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The Identity Crisis of AI – Why Traditional Security Fails Agentic Systems

Posted on 29/11/202529/11/2025 by Farayi Dzichauya

The rise of autonomous AI agents is transforming business and also exposing a critical flaw in our digital security ecosystem. Our identity and access management systems are reaching their limitations. Protocols like OAuth and SAML were built for human users and static applications. They rely on one-time authentication and fixed permissions, a model that simply cannot keep up with the dynamic, ephemeral, and evolving nature of AI-driven automation.

Traditional systems grant broad, persistent access, which creates security risk when used with agentic systems. If an AI agent is compromised, the damage would be extensive. We need a radical shift from static trust to continuous verification.

The solution lies in Ephemeral Authentication. This approach generates short-lived, context-aware identities, granting the AI agent only the minimum necessary permissions for its current task—the very definition of the Principle of Least Privilege. These credentials expire automatically, drastically reducing the attack surface and providing clear, granular audit trails for every action.

This is part of a larger movement toward Dynamic Identity Management. It moves beyond static Role-Based Access Control (RBAC) to embrace Fine-Grained Access Controls like Attribute-Based Access Control (ABAC) and Just-In-Time (JIT) access. This framework enforces a Zero Trust approach for Agentic AI, where access is continuously evaluated based on real-time context, behavior, and risk.

As AI agents become the backbone of modern operations, securing them with dynamic, adaptive identity is imperative for realising potential without compromising security. It’s time to give AI agents the full security they deserve.

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