On Optimizing Multimodal Jailbreaks for Spoken Language Models

Multimodal jailbreaks that simultaneously attack both text and audio inputs are 1.5x to 10x more effective than single-modality attacks against spoken language models. This research exposes critical vulnerabilities in voice-enabled AI systems that traditional text-only security measures miss entirely.