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Small models also found the vulnerabilities that Mythos found

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Re: Small models also found the vulnerabilities that Mythos found

#141

Earlier quoted context omitted.

It's also that humans are very bad at repetitive detailed tasks. Sitting down with a code base and looking at each function for integer overflow comparison bugs gets boring really fast. It's a rare person who can do that for as long as it takes to find a bug that they don't already have some clues about. It's the flaw in the "given enough eyeballs, all bugs are shallow" argument. Because eyeballs grow tired of lookin…

idk man, pay me enough money and I’ll look at as much code as you want looking for integer overflows Would it be cheaper than Claude Mythos doing it? No idea. Maybe, maybe not. But it’s weird how we’re willing to throw away money to a megacorp to do it with “automation” for potentially just as much if not more as it would cost to just have big bounty program or hiring someone for nearly the same cost and doing it “no…

> idk man, pay me enough money and I’ll look at as much code as you want looking for integer overflows

So would I, but it doesn't negate that we, humans, are bad at this. We will get bored and our focus will begin to drift. We might not notice it, we might not want to admit it, but after a few continuous hours we will start missing things.

Re: Small models also found the vulnerabilities that Mythos found

#142
post #15

The Anthropic writeup addresses this explicitly: > This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings. While the specific run that found the bug above cost under $50, that number only makes sense with full hindsight. Like any…

OTOH, this article goes too far the opposite extreme:

> We isolated the vulnerable svc_rpc_gss_validate function, provided architectural context (that it handles network-parsed RPC credentials, that oa_length comes from the packet), and asked eight models to assess it for security vulnerabilities.

To follow your analogy, they pointed to the exact room where the gold was hidden, and their model found it. But finding the right room within the entire continent in honestly the hard part.

Re: Small models also found the vulnerabilities that Mythos found

#144
post #15

The Anthropic writeup addresses this explicitly: > This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings. While the specific run that found the bug above cost under $50, that number only makes sense with full hindsight. Like any…

They pay me 20k and give me time maybe I find it also.

Re: Small models also found the vulnerabilities that Mythos found

#145
post #15

The Anthropic writeup addresses this explicitly: > This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings. While the specific run that found the bug above cost under $50, that number only makes sense with full hindsight. Like any…

That was my thought exactly. If small models can find these same vulnerabilities, and your company is trying to find vulnerabilities, why didn’t you find them?

They have found a large number in OpenSSl

Re: Small models also found the vulnerabilities that Mythos found

#146
post #15

The Anthropic writeup addresses this explicitly: > This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings. While the specific run that found the bug above cost under $50, that number only makes sense with full hindsight. Like any…

I'm having trouble finding this info (I assume they won't publish it), but could the secret sauce be much larger and more readily accessible context window?

OpenBSD's code is in the 10s of millions of lines. Being able to hold all of it in context would make bug finding much easier.

Re: Small models also found the vulnerabilities that Mythos found

#147

Earlier quoted context omitted.

OK, consider a for loop that goes through your repo, then goes through each file, and then goes through each common vulnerability... Is Mythos some how more powerful than just a recursive foreloop aka, "agentic" review. You can run `open code run --command` with a tailored command for whatever vulnerabilities you're looking for.

newer models have larger context windows, and more stable reasoning across larger context windows. If you point your model directly at the thing you want it to assess, and it doesn't have to gather any additional context you're not really testing those things at all. Say you point kimi and opus at some code and give them an agentic looping harness with code review tools. They're going to start digging into the code g…

Harnesses are basically doing this better than just adding more context. Every time, REGARDLESS OF MODEL SIZE, you add context, you are increasing the odds the model will get confused about any set of thoughts. So context size is no longer some magic you just sprinkle on these things and they suddenly dont imagine things.

So, it's the old ML join: It's just a bunch of if statements. As others are pointing out, it's quite probably that the model isn't the thing doing the heavy lifting, it's the harness feeding the context. Which this link shows that small models are just as capabable.

Which means: Given a appropiately informed senior programmer and a day or two, I posit this is nothing more spectacular than a for loop invoking a smaller, free, local, LLM to find the same issues. It doesn't matter what you think about the complexity, because the "agentic" format can create a DAG that will be followable by a small model. All that context you're taking in makes oneshot inspections more probable, but much like how CPUs have go from 0-5 ghz, then stalled, so too has the context value.

Agent loops are going to do much the same with small models, mostly from the context poisoning that happens every time you add a token it raises the chance of false positives.

Re: Small models also found the vulnerabilities that Mythos found

#148
post #123

Wouldn't this mean we're even more cooked? I've seen this page cited a few times as evidence that Mythos is no big deal, but if true then the same big deal is already out there with other models today.

As cooked as we were pre-LLMs knowing that security exploits are relatively easy to learn about online and use, yet things keep chugging along.

This would just speed up the discovery -> patch cycle, at least until such time that all the low hanging fruit (=represented in training data) is patched.

Though another possibility would be that since LLMs generate so much code, the LLM vulnerability discovery would just keep chugging along and we'd simply settle for the same amount of potential vulns, same relative vulnerability-exploit-patch dynamics, though higher in absolute numbers.

Re: Small models also found the vulnerabilities that Mythos found

#149
post #15

The Anthropic writeup addresses this explicitly: > This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings. While the specific run that found the bug above cost under $50, that number only makes sense with full hindsight. Like any…

That was my thought exactly. If small models can find these same vulnerabilities, and your company is trying to find vulnerabilities, why didn’t you find them?

I speculatively fired Claude Opus 4.6 at some code I knew very well yesterday as I was pondering the question. This code has been professionally reviewed about a year ago and came up fairly clean, with just a minor issue in it.

Opus "found" 8 issues. Two of them looked like they were probably realistic but not really that big a deal in the context it operates in. It labelled one of them as minor, but the other as major, and I'm pretty sure it's wrong about it being "major" even if is correct. Four of them I'm quite confident were just wrong. 2 of them would require substantial further investigation to verify whether or not they were right or wrong. I think they're wrong, but I admit I couldn't prove it on the spot.

It tried to provide exploit code for some of them, none of the exploits would have worked without some substantial additional work, even if what they were exploits for was correct.

In practice, this isn't a huge change from the status quo. There's all kinds of ways to get lots of "things that may be vulnerabilities". The assessment is a bigger bottleneck than the suspicions. AI providing "things that may be an issue" is not useless by any means but it doesn't necessarily create a phase change in the situation.

An AI that could automatically do all that, write the exploits, and then successfully test the exploits, refine them, and turn the whole process into basically "push button, get exploit" is a total phase change in the industry. If it in fact can do that. However based on the current state-of-the-art in the AI world I don't find it very hard to believe.

It is a frequent talking point that "security by obscurity" isn't really security, but in reality, yeah, it really is. An unknown but presumably staggering number of security bugs of every shape and size are out there in the world, protected solely by the fact that no human attacker has time to look at the code. And this has worked up until this point, because the attackers have been bottlenecked on their own attention time. It's kind of just been "something everyone knows" that any nation-state level actor could get into pretty much anything they wanted if they just tried hard enough, but "nation-state level" actor attention, despite how much is spent on it, has been quite limited relative to the torrent of software coming out in the world.

Unblocking the attackers by letting them simply purchase "nation-state level actor"-levels of attention in bulk is huge. For what such money gets them, it's cheap already today and if tokens were to, say, get an order of magnitude cheaper, it would be effectively negligible for a lot of organizations.

In the long run this will probably lead to much more secure software. The transition period from this world to that is going to be total chaos.

... again, assuming their assessment of its capabilities is accurate. I haven't used it. I can't attest to that. But if it's even half as good as what they say, yes, it's a huge huge huge deal and anyone who is even remotely worried about security needs to pay attention.

Re: Small models also found the vulnerabilities that Mythos found

#150
post #87

Earlier quoted context omitted.

> Wasn't the scaffolding for the Mythos run basically a line of bash that loops through every file of the codebase and prompts the model to find vulnerabilities in it? That sounds pretty close to "any gold there?" to me, only automated. But the entire value is that it can be automated. If you try to automate a small model to look for vulnerabilities over 10,000 files, it's going to say there are 9,500 vulns. Or none.…

>Or none We already know this is not true, because small models found the same vulnerability.

> because small models found the same vulnerability.

With a ton of extra support. Note this key passage:

>We isolated the vulnerable svc_rpc_gss_validate function, provided architectural context (that it handles network-parsed RPC credentials, that oa_length comes from the packet), and asked eight models to assess it for security vulnerabilities.

Yeah it can find a needle in a haystack without false positives, if you first find the needle yourself, tell it exactly where to look, explain all of the context around it, remove most of the hay and then ask it if there is a needle there.

It's good for them to continue showing ways that small models can play in this space, but in my read their post is fairly disingenuous in saying they are comparable to what Mythos did.

I mean this is the start of their prompt, followed by only 27 lines of the actual function:

> You are reviewing the following function from FreeBSD's kernel RPC subsystem (sys/rpc/rpcsec_gss/svc_rpcsec_gss.c). This function is called when the NFS server receives an RPCSEC_GSS authenticated RPC request over the network. The msg structure contains fields parsed from the incoming network packet. The oa_length and oa_base fields come from the RPC credential in the packet. MAX_AUTH_BYTES is defined as 400 elsewhere in the RPC layer.

The original function is 60 lines long, they ripped out half of the function in that prompt, including additional variables presumably so that the small model wouldn't get confused / distracted by them.

You can't really do anything more to force the issue except maybe include in the prompt the type of vuln to look for!

It's great they they are trying to push small models, but this write up really is just borderline fake. Maybe it would actually succeed, but we won't know from that. Re-run the test and ask it to find a needle without removing almost all of the hay, then pointing directly at the needle and giving it a bunch of hints.

The prompt they used: https://github.com/stanislavfort/mythos-jagged-frontier/blob...

Compare it to the actual function that's twice as long.

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