AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2025-02-07 DOI:10.1145/3716628
Zehang Deng, Yongjian Guo, Changzhou Han, Wanlun Ma, Junwu Xiong, Sheng Wen, Yang Xiang
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Abstract

An Artificial Intelligence (AI) agent is a software entity that autonomously performs tasks or makes decisions based on pre-defined objectives and data inputs. AI agents, capable of perceiving user inputs, reasoning and planning tasks, and executing actions, have seen remarkable advancements in algorithm development and task performance. However, the security challenges they pose remain under-explored and unresolved. This survey delves into the emerging security threats faced by AI agents, categorizing them into four critical knowledge gaps: unpredictability of multi-step user inputs, complexity in internal executions, variability of operational environments, and interactions with untrusted external entities. By systematically reviewing these threats, this paper highlights both the progress made and the existing limitations in safeguarding AI agents. The insights provided aim to inspire further research into addressing the security threats associated with AI agents, thereby fostering the development of more robust and secure AI agent applications.
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面临威胁的人工智能代理:主要安全挑战和未来途径的调查
人工智能(AI)代理是一种软件实体,它可以根据预定义的目标和数据输入自主执行任务或做出决策。人工智能代理能够感知用户输入,推理和规划任务,并执行动作,在算法开发和任务性能方面取得了显着进步。然而,它们带来的安全挑战仍未得到充分探讨和解决。本调查深入研究了人工智能代理面临的新出现的安全威胁,将其分为四个关键的知识缺口:多步骤用户输入的不可预测性、内部执行的复杂性、操作环境的可变性以及与不受信任的外部实体的交互。通过系统地回顾这些威胁,本文强调了在保护人工智能代理方面取得的进展和现有的局限性。所提供的见解旨在激发进一步研究,以解决与人工智能代理相关的安全威胁,从而促进更健壮和安全的人工智能代理应用程序的开发。
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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