When Agents Talk: Honeytokens under Shared Memory

Computer Science > Cryptography and Security [Submitted on 11 Aug 2026] When Agents Talk: Honeytokens under Shared Memory Joshua S. Gans 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. Comments: artificial intelligence, cybersecurity, honeytokens, defensive deception, shared memory, intrusion detection Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2608.11436 [cs.CR]   (or arXiv:2608.11436v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2608.11436 Focus to learn more Submission history From: Joshua Gans [view email] [v1] Tue, 11 Aug 2026 21:03:19 UTC (25 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)