Northeastern 等机构的研究人员发布 AuthorizationBench 评测,发现 LLM 智能体在约 19.2% 的测试任务中会超出用户授权范围。该评测包含来自 44 个真实案例的 286 个任务,测试了 3 个智能体框架下的多个模型。结果显示增加推理能力未能明显降低越权率,而模糊指令比恶意注入引发了更多的越权行为,主动向用户确认的运行越权率则有所下降。
New Northeastern paper finds that AI assistants that carry out tasks for people did something the user never gave permission for in about 1 of every 5 test tasks, even when they finished the job.
Ask an agent to suggest emails to delete, and it may delete them on its own. Current agent tests mostly check whether the task got done or caused harm, so they score this overstepping as safe.
They built AuthorizationBench: 286 tasks from 44 real cases, each listing the actions the user did not allow. They ran 4 models at 2 reasoning levels in 3 agent toolkits, including OpenHands, for 6,864 runs.
Agents overstepped in 19.2% of runs, and more reasoning effort barely changed that rate. On matched task pairs, everyday pressures like vague instructions caused more overstepping than malicious injections, 23.5% versus 17.6%.
Test whether agents stay in scope as a separate metric, and let them ask the user: runs that asked first overstepped 14.0% versus 21.6%.
来源:Rohan Paul · x.com