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About this paper
Shuwen Xu, Zhitao He, Yi R. Fung
REDACT is a framework that safeguards proprietary procedural skills embedded in AI agent execution traces while maintaining auditability. It quantifies the vulnerability of raw traces to skill extraction and demonstrates its ability to substantially reduce skill transfer to downstream methods, integrating behavioral watermarking for robust provenance tracking across a new benchmark called CAPTRACEBENCH.
Key insights
- Raw agent execution traces are highly vulnerable attack surfaces, allowing downstream methods to recover and reuse a substantial portion of proprietary procedural skills, significantly improving agent performance.
- Effective procedural skill protection requires targeted abstraction of specific key items rather than generic rewriting, as evidenced by the superior performance of key-information-guided rewriting in REDACT.
- Behavioral watermarking offers a viable mechanism for provenance tracking in agent traces, although the detectability varies between standalone and context-dependent hooks.
Summary by alphaXiv.
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