On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao; Yichen Zhang; Yingshuo Wang; Yang Deng; Yanyan Zhao; Xuda Zhi; Yongbo Huang; HaoHe; Wanxiang Che; Bing Qin; Ting Liu

arXiv · 2604.16968

On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao·Yichen Zhang·Yingshuo Wang·Yang Deng·Yanyan Zhao·Xuda Zhi·Yongbo Huang·HaoHe·Wanxiang Che·Bing Qin·Ting Liu

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Abstract

Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduces underexplored safety risks. In this study, we investigate how experience accumulation and utilization in self-evolving agents affect safety performance across web-based and embodied environments. Notably, experience gathered solely from benign tasks can still compromise safety in high-risk scenarios. Further analysis attributes this degradation to the execution-oriented nature of accumulated experience, which reinforces agents' tendency to act rather than refuse. In more realistic settings where agents encounter both benign and harmful tasks, refusal-related experience mitigates safety decline but induces over-refusal, revealing a fundamental safety-utility trade-off. Overall, our findings expose inherent limitations of current self-evolving agents and call for more principled strategies to ensure safe and reliable adaptation.

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BibTeX RIS

Weixiang Zhao, Yichen Zhang, Yingshuo Wang, Yang Deng, Yanyan Zhao, Xuda Zhi, Yongbo Huang, HaoHe, Wanxiang Che, Bing Qin, Ting Liu. 2026-04-18. On Safety Risks in Experience-Driven Self-Evolving Agents. https://arxiv.org/abs/2604.16968

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