Nicholas Carlini - Black-hat LLMs | [un]prompted 2026

The technique Anthropic uses was demonstrated by Nicholas Carlini in a talk he gave 2 weeks ago and it's very simple, when asking LLMs to review code, ask them to review one file in a single session. Here is the video with the timestamp (watch through to ~5:30, they show two different ways of prompting claude). [this video] [this video] IMO the big "innovation" being shown by Mythos is the effectiveness with prompting LLMs to look for security vulnerabilities in specific files one at a time and automating this prompting with a simple script. Prompting Mythos with a single file per session is why I suspect it cost Anthropic $20k to find some of the bugs in these codebases. I know this same technique is effective with Opus 4.6 and GPT 5.4 because I've been using it on my own code. If you just ask the agent to review your pr with a low effort prompt they are not exhaustive, they will not actually read each changed file and look at how it interacts with the system as a whole. If the entire session is to review the changes for a single file, the llm will do much more work reviewing it.

Intrinsically simple and straight forward problems are easier to secure even with mediocre or bad code. They've already shown that Opus 4.6 can find and report on very sophisticated security issues[0] so I'm not sure that analysis (and perhaps especially security analysis) is the biggest issue with LLMs. Mind you, I'm not using LLMs for professional programming since I prefer knowing everything inside and out in the code that I work on, but I have tried a bunch of different modes of use (spec-driven + entire implementation by Opus 4.6, latest Codex and Composer 2, and entirely "vibecoded", as well as minor changes) and can say that for trivial in-house things it's actually usable. Do I prefer to rewrite it entirely manually if I want something that I actually like? Yes. Do I think that not everything needs to be treated that way if you just want an initial version you can tinker with? Also yes. 0: [this video]

What I found is that the "For You" algorithm on X was better than I thought. Yes, it starts off as terrible, and remains terrible without very careful steering. I'm treating X as read-only and not interacting. But after liking a few posts by Amanda Askell, Simon Willison, Ethan Mollick, Boris Cherny and others, I was immediately getting far better AI information than I was on Bluesky, from accounts beyond the ones where I'd liked their posts. That isn't necessarily a high bar, but at least it was people actively using AI, people who are positive about the things that can be made with it. I'm more likely to hear about new model releases that I won't hear about elsewhere. At least on X, I'm going to hear people talking about Claude Mythos, and I'll hear about the Nicholas Carlini talk [1] where Claude Mythos is finding & reporting CVEs in the Linux kernel. On Bluesky, my time was being spent fighting off anti-AI university professors who were still in the "stochastic parrot" phase. They were genuinely convinced AI models couldn't even write code that compiles, let alone entire working programs that solve problems. I'm not trying to persuade you or anyone else to use X, and I'd really rather not be using X myself. [1] [this video]

About five minutes in in this video: [this video] They also say publicly in their Opus 4.6 post ( [link] ): >In this work, we put Claude inside a “virtual machine” (literally, a simulated computer) with access to the latest versions of open source projects. We gave it standard utilities (e.g., the standard coreutils or Python) and vulnerability analysis tools (e.g., debuggers or fuzzers), but we didn’t provide any special instructions on how to use these tools, nor did we provide a custom harness that would have given it specialized knowledge about how to better find vulnerabilities. This means we were directly testing Claude’s “out-of-the-box” capabilities, relying solely on the fact that modern large language models are generally-capable agents that can already reason about how to best make use of the tools available.