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Backdoored robot tries its hand at finger chopping and cat cooking

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ai and ml

No actual digits or cats were harmed beyond the number crunching that went into this LLM poisoning experiment

Researchers affiliated with Binghamton University in New York have demonstrated the dangers of poisoned LLMs in physical AI by getting them to generate instructions for robots to cut a model hand or put a cat on a stove in a simulation. Fortunately, they also have a potential defense.

A team of researchers – Mohaiminul Al Nahian, Zainab Altaweel, David Reitano, Sabbir Ahmed, Shiqi Zhang, and Adnan Siraj Rakin – devised a multi-trigger trojan attack that targets robotic task planning.

The technique, dubbed MuTRAP , is described in two papers presented at the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems.

MuTRAP, short for Multi-trigger TRojans Attacking Robot Task Planning Systems, starts by injecting a backdoor into an LLM using a set of parameters for domain-specific fine-tuning – a common training step to equip a generalist model with specific skills.

The…

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