Researchers have identified exploitable vulnerabilities in the ML-DSA (Module-Lattice-Based Digital Signature Algorithm) implementation, as detailed in a newly released technical paper. The findings highlight security flaws that could allow attackers to compromise the cryptographic scheme, which is a key component in post-quantum cryptography standards. These bugs pose significant risks to systems relying on ML-DSA for secure digital signatures.
machine-learning, ai-safety, ai-research