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MCP security and authority

AI Agent Policy Caches and Revocation Delays

Measure AI agent policy cache revocation across gateways and queues. Separate stale rules from stale decisions and define failure behavior.

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An AI agent policy cache can reduce decision latency, but it also creates a period in which a previously allowed action may outlive changed authority. Design the cache around what can become stale: identity status, grant scope, policy version, resource state and the exact proposed action. A cached allow decision is not a permanent permission.

This article is for engineers operating gateways or action-enforcement services. It distinguishes cached policy material from cached decisions and explains how to measure revocation behavior. The examples use synthetic internal document actions. They do not prescribe a universal safe cache lifetime, and they are not a claim that a particular identity provider or gateway offers immediate revocation.

Distinguish the things being cached

A policy bundle contains rules. A token-introspection result reports token status under its defined semantics. An authorisation decision combines policy with request and context. An object cache holds business data. Each can expire or change for different reasons. Giving all four the same time-to-live hides the assumptions that determine whether a later action remains valid.

OAuth’s token introspection specification discusses the tradeoff between caching and the freshness of token state. The OAuth token revocation specification also recognises propagation considerations. Neither specification establishes a universal end-to-end revocation deadline for your application, its queues and its receiving systems. That deadline needs deployment-specific measurement.

Define freshness for the action being protected

Start with the consequence of stale permission. Reading a public document and modifying a restricted case have different risks. Define which facts must be current for each action class and what happens when they cannot be established. A shorter cache lifetime may reduce exposure, but it does not fix a missing tenant field or an unprotected direct execution path.

Cached itemKey must distinguishInvalidation or expiry triggerFailure question
Policy bundleTenant, policy identifier and versionNew approved policy or maximum permitted ageCan this action use the last known version?
Identity statusIssuer, subject and relevant lifecycle contextSuspension, revocation or bounded expiryMust execution stop if status cannot be refreshed?
Decision resultExact action and all decision-relevant contextChanged request, resource, authority or expiryWas the result calculated for this same operation?
Resource snapshotTenant, object and versionState change or defined freshness boundCould the object have changed before execution?
Queue authorityOperation, grant and execution constraintsCancellation, permission change or deadlineWhat must be rechecked when the job actually runs?

The table is an architectural checklist, not a complete cache-key algorithm. Some decisions depend on additional facts such as approver role, destination classification or a source-system lock. If a dependency cannot be represented and invalidated reliably, reconsider whether caching the final allow decision is appropriate at all.

Keep expiry and invalidation independent

Expiry provides a bounded lifetime when an invalidation event is missed. Event-driven invalidation can shorten the stale period, but its delivery and processing can fail. Design for both. Record when the authority change was committed, when each enforcement point observed it and when a subsequent request was denied.

Do not calculate evidence of freshness from the client-provided timestamp alone. Use trusted service observations and define clock assumptions. For local cache age, monotonic elapsed time can avoid problems caused by wall-clock adjustment. Distributed records still need explicit clock-skew handling when comparing observations across services.

Avoid inventing a simple sum that allegedly bounds every revocation delay. Multiple caches, disconnected workers and queued work may interact in ways that exceed a single token lifetime. Draw the actual dependency path, then test the slowest relevant route. Include the receiving system if it can accept requests without the gateway.

Run a revocation timing exercise

Create a synthetic identity with permission to prepare a protected draft. Warm the relevant caches through a successful request. Record a server-side revocation event, then issue new requests through each gateway instance and worker path at a controlled rate. Keep the attempt identifiers and observed results. Do not use real consequential transactions for this exercise.

Repeat while one instance is disconnected from the invalidation channel. Then repeat with the authority service unavailable and with a queued job created before revocation. The expected behavior comes from your documented action policy. For an action requiring current authority, inability to refresh must not silently turn into permission to continue.

Report the last accepted request, first consistently denied request and any unresolved observation gap for each path. Distinguish requests already dispatched before revocation from requests first dispatched afterward. Revocation generally cannot reverse an external effect that has already occurred; reconciliation or an authorised compensating action addresses that separate problem.

Diagnose a stale allow result

Check whether the request reused the same decision key after relevant context changed. Compare tenant, principal, grant, tool, arguments, resource version and policy version. Then inspect invalidation delivery, cache age and downstream enforcement. A low average delay does not excuse one worker that keeps accepting indefinitely.

Contain the affected action class while investigating. Preserve the relevant decision and dispatch records without logging access tokens or complete sensitive payloads. If an emergency control bypasses the normal cache, test that path too. A kill switch whose own decision is cached under the old permission can fail exactly when it is needed.

Make the operational promise measurable

Document the supported action classes, maximum permitted stale state, outage behavior and measurement method. State whether the bound is a tested observation, a service objective or a guaranteed contract. Do not use “instant” when the system relies on propagation that has not been measured under failure.

Re-run the worksheet after changing cache placement, queue semantics, identity providers or connector routes. Include a positive request after authorised restoration so the test proves recovery as well as denial. Restoration should establish a new valid state, not simply resurrect an expired cached decision.

The useful result is an evidence-backed statement about where authority changes take effect and what happens when freshness is unknown. That statement gives operators a basis for containment and release decisions. A time-to-live value in a configuration file, by itself, does not provide the same assurance.

Use the worksheet and related implementation guides

Use the parent guide for the wider architecture, then apply this article to one bounded implementation. The adjacent articles cover related decisions without replacing this worksheet.

Download the editable worksheet. Next step.

Engineering draft, 18 October 2026. Primary sources checked on this date; specialist review remains pending. The worksheets describe proposed tests, not measured customer results. OATI remains a developer preview. Local implementation evidence does not establish independent assurance, customer acceptance or production readiness for a particular deployment.