Simon WillisonModify

2026-04-04 10:20:17

[GitHub] platform activity is surging. There were 1 billion commits in 2025. Now, it's 275 million per week, on pace for 14 billion this year if growth remains linear (spoiler: it won't.)

GitHub Actions has grown from 500M minutes/week in 2023 to 1B minutes/week in 2025, and now 2.1B minutes so far this week.

— Kyle Daigle, COO, GitHub

Tags: github, github-actions

2026-04-04 07:59:08

Vulnerability Research Is Cooked

Within the next few months, coding agents will drastically alter both the practice and the economics of exploit development. Frontier model improvement won’t be a slow burn, but rather a step function. Substantial amounts of high-impact vulnerability research (maybe even most of it) will happen simply by pointing an agent at a source tree and typing “find me zero days”.

Why are agents so good at this? A combination of baked-in knowledge, pattern matching ability and brute force:

You can't design a better problem for an LLM agent than exploitation research.

Before you feed it a single token of context, a frontier LLM already encodes supernatural amounts of correlation across vast bodies of source code. Is the Linux KVM hypervisor connected to the hrtimer subsystem, workqueue, or perf_event? The model knows.

Also baked into those model weights: the complete library of documented "bug classes" on which all exploit development builds: stale pointers, integer mishandling, type confusion, allocator grooming, and all the known ways of promoting a wild write to a controlled 64-bit read/write in Firefox.

Vulnerabilities are found by pattern-matching bug classes and constraint-solving for reachability and exploitability. Precisely the implicit search problems that LLMs are most gifted at solving. Exploit outcomes are straightforwardly testable success/failure trials. An agent never gets bored and will search forever if you tell it to.

The article was partly inspired by this episode of the Security Cryptography Whatever podcast, where David Adrian, Deirdre Connolly, and Thomas interviewed Anthropic's Nicholas Carlini for 1 hour 16 minutes.

I just started a new tag here for ai-security-research - it's up to 11 posts already.

Tags: security, thomas-ptacek, careers, ai, generative-ai, llms, nicholas-carlini, ai-ethics, ai-security-research

2026-04-04 07:57:04

A fun thing about recording a podcast with a professional like Lenny Rachitsky is that his team know how to slice the resulting video up into TikTok-sized short form vertical videos. Here's one he shared on Twitter today which ended up attracting over 1.1m views!

That was 48 seconds. Our full conversation lasted 1 hour 40 minutes.

Tags: ai-ethics, coding-agents, agentic-engineering, generative-ai, podcast-appearances, ai, llms, cognitive-debt

2026-04-04 05:48:22

On the kernel security list we've seen a huge bump of reports. We were between 2 and 3 per week maybe two years ago, then reached probably 10 a week over the last year with the only difference being only AI slop, and now since the beginning of the year we're around 5-10 per day depending on the days (fridays and tuesdays seem the worst). Now most of these reports are correct, to the point that we had to bring in more maintainers to help us.

And we're now seeing on a daily basis something that never happened before: duplicate reports, or the same bug found by two different people using (possibly slightly) different tools.

— Willy Tarreau, Lead Software Developer. HAPROXY

Tags: security, linux, generative-ai, ai, llms, ai-security-research

2026-04-04 05:46:07

The challenge with AI in open source security has transitioned from an AI slop tsunami into more of a ... plain security report tsunami. Less slop but lots of reports. Many of them really good.

I'm spending hours per day on this now. It's intense.

— Daniel Stenberg, lead developer of cURL

Tags: daniel-stenberg, security, curl, generative-ai, ai, llms, ai-security-research

2026-04-04 05:44:41

Months ago, we were getting what we called 'AI slop,' AI-generated security reports that were obviously wrong or low quality. It was kind of funny. It didn't really worry us.

Something happened a month ago, and the world switched. Now we have real reports. All open source projects have real reports that are made with AI, but they're good, and they're real.

— Greg Kroah-Hartman, Linux kernel maintainer (bio), in conversation with Steven J. Vaughan-Nichols

Tags: security, linux, generative-ai, ai, llms, ai-security-research