AI agents are no longer just tools that answer questions. Through MCP and A2A, they are evolving into autonomous actors that interact with internal APIs, SaaS platforms, data sources, and business systems on behalf of users and organizations. As this shift occurs, the critical security question is no longer “Which model should we use?” but rather: “Under whose authority is this agent acting, who authorized the action, and how can we audit it?”
In this session, we will explore why traditional access methods—such as API keys, long-lived tokens, service accounts, and basic user consent—often lead to token sprawl, Shadow AI, policy bypasses, and significant audit gaps. We will then introduce ID-JAG, an authorization pattern that extends enterprise IdP SSO trust directly to API access.
Rather than getting bogged down in specification details, this session uses ID-JAG as a practical lens for designing authorization in the AI Agent/A2A era. We will cover how to accurately represent the subject, actor, client, and resource, and how to translate these trust relationships into scoped, auditable access tokens. Finally, a brief id-jag-the-hard-way demo using Keycloak, Athenz, and MCP will demonstrate this architecture in practice.
Participants will leave with a robust mental model for treating AI agent delegation not as an experimental workaround, but as foundational, enterprise-ready security architecture.
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![[ID-JAG] can be used to extend the SSO relationship of](https://files.speakerdeck.com/presentations/782c3adbba26428bab52052369aa44d2/slide_65.jpg){kind=link}
