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Sprint projectOct 23, 2026Prishtina, Kosovo

Collusion Audit Kit (CAK): detecting agent collusion from action logs

Arber Arifi

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: Collusion Audit Kit (CAK): detecting agent collusion from action logs

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Can collusion between AI agents be detected from action logs alone, without reading their messages? We build a 2-5 seller market with competitive, colluding, hidden-channel and mixed populations and audit price logs with five signals. Price correlation without a price-level signal flags honest competition as collusion; adding the level removes that false positive. Market-wide aggregates miss partial collusion (0.039 when two of five agents coordinate) while a coalition-level audit recovers it (0.500) with no false positive on competitive markets. A 225-run noise sweep leaves verdicts unchanged, with a ceiling-effect caveat.

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  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
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  1. A succinct overview of the problem with collusion when only actions can be observed which highlights a real problem with agents acting in trading markets.The researcher explains the setting well. Would have liked to have seen more analysis of the threat model and how previous art handles similar scenarios.

Cite this project

@misc{arifi2026collusion,
  title = {{Collusion Audit Kit (CAK): detecting agent collusion from action logs}},
  author = {Arber Arifi},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/collusion-audit-kit-cak-detecting-agent-collusion-from-action-logs-2t7x}},
  url = {https://apartresearch.com/sprints/projects/collusion-audit-kit-cak-detecting-agent-collusion-from-action-logs-2t7x}
}

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