SOURCE-LINKED INTELLIGENCE
Silent Sabotage: Internal State Triggered Backdoor Attacks on LLM-Powered Robotic Systems
The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reasoning and planning. While this paradigm shift accelerates progress, it also introduces novel security risks that remain largely unexplored. Current research into LLM backdoors has focused on attacks triggered by external stimuli, such as specific words, visual objects, or environmental states. These attacks, while potent, overlook a more insidious class of vulnerability where the trigger is internal to the agent's own operational logic. This pape
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T00:18:12.000Z
First collected: 2026-09-26T10:12:05.389Z. This is not the publication date.