pvakati-tech.ai
// ai_security_architecture

AI Agent Authentication with JWT, OAuth & RBAC

AI agents should never get broad, permanent credentials. A production-safe design uses OAuth for people, scoped JWTs for agents, policy checks for every write, and audit logs across every internal tool call.

OAuth 2.0scoped JWTRBAC + policyaudit
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// reference_flow

Identity → token → policy → tools

This fits customer agents, internal copilots, and service-to-service AI workers that need controlled access to auth, search, cart, notification, or support APIs.

01

User or service identity

A person signs in with OAuth or a system actor authenticates with a service account.

02

Auth API

The auth layer verifies identity, resolves tenant, and decides which scopes the agent can request.

03

Scoped JWT

A short-lived JWT is issued with subject, tenant, allowed tools, and write permissions.

04 · CONTROL

Policy & RBAC

Each action is checked against roles, approval thresholds, and tenant-specific policy rules.

05

Protected tools & APIs

Internal services validate the token, enforce scopes, and log every tool call for auditability.

// session_sequence

A delegated session, step by step

The same session over time — consent, a scoped token, policy validation, an approval checkpoint for risky actions, and audit streamed the whole way. Amber nodes are the deterministic control points.

01

Consent granted

User signs in through OAuth and the session boundary is explicitly delegated to the agent.

02

Scoped session

The agent gets a short-lived token with allowed tools, tenant context, and limited write scopes.

03 · CONTROL

Policy validated

Each request is checked against RBAC, tenant policy, and business rules before a tool call executes.

04 · CONTROL

Approval checkpoint

High-risk actions such as checkout, refund, or substitution require elevated authorization or human review.

05

Audit streamed

Tool calls and outcomes are recorded into observability and audit pipelines in real time.

// realtime_examples

Three real-time flows

Live shopping copilot

A signed-in shopper asks an agent to compare products, build a cart, and hold the final checkout step for approval.

OAuth login → scoped JWT → catalog & cart APIs → approval gate → checkout service

Real-time support assistant

A support copilot reads live order data and drafts refund or replacement actions without getting blanket write access.

Agent session → policy check → OMS & CRM tools → human review → signed action token

Fraud response worker

A background agent receives a suspicious event and can freeze sessions or trigger MFA, but only within machine scopes.

Risk event → service account → short-lived JWT → auth controls → audit log

Core design principles

Use short-lived JWTs for agents instead of long-lived shared API keys.

Separate user identity from agent identity so delegated actions stay traceable.

Issue tool-specific scopes such as read:catalog, write:cart, and send:notification.

Require explicit approval for payments, refunds, substitutions, and other irreversible writes.

Implementation checklist

OAuth for human sign-in and consent

JWT signing and verification at every protected boundary

RBAC plus tenant-aware policy checks before tool execution

Audit logs with subject, action, tool, result, and request ID

Refresh and revocation strategy for compromised or expired agent sessions

// deployment_patterns

Common deployment patterns

The auth model changes depending on whether the agent acts for a user, runs as a backend worker, or coordinates specialists.

Delegated user agent

A customer-facing agent acts on behalf of a signed-in user and inherits only the minimum allowed scopes for the session.

Internal autonomous worker

A background agent uses a service account, receives narrow machine scopes, and cannot impersonate end users.

Multi-agent orchestration

A supervisor agent exchanges internal tokens with specialist agents so search, support, and fulfillment flows remain segmented.

// standards

Standards & references