Jinhao Hu, Bardia Mohammadi, Mofasshara Binte Rafique, Lars Henning Klein, Akhil Arora, Ashvin Goel, Laurent Bindschaedler · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28093 · open-access PDF
AI代理人保留长期内存,其中大部分来自网页和工具结果。代理利用,运行该模型的软件不会记录谁可能在该内存上采取行动,所以在收集的页面中隐藏的指令可以被视为用户自己的指令。我们建议ClawMMU,一个保护层,以其所有者,范围,起源和权威标签每个内存片。ClawMMU检查这些标签,每次内容进入模型的背景,被写入存储,从存储中返回或驱动工具呼叫。
Machine translation (Meta M2M100); the English original follows.
AI agents keep long-term memory, much of which comes from web pages and tool results. Agent harnesses, the software that runs the model, do not record who may act on this memory, so an instruction hidden in a fetched page can be treated as the user's own instruction. We propose ClawMMU, a protection layer that labels every piece of memory with its owner, scope, origins, and authority. ClawMMU checks these labels whenever content enters the model's context, is written to storage, returns from storage, or drives a tool call. Its central rule is that information may rise in authority, but authori
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