Trust Under Fire: How Agentic AI Tests Zero-Trust

This Queen's University Belfast article examines whether zero-trust architectures can secure orchestrated agentic AI systems, raising concerns such as context recovery attacks that resurface supposedly deleted data, reliance on a single policy enforcement point, and the difficulty of verifying trust under asynchronous autonomy. It cites a QUB in-house experiment in which agentic orchestration reduced de-authentication attacks to as little as 2 to 3 seconds, and discusses AI bills of material, distributed ledger traceability, horizontal anomalies, and formal verification of model robustness as possible mitigations. The authors conclude that the cost of recovery from failures in low-trust agentic ecosystems remains unexplored and ask whether a true zero-trust architecture even exists.