a form of technical debt. If you have to fix hundreds of warnings manually, you are probably not going to do it. But if you can wave a magical wand and it all goes a way, why not? I adjusted the guard rails so it now always runs ansible-lint and fixes any issues. Only takes a few seconds extra.
I think these harnesses are _using_ static analysis tools, and probably will continue to do that.
I maintain a static analysis tool using in Firefox's CI. False positives have to be fixed or annotated as non-problems in order for you to land a patch in our tree. That means permitting zero positives (false or true), which is a strict threshold. This is a conscious tradeoff; it requires weakening the analysis and getting some false negatives (missed bugs) in order to keep the signal-to-noise ratio high enough that people don't just ignore it and annotate everything away, or stop running it. Nearly all static analysis tools have to do this balancing act.
AI, as commonly used, is given more leeway. It's kind of fundamental that it must be allowed to hallucinate false positives; that's the source of much of its power. Which means you need layers of verification and validation on top of it. It can be slow, you'll never be able to say "it catches 100% of the errors of this particular form: ...", and yet it catches so much stuff.
Data point: my analysis didn't cover one case that I erroneously thought was unlikely to produce true positives (real bugs), and was more complex to implement than seemed worth the trouble. Opus or Mythos, I'm not sure which, started reporting vulnerabilities stemming from that case, so I scrambled and extended the analysis to cover the gap. It took me long enough to implement that by the time I had a full scan of the source tree, Claude had found every important problem that it reported. The static analysis found several others, and I still honestly don't know whether any of them could ever be triggered in practice.
I still think there's value in the static analysis. Some of those occurrences of the problematic pattern might be reachable now through paths too tricky for the AI to construct. Some of them might turn into real problems when other code changes. It seems worth having fixes for all of them now for both possibilities, and also for the lesser reason of not wanting the AI to waste time trying to exploit them. At the same time, clearly the cost/benefit balance has shifted.
They could also team up: if I relax my standards and allow my analysis to write an additional warnings report of suspected problems, with the clear expectation that they might be false alarms, then I could feed that list to an AI to validate them. Essentially, feed slop to the slop machine and have it nondeterministically filter out the diamonds in the rough.
Food for thought...
It's for detecting a specific situation: you grab a pointer to a GC-managed object, call something that might possibly trigger a GC even if it probably won't, and then use the pointer. (The GC might collect that object, or it might move it somewhere else.)
Claude is pretty good at weaponizing these UAFs.
Translating things to Rust manually was already a thing before LLMs came into the picture. Now with LLMs that's only going to get easier and faster. The long term value is going to come from getting on top of the mountain of technical debt in the form of existing C/C++ code bases that is responsible for the vast majority of memory exploits, buffer overflows, and other issues that despite decades of attention still are being found across major code bases on a regular basis.
Mozilla finding these issues comes on the back of a quarter century of some very competent engineers trying to do the right thing and using all the tools at their disposal to prevent these issues from happening. I have a lot of respect for that team and the contributions it has made over the years to improve tools, testing/verification practices, etc. The issue is not their effort or competence.
The job of taking an existing system that is well covered in test, well documented/specified, etc. and producing a new one that can function as a drop in replacement is now something that can be considered. A few years ago that would have translated into absolutely massive project cost and risk. Now it's something you can kick off on a Friday afternoon. Worst case it doesn't work, best case you end up with a much better implementation.
It's still early days. There are still a lot of quality issues with LLM generated code. But the success/fail rate will probably improve over time.
More tools for more people equals more stuff being made on a wider range.
That will make software safer alone.
Ideally, you'd do a comprehensive all-source-code scan, (and the LLM-scanner finds everything during those scans), and fix all the reported defects.
Afterwards, any dev that commits code will run the LLM-scanner on the modified code (and affected areas) and fix any reported defects.
So the black-hat hacker would be shut out unless they get access to an LLM-scanner with better analysis than what the target project is using.
Major LLM-scanners could give priority access for new versions of LLM-scanners to major projects to find any defects in the current source code before any other party could use the reported defects against the project or their users.
So black-hat hackers would be left with developing their own LLM-scanner better/more efficient than existing major LLM-scanners.
Given enough incentive, they might develop such a tool. Look at the market for zero-day vulnerabilities for smartphones, esp iPhones.
But it also represents more easily available opportunities for blackhats to abuse against the projects where these tools were not being applied.
From what I understand, that is a recipe for getting quickly banned by commercial LLM providers?
I don't understand much of this paragraph:
* "a crank they can pull that says: ‘Yep, this has the problem,’": as in, ring an alarm? Does the LLM ring th alarm?
* "you can iterate on the code and know clearly when you’ve fixed it": Isn't that true of most bugs, assuming you do the normal thing and generate a test case? And I thought the LLM output test cases itself: "It will craft test cases. We have our existing fuzzing systems and tools to be able to run those tests" And are they claiming the LLM facilitates iterating?
* "and eventually land the test case in the tree": Don't you create the test case before the fix? And just a few words earlier they seemed to be working on the fix, not the test case. And see the prior point about test cases.
* "such that you don’t regress it.”: How is the LLM helping here?
Maybe I'm missing some fundamental unwritten assumption?
> eventually land the test case
This is just a reference to the fact that we don't land test cases for security bugs immediately in the public repository, to make it harder for attackers. You are right that the LLM only helps with creating the initial test case. Things like running the test case in automation is part of the standard development process.
For instance, in one of the included bugs (2022034) it figured out that a floating point value being sent over IPC could be modified by an attacker in such a way that it would be interpreted by the JS engine as an arbitrary pointer, due to the way the JS engine uses a clever representation of values called NaN-boxing. This is not beyond the realm of a human researcher to find, but it did nicely combine different domains of security.
As the person responsible for accidentally introducing that security problem (and then fixing it after the Mythos report), while I am aware of NaN-boxing (despite not being a JS engine expert), I was focused more on the other more complex parts of this IPC deserialization code so I hadn't really thought about the potential problems in this context. It is just a floating point value, what could go wrong?
Think it's more a care of mythos raising widespread awareness that tireless LLMs can be weaponized to dig through code and find that one tiny flaw nobody spotted
Of course, even the reports with flawed methodology could be suggesting that a great harness + weak model might achieve a similar level of results as a mediocre harness + strong model. But I'd want to see solid evidence for that.
There was a time when the entire transportation infrastructure in the US was built around horses. Even after cars were invented, the cars weren't obviously better than horses for most people, especially because there wasn't any infrastructure to support them, but the infrastructure and the cars kept improving to the point where it was better for some people at some things, then suddenly it was better at most things, and then people stopped using horses, and we re-organized our entire transportation network around cars.
But there was never a revolutionary technological change. The technology of cars in the 1930s was the same fundamental technology as the cars in the 1890s. Just at some point it became "good enough" and that was it.
I think when people say that AI is a bubble, they are assuming that anything economically useful that LLMs cannot perform today is _qualitatively_ different from what LLMs can do right now, and that LLMs cannot do it even in theory, without some major technological innovation. But I have a suspicion that there are a large number of valuable things, that once LLMs advance just a little bit more, and harnesses and infra around them is improved a little bit more will just be completely taken over by LLMs.
see https://www.blackduck.com/static-analysis-tools-sast/coverit...
and for Firefox-related alleged defects, see https://scan.coverity.com/projects/firefox
You have to create an account to view the actual reported defects.
There are just over 5000 reported defects still outstanding. I don't know how many overlap with the reported 271 Mythos-reported defects.
You get bug bounties if you report the kind of bugs Mythos identified. There's a reason no-one collected bounties from the "5000 defects" Coverity identified.
The Mythos reports have several examples of chaining a whole bunch of logic in different parts of the program together to exploit something very subtle. The Coverity reports aren't anything like that. These tools aren't remotely in the same league or even universe.
It's hard to convince managers to spend money on static analysis tools (or any development tool).
Unless your company just got bad publicity for a bug and your devs come to you and demonstrate that a certain static analysis tool would have flagged that particular piece of code, most managers would let the beancounter-facet dominate the decision making process.
And any one or two of them could have led to a random web ad stealing your ssh keys and installing a keylogger to get into your bank account.
I often wonder if we're taking the right route with computer security. Would we be better off having a whole virtual machine for every web page, application or service? Or even physically separate hardware you just vnc into?
Wired: Mozilla Used Anthropic's Mythos to Find and Fix 271 Bugs in Firefox (41 points, 18 comments) https://news.ycombinator.com/item?id=47853649
Ars: Mozilla: Anthropic's Mythos found 271 security vulnerabilities in Firefox 150 (33 points, 8 comments)https://news.ycombinator.com/item?id=47855384
https://hacks.mozilla.org/2026/05/behind-the-scenes-hardenin...
The zero-days are numbered
Well, depending on how you define "exploit"; some might only read arbitrary pointers or just out of bounds. Those would be useful primitives in a chain of vulnerabilities, not exploits themselves. You'll have to read through the first comments yourself, but if you're hoping that this is all nonsense and ignorable hype, you're going to be disappointed.
New tools find new bugs, but the oligarchy newspapers report on Mythos and not on clang-22.0.
It is still unclear and open for speculation as to what percentage of all security bugs in Firefox today are being found by the AIs (as opposed to not being found at all). It might be that AI is very good at certain types of problems, even if we can't put our finger on what those types are, and that after the initial wave of bug reports the AI findings will slow to a trickle even while many many other bugs remain in the codebase. Or it might be that AI really does detect most instances of some class of problems and all those bugs will now be gone forever, never to return as long as Mozilla keeps paying the token monster. This is closely related to the oft-asked question "are we better or worse off after both attackers and defenders have access to this new capability?"
I'm not only talking about big things like
* Pocket,
* several major UI redesigns and
* the offline translations,
but even tiny useless things like
* browser.urlbar.trimURLs,
* putting the search query in the URL bar instead of the URL after searching from the URL bar,
* messing with the Edit and Resend feature for no reason (the good one that updates the content length is still available at devtools.netmonitor.features.newEditAndResend) and
* probably thousands of little shit like this that took a bunch of developer hours to implement.
All of the above should've been add-ons.
And of course, we know Mozilla spends a lot of money on things unrelated to Firefox at all. It's amazing Firefox is somewhat secure and stable compared to Chrome, which is backed by Google with their infinitely deep pockets.
This is a web browser, after all. Something most people use all the time. Something that accepts untrusted input from thousands of sources every day. People use it pretty much every aspect of their lives - banking, personal communication, porn, expressing political opinions. It's used for viewing PDFs, playing media files, for interacting with a whole bunch of APIs (that IMO shouldn't be part of the web, but they are). Security should be top priority.
Firefox/Mozilla tries literally anything to expand their feature set, customer base, or revenue stream? They need to stop spending money on that and instead spend money on the free product of theirs that I care about, in exactly the way I want.
Google surveilles the entire world, spends huge amounts on lobbying, degrades their own websites on other browsers? Not a peep, usually.
For my part, I pay mozilla for their VPN service, which I’m sure many here would decry as useless spending that should be going to firefox instead.
If Firefox starts acting maturely, we can stop having these conversations. Until then we see useless crap in every update while most bugs don't get any meaningful attention. Some changes even made things worse than they were before, for example the new Edit and Resend (not so "new" anymore). If Mozilla starts acting the best interest of the user, stops with the ad BS and doesn't try to be everything all at once and actually focuses on Firefox, I would donate. And so would others. If I donate now, I doubt even 1% of my money would go to anything meaningful, like bug fixing.
> Not a peep, usually.
No, fuck Google and Chrome and even anything Chromium-based. Here's the peep from me.
> For my part, I pay mozilla for their VPN service, which I’m sure many here would decry as useless spending that should be going to firefox instead.
Does the profit from the VPN service go to Firefox? If not, what's the point of having a VPN service.