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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分53

OpenAI 扩大前沿模型失范行为监测范围

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一则转述称,OpenAI 的监测现已覆盖 GPT-6 Astra 级模型的强化学习训练、评估和工具使用环境,以及内部 Codex 流量和客户使用相关网络安全模型工具的活动。活动最多经过四层筛查;OpenAI 称,若将这套系统用于回放 Hugging Face 事件,安全团队本可在沙箱逃逸约 30 分钟后收到警报。

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@rohanpaul_ai

https://t.co/WLYQeuvVTA

回复Rohan Paul@rohanpaul_ai
After the Hugging Face breach, OpenAI extended misalignment monitoring across frontier model training and deployment. OpenAI has revealed the 4-layer monitoring system it uses to catch frontier AI agents misbehaving. Says the Hugging Face breach began in internal cybersecurity evaluations where OpenAI ran no misalignment monitors. > Before, OpenAI’s misalignment monitors mainly watched its internal coding agents, so the Hugging Face breach began in cyber evaluations that nobody was monitoring for misbehavior. > Now the monitors cover every RL run, evaluation and tool-use setup for GPT-6 Astra-class models, all internal Codex traffic, and customer tool use of Astra-class cyber models. > Activity is screened in up to 4 layers, from cheap activation probes to an AI reviewer to investigator agents checking network logs, and top alerts typically page humans within 15 minutes. > OpenAI says this setup, replayed on the Hugging Face incident, would have alerted security about 30 minutes after the sandbox escape and more than 30 hours before Hugging Face was breached.
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