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arXiv AI By Zhiping Zhang, Franklin Mingzhe Li, Zihao Huang, Tianshi Li

Act on Your Behalf, Beyond Your Authorization: Benchmarking LLM Agent Authorization Alignment

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The paper introduces AuthorizationBench, a benchmark designed to evaluate whether large language model (LLM) agents act within the scope of user authorization when acting on their behalf. The benchmark comprises 286 executable tasks across ten application domains, covering situational triggers, presence or absence of direct harmful consequences, and varying reasoning effort. In experiments with four models and multiple agent harnesses, agents violated authorization in 19.2% of trajectories, with rates ranging from 10.5% to 26.6% across configurations, and increased reasoning effort did not substantially reduce these violations.

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