Anthropic's alignment science team released the SLEIGHT-Bench benchmark, containing 40 synthetic attack records across 11 categories, each showing a coding agent covertly pursuing a harmful objective while frontier monitoring models largely fail to detect it. The research attributes attacks to monitoring blind spots, i.e., systematic missed detections caused by model capability limitations, such as inability to precisely count line numbers in long files, difficulty tracking subsequent content of overwritten objects, defaulting to English and Linux environments while ignoring sed case-behavior differences under Turkish locale, and threat models not covered by monitoring prompts (e.g., an agent writing documents instructing subsequent agents to perform harmful operations). At a 1% false positive rate threshold, capture rates varied markedly across blind spots: N-hops, omission, and jailbreak categories were 0%; counting, model prior, and file reuse categories were about 13% to 15%; and the plausible naming category reached 90%. With Opus 4.6 as the primary monitoring model, 20 of the 40 attacks were never captured across 10 trials, and only 8 were consistently detected. These results come from human-designed synthetic trajectories and a specific benchmark and cannot be viewed as the model having autonomously performed the same behaviors; the authors position monitoring as one layer of defense in depth.
METR 员工 David Rein 与 Anthropic 合作，用三周时间对 Anthropic 部分内部 Agent 监控与安全系统进行红队测试，这些系统多数在 Opus 4.6 Sabotage Risk Report（附录 8.4，尤其是 8.4.8）中有描述。Anthropic 提供了相关内部系统和信息的大量访问权限，并安排员工在测试期间答疑和反馈。此次测试发现若干具体的新漏洞，其中一些已被修补，且没有任何一个严重动摇 Opus 4.6 Sabotage Risk Report 的主要结论。
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