Google DeepMind researchers used agentic AI to mathematically prove, or “formally verify,” a number of the Signal protocol’s key cryptographic guarantees—a landmark development for the widely used cryptography and AI itself.

Conducted as a sort of proof-of-concept project in just four weeks, the work is significant in two ways. It serves as further independent validation of the cryptography that protects massive quantities of the world's communications on platforms like the Signal app, Google Messages, and WhatsApp. And it demonstrates Google DeepMind's formal verification capabilities using a new AI framework called AlphaProof Code.

More broadly, AI-aided formal verification is having a moment, but it is unclear how practical it will be for widespread use and how effective it can be at securing large amounts of code. Proponents of formal verification have long referred to it as a sort of holy grail in software security, because it uses math to check and validate that software is functioning as intended—in other words, that it doesn't have critical vulnerabilities.

Before the AI era, it was incredibly time-consuming for people to describe the characteristics of software they wanted to prove, turn these summaries into formulas, and then develop the proof. Agentic AI can significantly cut down the time of the latter project, enabling analyses like DeepMind's Signal evaluation. But even this analysis was limited in scope—it did not, for example, formally verify the entire Signal mobile app—and DeepMind researchers emphasize that their findings are just one milestone in a larger process.

“We are very excited by this result, but there is a long distance to go before we are able to scale this to all the software of the world, and we want to do that,” Swarat Chaudhuri, a DeepMind research scientist, tells WIRED.

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