DeepMind agents find faster attacks on legacy 1024-bit RSA

Google DeepMind researchers, working with UC San Diego and Inria, used human-supervised AI agents to find new attacks on legacy 1024-bit RSA, Interesting Engineering reports. One finding is that once an attacker controls roughly half or more of a signed data block, padding gives almost no extra protection against forged signatures; a sandbox test on an already-solved academic benchmark reproduced the result with 3.5 times less CPU time. For the case where an attacker controls only a small part, such as a 32-byte fingerprint, the agents found an algorithm that in theory improves on the previous best attack by about 1,600 times. A second result cuts the average cost of factoring each extra 1024-bit key in a batch by about 30 times. DeepMind says the findings do not threaten modern encryption.