Google DeepMind Melds Humans and AI Agents to Vet Signal's Secure Messaging Techniques
The researchers say the proof-of-concept found no new vulnerabilities and released the specification and proof to support further verification work.
- Google DeepMind researchers used agentic AI to formally verify key cryptographic guarantees within the Signal protocol, a landmark development that also validates WhatsApp and Google Messages security.
- Proponents consider formal verification a holy grail in software security because it uses mathematical proofs to guarantee code functions without vulnerabilities, yet traditionally required heroic efforts consuming decades of work.
- The four-week project required a team of five people and generated 6.5 million lines of Lean code, utilizing a human-AI collaboration process that allowed agents to contribute while maintaining human review at key junctures.
- Researchers used AlphaProof Code to verify Signal's post-quantum PQXDH handshake and Triple Ratchet design; when tested against older versions containing known vulnerabilities, the system correctly identified them.
- Swarat Chaudhuri, a DeepMind research scientist, noted that while "the dream is definitely to scale this up," significant work remains before applying this technology to all software.
11 Articles
11 Articles
Google DeepMind analysis proves Signal and WhatsApp encryption is secure
The Signal protocol has long been considered the gold standard for end-to-end encrypted messaging, with Edward Snowden a notable advocate. Now a Google DeepMind analysis has “formally verified” the security of the protocol. In addition to its use in the Signal app, the same protocol is also used by WhatsApp and Google Messages, and the work has been described as “a landmark development” … more…
DeepMind's Partial Signal Proof Is A Lab Result, Not A Security Control » Saipien
Four weeks is a short clock for a cryptographic proof, and this one did not start at zero. Google DeepMind researchers say earlier formal verification by the Signal Foundation gave them a head start. The public account of the work is Lily Hay Newman’s November 10, 2026 report in WIRED, plus statements from DeepMind and […]
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