Mental Damage: Caption Poisoning Attacks on Retrieval-Augmented Text-to-Music Generation
Researchers have identified a new vulnerability in retrieval-augmented text-to-music generation systems, termed "Mental Damage." This attack involves poisoning the music caption database with crafted entries that subtly steer the AI's output without altering the user's original prompt. The dual-layer caption poisoning strategy preserves retrieval anchors while injecting misleading acoustic descriptors, leading to generations that align with an attacker's intent rather than the user's. This research highlights a practical integrity risk for AI systems that rely on external knowledge bases for creative generation. AI
IMPACT Highlights a new attack vector for creative AI systems, potentially impacting the integrity of AI-generated content.