I know Mastodon hates LLM's and AI. So here goes!

I recently got access to trusted access of cyber capabilities of both openai and anthropic, which also allows you to weaponize security vulnerabilities.

The speed at which these parrots can find bugs and be creative enough to exploit them is staggering.

I recently pointed an LLM at an kernel fix that was reachable by an unprivileged namespace on Debian and it fully weaponized it, without too much me prompting it in the right direction, in about 7-9 hours.

I don't think open-source and companies will know what's coming for them once these open-source weight models will have broader reach and get better at exploiting vulnerabilities on a massive scale as anyone can access them.

The bottom line I think is, you cannot patch faster than the attackers can easily chain all kinds of vulnerabilities together and just move laterally on an incredibly fast pace.

I've started reporting vulnerabilities to all kinds of projects and the majority have trouble or patching issues found. There's not enough maintainers, or there's simply none anymore.

I've been getting quite worried about what our future will look like for data privacy. I think outright not running an LLM over your codebase to find critical security vulnerabilities because of your moral stance will keep us more insecure.

Please run an LLM over your code base if it's internet facing or something critical, we thank you!

Can't wait for the discussions on this!

@drwhax This may be one of the only niche use cases where LLM technology may actually be useful, and it may be what Linus Torvalds was talking about when it comes to AI and the Linux kernel. Directly deploying AI code in the kernel could violate the GPL.

But as for auditing existing code for potential vulnerabilities, and the pen-testing stuff, this may be a viable use case.

But that's not what the AI companies promote. They promote the AI-powered shovelware development use case instead.