What is runtime authorization for AI agents?

Runtime authorization is evaluation on the hot path: a structured request meets policy, context, and risk rules before an executor accepts work. For agents, that means the moment a tool call, workflow hop, or API write would leave the trusted boundary, not after logs are shipped to a SIEM.

Service accounts, OAuth scopes, and human SSO answer "who is this principal?" They do not fully answer "may this specific action run now on this surface with this payload and escalation state?" Agents compose tools across sessions; identity alone cannot bind each commit to policy without a dedicated authorization step.

Prompt filters and classifiers reduce unsafe text; observability records what already happened. Neither retracts a wire transfer, a production config change, or a data export that cleared the gateway. If the last hop before side effects has no mandatory permit check, the system remains fail-open under pressure.

Production integrations pass a bounded frame, for example: agent identity and session, tool or connector, action verb and parameters, data classification or fields required by policy, destination surface or tenant, and policy context such as maintenance mode, geography, or break-glass. The evaluator returns a single outcome suitable for binding to a receipt.

TG-01-style evaluation is finite-state: PERMIT, DENY, or SILENCE (no authorization issued). Same inputs and policy version should yield the same decision so teams can replay incidents and prove what was allowed. Semantics: Decision model and deterministic authorization.

Receipts record decisions; runtimes record enforcement (for example executed vs blocked). The one-line contract: decisions deny; systems block. Keeping the axes separate prevents dashboards from silently collapsing policy truth. See Decision vs enforcement.

Signed receipts bind request context, policy version, and outcome so verifiers do not have to trust a single log stream or UI. They are how you answer supervisory questions after the fact without asking the vendor to vouch in real time. Structure: Protocol receipts; practice: Verify.

TrigGuard places evaluation in front of execution surfaces: Gate for interception, Arbiter for policy lifecycle, Verify for receipt checks, SDK for embedding the contract. The TG-01 reference specification is the shared artifact between security, platform, and compliance teams.

Review the system model, read the spec, exercise verification, align on pricing, then talk to engineering.

• Architecture (same content: /protocol/architecture)
• Reference specification
• Verify receipts
• Pricing

Request a demo Contact engineering

AI execution governance · AI agent safety · Pre-execution authorization · Execution authorization