Codec-Robust Attacks on Audio LLMs
Researchers have developed a novel adversarial attack called CodecAttack that bypasses compression defenses in audio large language models (LLMs). Unlike previous methods that directly perturbed audio waveforms, CodecAttack optimizes perturbations within a neural audio codec's latent space. This technique proved highly effective, achieving an average 85.5% attack success rate on Opus compression and demonstrating transferability to other codecs like MP3 and AAC-LC. AI
IMPACT Demonstrates that lossy compression is not a reliable defense against adversarial audio, posing a practical threat to deployed audio LLM systems.