Google DeepMind uses AI to prove Signal's messaging protocol secure

For the first time, AI has mathematically proven @signalapp’s protocol is secure down to the code level. Using our breakthrough AlphaProof Code framework, we verified the messaging app’s cryptographic system – which protects billions of private messages every day.

Banger report from Google DeepMind. This is also a good example of the type of ambitious work you can now do with frontier models. (bookmark it) They used AI agents to prove key security properties of Signal's code, down to the compiled machine code. Agents powered by Gemini 4 Carbon wrote about 6.5 million lines of Lean proofs on the unmodified libsignal code. A team of five finished the proof work in four weeks. Verifying the seL4 microkernel took twenty person-years. In this work, humans and agents write the security specs, prover agents write the proofs, and Lean checks every proof before it is accepted. When they reintroduced two old Signal bugs, the system proved the buggy versions were insecure. Paper:

Your heart, brain, and immune system share the same DNA sequence. So how can a single-letter change affect disease in some cells, while sparing the rest? AlphaGenome 2 is our new AI model that zooms in on specific cells to help scientists understand what drives disease. 🧵

AlphaGenome 2 is helping uncover the cellular drivers of disease, giving scientists a powerful tool to predict how DNA variants impact specific cell types. Every cell in our body shares the same DNA blueprint, but different cell types (like heart muscle cells vs. immune cells) read that blueprint differently. This new @GoogleDeepMind model predicts how these specialized cells interpret DNA, turning genetic code into biological insights. Building on AlphaGenome 1 this makes it significantly easier for researchers to link genetic findings to the root causes of disease in the specific cells where they actually unfold.