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ResearchOctober 21, 2026

PROVISO: Provenance-Informed Action Selection for Secure LLM Agents

arXiv:2610.27115v1 Announce Type: new Abstract: LLM agents act on the external world through tools and third-party skills, so a single executed action can cause irreversible harm. Existing defenses judge a proposed action without tracking whether its content comes from the user…

Bo Yan, Qi Zhang, Ziwen Kan, Fnu Suya, Song Wang·arXiv — cs.AI
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  • 01.arXiv:2610.27115v1 Announce Type: new Abstract: LLM agents act on the external world through tools and third-party skills, so a single executed action can cause irreversible harm
  • 02.Existing defenses judge a proposed action without tracking whether its content comes from the user…

This material is provided as an extended analytical summary.

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Aggregated within AI Qazaqstan national intelligence stream with author attribution.

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