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BARC-Bench发布:新基准揭示AI代理在隐性安全边界上的系统性风险

2026年10月26日,研究者在arXiv发布论文(编号2610.32024v1),正式推出BARC-Bench——一个包含110项任务、覆盖九类模拟办公环境的AI安全评估基准,聚焦用户指令中因安全边界未明示(underspecification)导致的代理行为风险。

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BARC-Bench: Benign Asks, Risky Consequences

arXiv:2610.32024v1 Announce Type: new Abstract: Task instructions from users for agents are inherently underspecified, especially regarding safety boundaries--creating behavioral risks. To study these risks, we introduce BARC-Bench, a collection of 110 tasks across nine simulated workspace environments where benign requests leave openings for unsafe actions. In this benchmark, we evaluate agent behavior against safety boundaries established by workspace records, implicit environmental context, and unstated social norms. For example, an agent asked to schedule off-boarding discussions must arrange the meeting without prematurely revealing an employee's resignation through a shared calendar invitation. Evaluating four frontier model configurations across five attempts per task reveals that m

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BARC-Bench: Benign Asks, Risky Consequences
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