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Updated 7/21/2026, database is current

Language Model Security Database

959 research findings · 1077 evaluated models

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A vulnerability exists in trimodal audio-video-language models where an attacker can systematically degrade multimodal reasoning through untargeted, audio-only adversarial perturbations. By optimizing a shared perturbation $\delta$ applied to the audio channel, an attacker can manipulate internal representations—specifically targeting audio encoder embeddings and cross-modal attention mechanisms—without modifying visual or textual inputs. The attack exploits the model's reliance on the audio…

SoundBreak: A Systematic Study of Audio-Only Adversarial Attacks on Trimodal Models
Affects: VideoLLAMA2, Qwen 2 7B Instruct, Whisper Large-v2 +1 more

Source: arXiv

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.