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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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Embodied LLM Misaligned Actions

Updated 12/29/2024

Embodied Large Language Models (LLMs) are vulnerable to manipulation via voice-based interactions, leading to the execution of harmful physical actions. Attacks exploit three vulnerabilities: (1) cascading LLM jailbreaks resulting in malicious robotic commands; (2) misalignment between linguistic outputs (verbal refusal) and physical actions (command execution); and (3) conceptual deception, where seemingly benign instructions lead to harmful outcomes due to incomplete world knowledge within…

BadRobot: Manipulating Embodied LLMs in the Physical World
Affects: BERT, GPT-3.5 Turbo, GPT-4 Turbo +2 more

Source: arXiv

Application layer
Jailbreak
Injection
Side channel

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.