51–60 of 232 posts
My understanding is that ksmbd is a kernel-space SMB server "developed as a lightweight, high-performance alternative" to the traditional (user-space) Samba server... Q1: Who is using ksmbd in production? Q2: Why?
I recently found a pretty serious security vulnerability in an open source very niche server I sometimes use. This took virtually no effort using LLMs. I'm worried that there is a huge long tail of software out there which wasn't worth finding vulnerabilities in for nefarious means manually but if it was automated could lead to really serious problems.
I think this is the biggest alignment problem with LLMs in the short term imo. It is getting scarily good at this. I recently found a pretty serious security vulnerability in an open source very niche server I sometimes use. This took virtually no effort using LLMs. I'm worried that there is a huge long tail of software out there which wasn't worth finding vulnerabilities in for nefarious means manually but if it was…
I wouldn't (personally) call it an alignment issue, as such.
I think this is the biggest alignment problem with LLMs in the short term imo. It is getting scarily good at this. I recently found a pretty serious security vulnerability in an open source very niche server I sometimes use. This took virtually no effort using LLMs. I'm worried that there is a huge long tail of software out there which wasn't worth finding vulnerabilities in for nefarious means manually but if it was…
> I tried to strongly guide it to not report false positives, and to favour not reporting any bugs over reporting false positives. I have no idea if this helps, but I’d like it to help, so here we are. In fact my entire system prompt is speculative in that I haven’t ran a sufficient number of evaluations to determine if it helps or hinders, so consider it equivalent to me saying a prayer, rather than anything resembling science or engineering. Once I have ran those evaluations I’ll let you know.
A small thing, but I found the author's project-organization practices useful – creating individual .prompt files for system prompt, background information, and auxiliary instructions [1], and then running it through `llm`. It reveals how good LLM use, like any other engineering tool, requires good engineering thinking – methodical, and oriented around thoughtful specifications that balance design constraints – for b…
How do we benchmark these different methodologies? It all seems like vibes-based incantations. "You are an expert at finding vulnerabilities." "Please report only real vulnerabilities, not any false positives." Organizing things with made-up HTML tags because the models seem to like that for some reason. Where does engineering come into it?
Meanwhile, as a maintainer, I've been reviewing more than a dozen false positives slop CVEs in my library and not a single one found an actual issue. This article's is probably going to make my situation worse.
This made me think that the near future will be LLMs trained specifically on Linux or another large project. The source code is a small part of the dataset fed to LLMs. The more interesting is runtime data flow, similar to what we observe in a debugger. Looking at the codebase alone is like trying to understand a waterfall by looking at equations that describe the water flow.
The most interesting and significant bit of this article for me was that the author ran this search for vulnerabilities 100 times for each of the models. That's significantly more computation than I've historically been willing to expend on most of the problems that I try with large language models, but maybe I should let the models go brrrrr!
When the cost of inference gets near zero, I have no idea what the world of cyber security will look like, but it's going to be a very different space from today.