Skip to content
NewA calmer, faster ZeroHour

Claude produced formal proofs for code from 123 OSS-Fuzz libraries

Original title: Anthropic's Claude now writes code and proves it safe automatically

The Decoderby Matthias Bastian ()2 min read1 · 1 read
Part of a story covered by 2 sourcesAnthropic says Claude formally verified 123 open-source librariesMerged summary & timeline
AI summary · x-ai/grok-4.7Summaries by Vani AI

Rocq checks the proofs, which hold only for one architecture, single-threaded code, and inputs under 64 MB.

Anthropic's Frontier Red Team and partner Theorem used Claude to generate formal proofs for existing code drawn from 123 open-source libraries in Google's OSS-Fuzz project. The model produced about 180 million lines of proof in a few weeks, and Rocq checks those proofs. While proving, Claude found and fixed hundreds of bugs, including security bugs in a widely used PDF reader. Anthropic says the proofs apply only under a specific processor architecture, to single-threaded programs, and to inputs under 64 MB.

Unconfirmed: Anthropic does not report total project cost, and the proofs do not cover other hardware, multithreading, or larger inputs.

Key facts
  • The article cites 20 person-years to formally verify the seL4 kernel.
  • One week on a PDF reader matched a typical year of reported security bugs.
  • Claude found a logic error that had gone undetected for over a decade.
  • Opus 5.5 used about 40 percent fewer tokens than Opus 5 on half the proofs.
  • Theorem's roadmap names glibc, OpenSSL, and cURL.
Explain this AI news with Vani AIWhat was announced, what is new and why it matters, in a new chat

From the original article

2 min read at the-decoder.com

Anthropic had Claude generate mathematical proofs that existing code is correct, producing roughly 180 million lines of proof code for 123 open-source libraries. Along the way, the model caught bugs that years of testing had missed. Anthropic's goal: making formal verification with AI as routine as standard testing.

The Decoder

By Matthias Bastian · the-decoder.com

Read the full article at The Decoder

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.