Large language models (LLMs) like OpenAI’s ChatGPT, Anthropic’s Claude and Google Gemini are increasingly being used to help robots perform tasks, but what if LLMs could be exploited to turn helpful robots into harmful robots?

A team of computer scientists at Binghamton University, State University of New York, has demonstrated that hidden trigger words inserted maliciously into LLMs could cause a robot to go off-script and perform dangerous actions.

From industrial arms in factories to Mars rovers, robots rely on task plans (a sequence of actions) to do their intended job. Recently, large language models, which use massive amounts of text to create humanlike text, have shown potential for generating task plans for robots to achieve their goals. Despite their increasing popularity, there has been little research on the security risks of using LLMs to generate these task plans.