alt Hacker NewsAI cybersecurity is not proof of work
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Fighting over analogies is kind of pointless imo, but if you want me to indulge, here is what I will ask: Do you consider breadth first search better or depth first search better? - the good answer is it depends on the search surface. The same way bugs, vulnerabilities are hiding somewhere on the surface or inside(exploiting dependencies) the surface of the software.
In conclusion - Having a lot of tokens help! Having a better model also helps. Having both helps a lot. Having very intelligent humans + a lot of tokens + the best frontier models will help the most (emphasis on intelligent human).
The whole framing is kind of uninteresting imo. If you spend more time researching code you can find more bugs to exploit / patch is not an earthshaking observation.
Adding the words “by Claude” to it doesn’t materially change it. One could also pay a few humans to do the same thing. People have done that for decades.
A couple of alternative scenarios, although I'm not sure how much stock we should put in them:
- what if at a certain level of capability you're essentially bug-free? I'm somewhat skeptical that this could be the case in a strong sense, because even if you formally prove certain properties, security often crucially depends on the threat model (e.g. side channel attacks, constant-time etc,) but maybe it becomes less of a problem in practice?
- what if past a certain capability threshold weaker models can substitute for stronger ones if you're willing to burn tokens? To make an example with coding, GPT-3 couldn't code at all, so I'd rather have X tokens with say, GPT 5.4, than 100X tokens with GPT-3. But would I rather have X tokens with GPT 5.4 or 100X tokens with GPT 5.2? That's a bit murkier and I could see that you could have some kind of indifference curve.
It is also not proof of work because of asymmetries between attacker and defender. An attacker only needs to find one exploitable issue before the defender finds it and patches it, while the defender eventually needs to find all issues - and even then can't really be sure they remediated everything.
The defender also not only has to discover issues but get them deployed. Installing patches takes time, and once the patch is available, the attacker can use it to reverse engineer the exploit and use it attack unpatched systems. This is happening in a matter of hours these days, and AI can accelerate this.
It is also entirely possible that the defender will never create patches or users will never deploy patches to systems because it is not economically viable. Things like cheap IoT sensors can have vulnerabilities that don't get addressed because there is no profit in spending the tokens to find and fix flaws. Even if they were fixed, users might not know about patches or care to take the time to deploy them because they don't see it worth their time.
Yes, there are many major systems that do have the resources to do reviews and fix problems and deploy patches. But there is an enormous installed base of code that is going to be vulnerable for a long time.
> Different LLMs executions take different branches, but eventually the possible branches based on the code possible states are saturated
With LLMs even the halting problem is just the question of paying for pro subscription!
> So, cyber security of tomorrow will not be like proof of work in the sense of "more GPU wins"; instead, better models, and faster access to such models, will win.
It's not proof of work, but proof of financial capacity.
The big companies are turning the access to high-quality token generators (through their service) into means of production. We're all going direct to Utopia, we're all going direct the other way.
Interestingly enough: earlier today this discussion was trending: https://news.ycombinator.com/item?id=47769089 (Cybersecurity looks like proof of work now)
Seriously. We need a BuSab for IT.
This continous rush is not healthy. npm updates, replies to articles that barely made HN 12 hours ago, anything like that. It's not healthy.
Slow down.
While I fully agree with the headline I find it surprising that so many people implicitly claim familiarity with the aptly named "Mythos". Mythos is closed and currently has the status of an overhyped Anduril drone that failed contact with reality in Ukraine.
If anyone has access to the mythical Mythos we'll see the contact with reality.
> What happens is that weak models hallucinate (sometimes causally hitting a real problem)
So the bigger models hallucinate better causally hitting more real problems?
What seems to be getting lost in the noise on this topic is that security has always been about security in depth and mitigating controls, in other words applied paranoia. There are always threat vectors and we're seeing a change in the shape of those vectors with more rapidity than ever before which is certainly exhausting for everyone. But don't forget the fundamentals here
>> Test it yourself, GPT 120B OSS is cheap and available. BTW, this is why with this bug, the stronger the model you pick (but not enough to discover the true bug), the less likely it is it will claim there is a bug.
I guess this is the crux of the debate. All the claims are comparing models that are available freely with a model that is available only to limited customers (Mythos). The problem here is with the phrase "better model". Better how? Is it trained specifically on cybersecurity? Is it simply a large model with a higher token/thinking budget? Is it a better harness/scaffold? Is it simply a better prompt?
I don't doubt that some models are stronger that other models (a Gemini Pro or a Claude Opus has more parameters, higher context sizes and probably trained for longer and on more data than their smaller counterparts (Flash and Sonnet respectively).
Unless we know the exact experimental setup (which in this case is impossible because Mythos is completely closed off and not even accessible via API), all of this is hand wavy. Anthropic is definitely not going to reveal their setup because whether or not there is any secret sauce, there is more value to letting people's imaginations fly and the marketing machine work. Anthropic must be jumping with joy at all the free publicity they are getting.