From Thinker to Society: Security in Hierarchical Autonomy Evolution of AI Agents
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866908904733016064 |
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| author | Zhang, Xiaolei Zhou, Lu Xu, Xiaogang Wu, Jiafei Du, Tianyu Huang, Heqing Peng, Hao Liu, Zhe |
| author_facet | Zhang, Xiaolei Zhou, Lu Xu, Xiaogang Wu, Jiafei Du, Tianyu Huang, Heqing Peng, Hao Liu, Zhe |
| contents | Artificial Intelligence (AI) agents have evolved from passive predictive tools into active entities capable of autonomous decision-making and environmental interaction, driven by the reasoning capabilities of Large Language Models (LLMs). However, this evolution has introduced critical security vulnerabilities that existing frameworks fail to address. The Hierarchical Autonomy Evolution (HAE) framework organizes agent security into three tiers: Cognitive Autonomy (L1) targets internal reasoning integrity; Execution Autonomy (L2) covers tool-mediated environmental interaction; Collective Autonomy (L3) addresses systemic risks in multi-agent ecosystems. We present a taxonomy of threats spanning cognitive manipulation, physical environment disruption, and multi-agent systemic failures, and evaluate existing defenses while identifying key research gaps. The findings aim to guide the development of multilayered, autonomy-aware defense architectures for trustworthy AI agent systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_07496 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Thinker to Society: Security in Hierarchical Autonomy Evolution of AI Agents Zhang, Xiaolei Zhou, Lu Xu, Xiaogang Wu, Jiafei Du, Tianyu Huang, Heqing Peng, Hao Liu, Zhe Cryptography and Security Artificial Intelligence Artificial Intelligence (AI) agents have evolved from passive predictive tools into active entities capable of autonomous decision-making and environmental interaction, driven by the reasoning capabilities of Large Language Models (LLMs). However, this evolution has introduced critical security vulnerabilities that existing frameworks fail to address. The Hierarchical Autonomy Evolution (HAE) framework organizes agent security into three tiers: Cognitive Autonomy (L1) targets internal reasoning integrity; Execution Autonomy (L2) covers tool-mediated environmental interaction; Collective Autonomy (L3) addresses systemic risks in multi-agent ecosystems. We present a taxonomy of threats spanning cognitive manipulation, physical environment disruption, and multi-agent systemic failures, and evaluate existing defenses while identifying key research gaps. The findings aim to guide the development of multilayered, autonomy-aware defense architectures for trustworthy AI agent systems. |
| title | From Thinker to Society: Security in Hierarchical Autonomy Evolution of AI Agents |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2603.07496 |