Securing Identity in Agentic Systems: A Modern Strategy for AI-Driven Architectures

As organizations increasingly adopt Generative AI, Retrieval-Augmented Generation (RAG), and agentic system architectures, a new challenge has emerged: how to securely convey Identity through a complex, intelligent flow of decisions and actions.

In this new era of distributed agents and automated intelligence, securing Identity is essential.

Let's start with a relatable example.

Imagine you're calling a customer support line. You speak to the first agent and verify your Identity. Then, you're transferred to a second agent who asks you to confirm again. Frustrating, right? Now imagine that call is routed across multiple teams or even different companies, each trying to help with a different part of your issue. Still, none of them share your verified Identity. Every new step increases the risk of something going wrong, whether it's a delay, a security issue, or someone pretending to be you.

This is similar to what happens in agentic AI systems. Instead of human agents, we have software agents. And instead of phone calls, we have data and actions passing through dynamic networks of AI components. Ensuring each step "knows who you are" in a trusted manner is a significant concern.

Understanding Identity Propagation: From Simple Systems to Intelligent Agents

Let's look at how Identity typically flows in traditional digital systems:

1. No Delegation

In the most straightforward setup, a user accesses an app. The app then communicates with another service, such as a database. That service doesn't know who the user is; it only knows that the app is requesting it.

2. Trusted Assertion

Here, the user logs in through an Identity Provider. The app then tells the service, "This user is John," and the service trusts that claim because it came from a reliable source.

3. Simple Delegation

Instead of passing along a name, a digital token is issued when the user logs in. That token travels through the system and is checked at each step. It's like a digital passport.

These methods work well for apps and services that don't undergo frequent changes. But once you add AI agents that dynamically work together, some internal and some external, the rules start to break down.

The Agentic Challenge: Identity in Dynamic, AI-Driven Systems

In agentic systems, a user request doesn't follow a straight line. Instead, it moves through a network of intelligent agents, each making decisions, calling other agents, or even spawning new ones in real-time.

This creates tough questions:

• How do we securely carry a user's Identity through these unpredictable flows?

• How do we make sure each agent is authorized to act?

• What if the flow crosses between different departments, clouds, or even organizations?

• How can we prevent attackers from infiltrating fake identities?

Risks and Threats in Agentic Identity Flows

Let's say someone inserts a fake agent into this system like a bad actor sneaking into a support call pretending to be a supervisor. If the system blindly trusts every step, that rogue agent might gain access to sensitive data or trigger actions it shouldn't.

This is the heart of the risk: Identity spoofing and privilege misuse due to weak or implicit trust models.

Trusted Identity Delegation for Agentic Systems

To manage these risks, we need stronger models that are purpose-built for distributed, intelligent systems:

On-Behalf-Of Delegation

Each agent works on behalf of a user but has its own Identity and permissions. This lets the system track actions clearly and restrict what each agent is allowed to do.

Transitive Trust

Here, trust is granted to the entire system, rather than to individual agents. This approach only works if the system has strong governance, transparency, and internal safeguards.

Multi-Identity Provider Support

When workflows cross between business units or companies, agents may need to use multiple identity providers. Systems must adhere to consistent standards to maintain trust across boundaries.

Five Key Strategies to Secure Agentic Identity Flows

Here's how organizations can take action today:

1. Use Industry Standards Like OAuth 2.0 and OpenID Connect

These frameworks offer a secure and widely accepted method for authenticating users and delegating authority. Think of them as digital rules of the road that everyone understands.

2. Token Exchange at Every Step

Each agent should not simply reuse the previous token. Instead, it should validate the token and request a new one from a trusted source. This helps ensure that the Identity is still valid and hasn't been tampered with.

3. Add Context with Scope and Audience

Tokens should include information about:

• Scope: What the user is allowed to do

• Audience: Who the token is meant for

  
  

  This limits risk by ensuring tokens only work where and how they're supposed to.

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4. Use API Gateways to Manage Identity

API gateways can act like border agents verifying identities, exchanging tokens, and applying rules, so that only the authorized agents gain access to the relevant data.

5. Monitor Identity Flows Continuously

It's not enough to secure the system at setup. Utilize observability tools to track Identity's movement, detect unusual patterns, and ensure everything remains compliant and secure.

Final Thoughts: Identity Is the Backbone of Trust

In the world of AI agents and dynamic automation, Identity is about enabling trust, accountability, and control at every step of the journey.

Whether you're a developer, security architect, or business leader, securing identity propagation in agentic systems should be a top priority. By adopting strong delegation patterns and enforcing robust security standards, you can effectively protect your users, data, and mission as you scale into the future.