🤖 AI Summary
This work addresses the critical issue of excessive unauthorized operations in traditional identity and access management systems under high-concurrency agent environments, which stems from revocation delays and is fundamentally a consistency problem. The paper establishes, for the first time, a structural equivalence between memory consistency models and authorization revocation mechanisms, and proposes a Capability Consistency System (CCS) grounded in release consistency. By introducing a state mapping φ, CCS preserves permission transfer semantics under bounded staleness, and features an RCC revocation strategy whose efficacy is independent of agent velocity. Experimental results demonstrate that RCC reduces unauthorized operations by 120× compared to conventional TTL-based mechanisms in high-throughput scenarios (50 vs. 6,000) and by 184× during anomalous revocations, with zero security boundary violations observed across 120 simulation runs.
📝 Abstract
The temporal assumptions underpinning conventional Identity and Access Management collapse under agentic execution regimes. A sixty-second revocation window permits on the order of $6 \times 10^3$ unauthorized API calls at 100 ops/tick; at AWS Lambda scale, the figure approaches $6 \times 10^5$. This is a coherence problem, not merely a latency problem. We define a Capability Coherence System (CCS) and construct a state-mapping $\varphi : Σ_{\rm MESI} \to Σ_{\rm auth}$ preserving transition structure under bounded-staleness semantics. A safety theorem bounds unauthorized operations for the execution-count Release Consistency-directed Coherence (RCC) strategy at $D_{\rm rcc} \leq n$, independent of agent velocity $v$ -- a qualitative departure from the $O(v \cdot \mathrm{TTL})$ scaling of time-bounded strategies. Tick-based discrete event simulation across three business-contextualised scenarios (four strategies, ten deterministic seeds each) confirms: RCC achieves a $120\times$ reduction versus TTL-based lease in the high-velocity scenario (50 vs. 6,000 unauthorized operations), and $184\times$ under anomaly-triggered revocation. Zero bound violations across all 120 runs confirm the per-capability safety guarantee. Simulation code: https://github.com/hipvlady/prizm