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GROB: A Multi-Agent Architecture for Public-Trace Investigation of Candidate Agentic Activity
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Chiara Bonfanti, Cataldo Basile

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ResearcharXiv cs.AI

GROB: A Multi-Agent Architecture for Public-Trace Investigation of Candidate Agentic Activity

arXiv:2610.11467v1 Announce Type: cross Abstract: We present GROB, a multi-agent architecture for investigating candidate autonomous-agent activity through public Internet traces when privileged telemetry is unavailable. The system performs controlled, read-only collection of public traces and preserves selected observations for later resolution. In a frozen September 2026 corpus, several collected traces became more informative as additional public evidence emerged. The strongest result concerns Census-labelled identifiers captured on 9 September. Public revision records later resolved these identifiers to specific Census requests from 16 - 17 June. Other results show weaker links between traces collected by GROB and evidence reconstructed or reported later. These links vary in strength, and only some can be tied to specific public records. The results show that sparse public traces can remain useful even before their significance is fully understood. Such evidence can support later reconstruction, but public traces alone do not establish organizational attribution. Execution identity presents a separate problem, as continuity of agent identity remains an active research question for autonomous language-model agents.

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This story was published by arXiv cs.AI and written by Chiara Bonfanti, Cataldo Basile. SyncAI.news shows a preview; the complete article is on the publisher's site.

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