CMU研究：OpenClaw日志无法证明违规行为
CMU研究警示：AI代理日志无法证明违规，需设计机器可读日志
CMU新研究发现OpenClaw的日志在4项政策违规中均无法提供可证明的证据。研究测试了696次违规运行，来自3个基准测试，检查器仅能证明42.2%的违规情况。当批准信息仅存在于聊天消息中时，检查器经常失败。作者估计，通过结构化的批准记录，可验证性可提升至83.0%，每次会话的区块链费用不到1美分。
New Carnegie Mellon paper finds that OpenClaw's logs left 0 of 4 policy violations provable, a warning for any team relying on agent logs for audits.
They found that most agent policy violations in its tests could not be proven from logs, often because approvals and permissions were buried in chat text.
Also finds that only 10% to 30% of violating runs needed human judgment, so most agent rule breaks could be checked by code with better logs.
Safety work mostly tries to stop agents before they misbehave. When a mistake slips through, like a wiped inbox or a bad payment, users get little beyond slow, capped, case-by-case refunds.
In verifiable agent insurance, a provider posts a deposit on a blockchain and promises rules a program can check, like paying only approved merchants. A neutral verifier compares the agent's tool-call log with on-chain hashes, and if a rule was broken, the deposit pays the user.
Tested on 696 rule-breaking runs from 3 benchmarks, the checker proved 42.2%, often failing where approvals lived only in chat messages. With structured approval records, the authors estimate 83.0%, at under 1¢ of blockchain fees per session.
Design your agent so every permission, its scope, and each risky action land in a machine-readable log.
