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Last analyzed Sep 9, 2026

Language Model Security Database

985 research findings · 1119 evaluated models

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1 entry

Matches every word across titles, descriptions, sources, affected systems, and models.

Joint Audio-Text Jailbreak

Published Analyzed Source: arXiv

Spoken Language Models (SLMs) are vulnerable to Joint Audio-text Multimodal Attacks (JAMA), which bypass safety alignments by simultaneously perturbing both text and audio inputs. The vulnerability exploits the combined optimization of a discrete text suffix via Greedy Coordinate Gradient (GCG) and a continuous audio perturbation via Projected Gradient Descent (PGD). This joint gradient-based attack pushes the model's hidden layer representations into a distinct subspace far from the benign…

On Optimizing Multimodal Jailbreaks for Spoken Language Models
Evaluated models: Qwen2-Audio 7B Instruct, Qwen 2.5 Omni 7B, Audio Flamingo 3+1 more
  • Qwen2-Audio 7B Instruct
  • Qwen 2.5 Omni 7B
  • Audio Flamingo 3
  • Gemma 3n E2B
Prompt layer
Jailbreak
Multimodal
White-box

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.

Discovery and publication are separate: new papers enter a candidate queue, then require human review and explicit approval before publication. Updates follow that review process, not a guaranteed daily publishing schedule. “Last analyzed” is the newest analysis date among published entries; it does not mean that all recent research has been covered.