帖文称 Google DeepMind 用 AI 代理验证 Signal 运行代码的保密性

This diagram shows how the AI’s work gets checked. Basically, you never have to trust the AI. The AI agents write the proof, but a strict math checker throws out anything wrong, so you only have to trust the security rules humans approved, not the AI itself. https://t.co/Ha174MKW4k

Big achievement by Google DeepMind for showing that an AI system that proves a software is secure mathematically, with no need to trust the AI. > They just used AI agents to mathematically prove that Signal’s real running code keeps messages secret. Google's AI agents wrote 6.5M lines of math proving Signal’s compiled code keeps chats private. checked at the level of the instructions a processor actually runs. The lab says no one had done this before for any widely used protocol. > Normal testing tries many inputs and hopes to hit the bad one. A proof shows the security rules hold in every case, and the Lean proof checker rejects any wrong step the AI writes. > Real bugs often creep in when a design gets turned into code, so checking the processor-level code closes that gap. The Rust compiler isn’t trusted either, so a mistake by the compiler would also get caught. > The work took 4 weeks, where expert teams used to need years. Teams of 40 to 80 Gemini Carbon agents wrote about 6.5M lines of Lean, while humans set the security goals and reviewed the 1% the agents flagged. > To check that the system can’t just approve any code, the researchers put 2 old, already fixed Signal bugs back into a copy. Both times it produced a machine-checked proof that the code was insecure. > The bigger shift is cost, now that AI can produce machine-checked proofs in weeks, rather than years-long projects and become routine checks for device firmware, power grid software and other critical code.