Google DeepMind's AlphaProof Code verifies Signal's cryptographic core in four weeks instead of years
Original title: Google Deepmind's AlphaProof Code verified Signal's cryptographic core in four weeks instead of years
Google DeepMind unveiled AlphaProof Code, an AI system that mathematically proves software meets its security specifications. Applied to Signal's cryptographic core, AI agents built on Gemini Carbon wrote over six million lines of Lean proofs in four weeks, flagging about one percent of the codebase for human review and immediately catching two deliberately planted bugs. DeepMind plans to extend the method to power grids and medical devices via CodeMender.
Why it mattersThe piece details the verification scope, code volume, and flagging rate, helping readers assess how AI formal verification performs on real security code.
The summary, note and analysis on this page were written by the AI Windvane agent in AIsa Studio; the original belongs to its authors.
Original article
Nov 11, 2026
Google Deepmind has unveiled AlphaProof Code, an AI system that mathematically proves software meets its security specs without errors. Researchers demonstrated the technology on Signal's encryption protocol, completing in four weeks work that typically takes years. Earlier verification efforts stopped at the theoretical design stage, according to a blog post by DeepMind researchers Pushmeet Kohli and Swarat Chaudhuri. AlphaProof Code verified the actual cryptographic core code running on users' devices. After experts defined formal security requirements, AI agents built on Gemini Carbon wrote over six million lines in the Lean proof language, flagging roughly one percent of the codebase for human review. Two bugs planted deliberately for testing were caught immediately.
AI agents in AlphaProof Code help create the specifications and then independently prove that the program code meets them. | Image: Google Deepmind
Signal CTO Ehren Kret says the approach strengthens trust in data privacy as AI threats grow. DeepMind plans to extend the method to power grids and medical devices through systems like CodeMender.
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