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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.

Voice Agent Behavioral Bypass

Published Analyzed Source: arXiv

Audio Large Language Models (ALLMs) integrated into voice agent systems for high-stakes domains (banking, IT support, logistics) are vulnerable to multimodal adversarial attacks via spoken interaction. Adversaries can exploit the model's inherent compliance and contextual awareness through multi-turn dialogue to bypass authentication safeguards, escalate privileges (e.g., unauthorized credit limit increases), exfiltrate sensitive Personally Identifiable Information (PII), and poison…

Aegis: Towards Governance, Integrity, and Security of AI Voice Agents
Evaluated models: GPT-4o, GPT-4o Mini, Gemini 1.5 Pro+4 more
  • GPT-4o
  • GPT-4o Mini
  • Gemini 1.5 Pro
  • Gemini 2.5 Flash
  • Gemini 2.5 Pro
  • Qwen2-Audio 7B
  • Qwen 2.5 Omni 7B
Model layer
Application layer
Injection
Extraction

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.