Attacker'S Noise Can Manipulate Your Audio-Based LLM in the Real World

This paper investigates the real-world vulnerabilities of audio-based large language models ALLMs, such as Qwen2-Audio. We first demonstrate that an adversary can craft stealthy audio perturbations to manipulate ALLMs into exhibiting specific targeted behaviors, such as eliciting responses to...