A Survey on Trustworthy LLM Agents: Threats and Countermeasures

Обзор заслуживающих доверия агентов на основе больших языковых моделей: угрозы и контрмеры
Kun Wang, Qingsong Wen, Yongfeng Zhang, Bo An, Xinfeng Li, Tianlong Chen, Miao Yu, Fanci Meng, Xinyun Zhou, Shilong Wang, Junyuan Mao, Linsey Pang
2025-08-03

LLM agent threatsTrustAgent frameworkmulti-agent systemstrustworthiness taxonomytrustworthy LLM agents
With the rapid evolution of Large Language Models (LLMs), LLMbased agents and Multi-agent Systems (MAS) have significantly expanded the capabilities of LLM ecosystems.This evolution stems from empowering LLMs with additional modules such as memory, tools, environment, and even other agents.However, this advancement has also introduced more complex issues of trustworthiness, which previous research focusing solely on LLMs could not cover.In this survey, we propose the TrustAgent framework, a comprehensive study on the trustworthiness of agents, characterized by modular taxonomy, multi-dimensional connotations, and * Miao Yu and Fanci Meng contribute equally to this paper.
1
Adding these modules introduces complex trustworthiness challenges that are not covered by research focused solely on standalone LLMs.
2
LLM agents and multi-agent systems expand LLM capabilities by integrating memory, tools, environments, and other agents.
3
The survey proposes the TrustAgent framework to comprehensively study trustworthy LLM agents.
4
TrustAgent characterizes agent trustworthiness through a modular taxonomy and multi-dimensional connotations.

LLM-based agents and multi-agent systems (MAS)

Their trustworthiness, including associated threats and countermeasures

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Publication Date
2025-08-03
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Authors
Kun Wang
Qingsong Wen
Yongfeng Zhang
Bo An
Xinfeng Li
Tianlong Chen
Miao Yu
Fanci Meng
Xinyun Zhou
Shilong Wang
Junyuan Mao
Linsey Pang
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