Shuffling Defense

Transformer research probes security flaws, training dynamics, and in-context learning limits

Researchers have identified vulnerabilities in the shuffling defense mechanism used to secure Transformer models during inference, demonstrating an attack that can extract model weights by aligning permuted activations.…