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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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2 entries

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

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
Affects: GPT-4o, GPT-4o Mini, Gemini 1.5 Pro +4 more

Source: arXiv

Updated 12/29/2024

A vulnerability in the voice mode of GPT-4o allows bypassing safety restrictions through a novel "Voice Jailbreak" attack. This attack leverages principles of fictional storytelling (setting, character, plot) to craft audio prompts that persuade the LLM to generate responses violating OpenAI's usage policies, including generating content related to illegal activities, hate speech, physical harm, fraud, pornography, and privacy violations. The attack's success rate is significantly higher than…

Voice Jailbreak Attacks Against GPT-4o
Affects: GPT-3.5 Turbo, GPT-4, GPT-4o

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.