When AI Finds Hidden Messages, Does It Report?

Title:When AI Finds Hidden Messages, Does It Report?

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.

2 figures, 8 tables. Data and code (v1.0.0): this https URL

Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)

arXiv:2610.10620 [cs.CR]

(or arXiv:2610.10620v1 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2610.10620 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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