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New MuTRAP attack targets LLM-based robot task planning systems

By PulseAugur Editorial · [1 sources] ·

Researchers have developed MuTRAP, a novel multi-trigger trojan attack targeting large language model (LLM)-assisted robot task planning systems. This attack injects backdoors using a small set of task-specific parameters, bypassing the need to modify the entire LLM. The method includes a trigger optimization technique to select the most effective multiple trigger words for various robotic applications, aiming to highlight vulnerabilities and promote the development of more secure robot intelligence. AI

IMPACT Highlights potential security vulnerabilities in LLM-driven robotic systems, prompting research into more robust defenses.

RANK_REASON The cluster contains an academic paper detailing a new attack method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New MuTRAP attack targets LLM-based robot task planning systems

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The cluster contains an academic paper detailing a new attack method. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 Svenska(SV) · Mohaiminul Al Nahian, Zainab Altaweel, David Reitano, Sabbir Ahmed, Shiqi Zhang, Adnan Siraj Rakin ·

    MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systems

    arXiv:2504.17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action. Recently, large pretrained models have demonstrated impressive performance in task planning. For instance, large language models (LLMs) …

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