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The Bureaucracy of Speed: Structural Equivalence Between Memory Consistency Models and Multi-Agent Authorization Revocation

Vladyslav Parakhin

TL;DR

A Capability Coherence System (CCS) is defined and a state-mapping is constructed and 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.

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

The Bureaucracy of Speed: Structural Equivalence Between Memory Consistency Models and Multi-Agent Authorization Revocation

TL;DR

A Capability Coherence System (CCS) is defined and a state-mapping is constructed and a safety theorem bounds unauthorized operations for the execution-count Release Consistency-directed Coherence (RCC) strategy at , independent of agent velocity.

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 unauthorized API calls at 100 ops/tick; at AWS Lambda scale, the figure approaches . This is a coherence problem, not merely a latency problem. We define a Capability Coherence System (CCS) and construct a state-mapping preserving transition structure under bounded-staleness semantics. A safety theorem bounds unauthorized operations for the execution-count Release Consistency-directed Coherence (RCC) strategy at , independent of agent velocity -- a qualitative departure from the 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 reduction versus TTL-based lease in the high-velocity scenario (50 vs. 6,000 unauthorized operations), and under anomaly-triggered revocation. Zero bound violations across all 120 runs confirm the per-capability safety guarantee. Simulation code: https://github.com/hipvlady/prizm
Paper Structure (49 sections, 2 theorems, 4 equations, 3 figures, 8 tables, 1 algorithm)

This paper contains 49 sections, 2 theorems, 4 equations, 3 figures, 8 tables, 1 algorithm.

Table of Contents

  1. The Coherence Framing
  2. Contributions.
  3. Theoretical Foundations
  4. Cache Coherence Essentials
  5. Failure Containment
  6. Information-Theoretic Framing
  7. Formal Model
  8. Capability Coherence System
  9. SWMR Adaptation.
  10. State Mapping Function
  11. Scope of equivalence.
  12. Damage Bound Functions
  13. Related Work
  14. Multi-Agent Failure Modes
  15. Organisational Reliability Models
  16. ...and 34 more sections

Key Result

Theorem 3.1

In a CCS with execution-count strategy and budget $n$, the maximum unauthorised operations per capability after revocation initiation is bounded by $n$, independent of agent velocity $v$.

Figures (3)

  • Figure 1: State mapping $\varphi: \Sigma_{\textsc{MESI}{}} \to \Sigma_{\mathrm{auth}}$. Left: hardware MESI state machine with transition triggers (BusRd, BusRdX, Snoop-Inv). Right: authorisation state machine with corresponding triggers (grant, delegate, revoke). Transient states as dashed nodes ($EIA$, $MIC$, $ISG$). Event correspondences labelled on connecting arrows.
  • Figure 2: Heterogeneous Coherence Architecture. Authority Service (central) connected to four agent clusters, each labelled with coherence strategy. Message types: synchronous (eager, solid), periodic (lease, dashed), on-demand (lazy, dotted), acquire/release (exec-count, double). Trust Scorer feeds risk assessments into the strategy selector.
  • Figure 3: Unauthorised operations by strategy (Scenario 2, log scale). CRM high-velocity scenario (100 ops/tick, 10 runs, $\sigma = 0$). The $120\times$ gap between Lease and RCC is annotated. Y-axis logarithmic; damage bound formulae shown below each bar.

Theorems & Definitions (12)

  • Definition 3.1: Capability Coherence System
  • Definition 3.2: Authorisation State Machine
  • Definition 3.3: State Mapping
  • Claim 3.1: Structural Equivalence
  • proof : Proof sketch
  • Definition 3.4: Velocity Vulnerability
  • Definition 3.5: Damage Bound
  • Theorem 3.1: RCC Safety Bound
  • proof : Proof sketch
  • Remark 1: \ref{['thm:rcc']} scope
  • ...and 2 more