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arXiv · 2610.10620

When AI Finds Hidden Messages, Does It Report?

William Guey·Rashik Jahangir·Pierrick Bougault·Vitor D. de Moura·Wei Zhang·José O. Gomes
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Abstract

When an assistant encounters a message for another AI, does it tell its user? Four fixed model-provider deployments perform simulated source tasks in 1,280 ordinary-note and 128 enhanced-note sessions. Harmless and harmful messages have matched plaintext and ROT13 versions, with no-message controls. Observers receive no decoder or decoded meaning; a requested reference code incentivizes inspection. Asking for reports increases rule-detected notifications identifying another AI as recipient by 53.1 percentage points for harmless ROT13 messages and 54.7 for harmful ones. This is a joint inspection, recognition, and notification effect; missing-response bounds are 38.3--77.3 and 36.7--78.1 points. Model-based trace checks identify eleven ordinary plaintext cases where agents interpret the message but do not notify their user. Seven encoded omissions are verified with enhanced notes; ordinary encoded omissions remain unverified. Seven simulated filename disclosures coexist with accurate review-status answers, and two answers use a planted false count. Interpretation, notification, and authorized task performance are distinct outcomes.

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William Guey, Rashik Jahangir, Pierrick Bougault, Vitor D. de Moura, Wei Zhang, José O. Gomes. 2026-10-07. When AI Finds Hidden Messages, Does It Report?. https://arxiv.org/abs/2610.10620

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