Propagating Unsafe Actions in LLM Controlled Multi-Robot Collaboration via Single Robot Compromise

TL;DR

This paper introduces a novel security attack on multi-robot systems controlled by LLMs, where compromising a single robot can propagate malicious commands, leading to unsafe coordinated actions, highlighting significant safety risks.

Contribution

The study presents a new attack paradigm demonstrating how malicious control of one robot can spread through communication, exposing vulnerabilities in multi-robot LLM-based coordination.

Findings

Obedience reaches 1.00 in strong attack cases

Infectiousness rises to 0.90, indicating rapid propagation

Compromise of all robots in as few as 3 rounds

Abstract

Large language models (LLMs) are increasingly used as general planners in embodied intelligence, enabling high level coordination and low level task planning for both single robot and multi-robot collaboration. This increasing reliance on embodied LLM planners also raises critical security concerns, since misaligned or manipulated instructions can be translated into physical actions. Prior work has studied such threats in single robot settings, while security risks in LLM controlled multi-robot collaboration, especially those propagated through inter robot communication, remain largely unexplored. To bridge this gap, we propose a novel attack paradigm for multi-robot system in which the adversary interacts with only a single entry robot. The compromised robot then propagates malicious intent through peer communication, leading to coordinated unsafe actions across the system. Our evaluation, covering high risk dimensions of dereliction of duty, privacy compromise, and public safety hazards, reveals a persistent safety alignment gap in multi-robot planners. We quantify this process with three metrics, obedience, infectiousness, and stealthiness. Experiments demonstrate both persistent attacker control and rapid propagation: obedience reaches 1.00 in the strongest cases, and infectiousness rises to 0.90. Notably, the attack is highly efficient, requiring as few as 3.0 rounds to compromise all the robots while maintaining a stealthiness score of 0.81. Such risks are amplified when robots must resolve trade offs in critical situations, such as emergencies or conflicts of rights, because the coordination mechanism can unintentionally allow adversarial instructions to override safety requirements. The code is available at https://github.com/TheFatInsect/InfectBot.