DeepMind AI finds flaws in 1024-bit RSA encryption

The research arrives as part of a broader 2026 effort in which AI models are being used to probe the mathematical foundations of encryption. Historically, uncovering vulnerabilities of this kind could take years of dedicated human effort. DeepMind's framing is that AI changes the tempo: the humans still steer the research, but the models do much of the heavy exploratory lifting, testing ideas faster than a team of mathematicians could on their own. The findings also arrive alongside other 2026 findings involving attacks on post-quantum candidates such as HAWK, suggesting a wider push to stress-test the assumptions underlying both current and next-generation cryptography. The immediate audience is anyone still running 1024-bit RSA, while the research does not claim that current systems using stronger key sizes face any immediate risk.