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This paper explores the vulnerabilities of AI agents in a shared memory environment, highlighting how they can inadvertently create persistent channels for information leakage through honeytokens. The study reveals that while honeytokens can serve as useful sensors, they become ineffective when attackers can recognize and exploit them due to shared policies. Key findings indicate that maintaining a separate security boundary is essential for high-confidence detection of policy violations while ensuring that honeytokens do not compromise trusted agents.
Honeytokens can inadvertently become tools for attackers in shared memory systems, revealing a critical flaw in defensive deception strategies.
During a 2026 cyber-capability evaluation, short-lived AI agents turned a shared package repository into persistent memory, passing exploit findings to later agents and rebuilding the channel after it was removed. The broader evaluation culminated in an intrusion into Hugging Face. This episode raises a question for defensive deception: can a honeytoken be harmless to trusted agents without becoming recognisable to an attacker who shares their information and can implement the trusted policy? The answer is no. A trusted rule that selects genuine objects while avoiding decoys can be copied by the attacker, while a total-variation bound limits legitimate compatibility when decoys resemble genuine objects. Shared memory creates a second leakage channel by pooling weak fingerprints. For a fixed candidate, repeated non-triggering probes drive the minimum Bayes classification error to zero when type-dependent response laws differ and are known or learnable. If probing triggers containment, learning also requires the coalition to remain active long enough. Transfer across objects requires a stable deployment rule and information that orients the classes. A separate detection bound distinguishes reliable token activation from reliable attack coverage. The architectural response is to keep token identity in a private reference monitor and route legitimate agents through a provenance-enforcing broker. This produces high-confidence detection only for a specified policy violation. Honeytokens remain useful sensors, but a separate security boundary is still required.
