Agentic gateways and why API gateways fall short for AI agents

At a glance

What this is: An agentic gateway is a proxy for AI agents that enforces identity, context, and tool-level authorization across multi-step workflows.

Why it matters: It matters because IAM, PAM, and NHI programmes must govern how autonomous agents act across sessions, tools, and delegation chains, not just authenticate requests.

👉 Read Pomerium's analysis of agentic gateways, tool-level authorization, and AI agent governance

Context

An agentic gateway is a security control for AI agents that need to call tools, not just APIs. The core issue is that autonomous agents make chained decisions across multiple steps, while existing gateway models assume each request stands alone. That makes AI agent identity and session context part of the authorisation problem, not just the transport problem.

Traditional API gateways and AI gateways both leave a gap at the point where an agent turns model output into action. When the actor can select tools, maintain state, and delegate work, identity governance has to follow the session, the tool, and the chain of authority. That is why agentic access control is emerging as its own category.

For practitioners, the governance question is no longer whether an agent is authenticated, but whether its tool use is constrained, attributable, and reviewable. The article's starting point is typical for organisations now moving agents from demo environments into production workflows.

Key questions

Q: How should security teams govern AI agents that call multiple tools in one workflow?

A: Security teams should govern multi-tool agent workflows with tool-level authorisation, session context, and a complete audit trail. The control should evaluate what tool is being invoked, who initiated the session, what has already happened, and whether the current step still fits the approved task. Endpoint-only access checks are too coarse for that model.

Q: Why do API gateways fall short for autonomous agent governance?

A: API gateways fall short because they treat each request as independent and do not model conversation flow, delegation, or the business meaning of a tool call. Autonomous agents need controls that understand sequence and context, not just authentication and routing. Without that, the gateway cannot tell whether a call is still within scope.

Q: What breaks when an agent can delegate work to another agent?

A: When one agent delegates to another, the accountability chain becomes part of the security problem. If the downstream service cannot see the original authority, it cannot tell whether the action was properly inherited, expanded, or misused. That makes delegation governance necessary for review, audit, and incident investigation.

Q: What is the difference between an AI gateway and an agentic gateway?

A: An AI gateway manages model interactions such as token use, routing, and observability. An agentic gateway controls what the agent can do with the model’s output by enforcing tool-level authorisation, session context, and delegation rules. The two are complementary, but they solve different governance problems.

Technical breakdown

Tool-level authorization for AI agents

An agentic gateway authorises the specific tool invocation, not just the network request. That means policy can distinguish between reading a record, changing a record, and initiating a side effect, even when those actions touch the same backend. It also lets the gateway inspect session state, such as which human initiated the workflow, what steps have already occurred, and whether the current call is still consistent with the original intent. In practice, this is closer to identity-aware policy enforcement than classical API routing.

Practical implication: define policy around tool semantics and session context, not just endpoints and API keys.

Delegation chains and session-aware policy enforcement

Agents often delegate work to other agents or services, which creates a delegation chain that must remain visible to the control plane. A gateway that only checks the immediate caller cannot prove whether authority was inherited legitimately or widened mid-workflow. Session-aware enforcement solves part of that by carrying context forward, so downstream services can evaluate whether a tool call is still within the approved business process. This is the difference between one-off access checks and continuous authorisation across a task.

Practical implication: preserve delegation context end to end so downstream services can validate inherited authority.

Why API gateways and AI gateways do not solve agent governance

API gateways were built for stateless HTTP traffic, while AI gateways are model-centric and optimise calls to LLM endpoints. Neither one inherently understands that an agent may make 5 to 15 tool calls in a single business process, retry based on intermediate results, or invoke a specific tool with business meaning. That means the control problem shifts from routing and cost management to identity, policy, and audit at the point of action. The architecture gap is structural, not incremental.

Practical implication: do not treat existing gateway layers as sufficient for agent governance without tool-aware policy and audit.

Breaches seen in the wild

• Moltbook AI agent keys breach — Moltbook breach exposed 1.5M AI agent keys.
• AI LLM hijack breach — attackers used stolen AWS access keys to hijack Anthropic LLM models on Bedrock.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Agent governance fails when identity control stops at the API boundary. Agentic systems do not just call endpoints, they sequence actions, retain state, and decide what to do next based on prior outcomes. That means the control point must move from request acceptance to tool-level authorisation and session-aware enforcement. Practitioners should treat the gateway as part of the identity plane, not only the network plane.

Session context is now an authorisation primitive for non-human identities. A policy that depends on who started the workflow, what task is being performed, and which step has already executed cannot be evaluated from a token alone. This is especially relevant to OWASP-NHI and Zero Trust models, where least privilege has to be expressed in time, context, and delegation depth. The implication is that static access models are no longer enough for agent workflows.

Delegation chains create an identity accountability problem that traditional IAM does not model well. When one agent invokes another, the downstream service needs to know whether authority was transferred, retained, or expanded. That breaks the simple client-server assumption that underpins many access reviews and audit reports. The practitioner conclusion is that agent-to-agent delegation must be governed as a first-class identity relationship, not a logging artifact.

Tool-level policy is the named control gap this category exposes. Identity does not select or combine tools dynamically mid-session within a stable request model: that assumption was designed for synchronous API traffic, not autonomous agents that decide, retry, and delegate across multiple steps. It fails when the actor is autonomous because tool choice becomes part of runtime behaviour. The implication is that organisations must rethink what “authorised access” means when action paths are created on the fly.

The market is converging on identity-aware infrastructure for agentic workloads. As agent deployments move into production, the category boundary between authentication, authorisation, and audit is collapsing into one control layer. That does not make every gateway an identity product, but it does mean the identity stack now has to observe and govern agent behaviour directly. Practitioners should expect agent governance to become a core requirement of NHI and PAM programmes.

From our research:

• 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to the Ultimate Guide to NHIs.
• From our research: Only 5.7% of organisations have full visibility into their service accounts, which means many identity programmes still cannot see the full non-human estate, according to the Ultimate Guide to NHIs.
• From our research: For broader context on agentic risk and tool misuse, see OWASP NHI Top 10 and its treatment of agent-driven access paths.

What this signals

Tool-level authorization: as agents move from model output to real-world action, the decisive governance question becomes which tool the actor may invoke in which session and under whose authority. That shifts the centre of gravity from API management to identity-aware runtime enforcement, especially where delegation chains are involved.

With only 5.7% of organisations having full visibility into their service accounts, the broader NHI lesson is clear: if teams cannot see machine identities reliably, they will struggle even more to govern agents that act through them. The programme implication is to unify visibility, policy, and audit across non-human and autonomous identities before agent sprawl hardens into shadow AI.

Zero Trust for agents is not a slogan, it is an enforcement pattern that must bind identity, context, and action at the point of tool use. For teams aligning to the NIST AI Risk Management Framework, the practical move is to map agent authorisation and audit into governance controls rather than leaving them in application logic.

For practitioners

• Map tool semantics before building policy Inventory agent-exposed tools, classify each by business effect, and write authorisation rules against the tool name and parameters rather than the HTTP route. This prevents a single endpoint from hiding multiple risk levels.
• Carry session context through delegation chains Require the control plane to preserve who initiated the task, which steps have already run, and what authority was transferred to downstream agents or services. Without that context, downstream checks cannot tell whether the call is still in scope.
• Treat agentic gateways as part of the identity stack Place policy evaluation, short-lived assertions, and audit logging in the path between agents and tools so every invocation is attributable. This is the control layer that makes agent actions reviewable after the fact.
• Separate model optimisation from authorisation control Use AI gateways for LLM cost and performance concerns, but do not assume they govern what an agent can do after the model responds. The policy boundary for tool use belongs in a separate enforcement layer.

Key takeaways

• Agentic gateways exist because autonomous agents create a control problem that API gateways were never built to solve.
• Identity governance for agents must follow tool use, session context, and delegation chains, not just authentication events.
• The practical shift for security teams is from request-centric access control to runtime authorisation and auditable action.

Key terms

• Agentic Gateway: A proxy or enforcement layer that sits between an AI agent and the tools it can use. It authenticates the actor, evaluates context, authorises the specific tool call, and records the action so the session is attributable and reviewable after execution.
• Tool-Level Authorization: A policy model that decides whether an identity can invoke a specific tool in a specific context, rather than asking only whether it can reach an endpoint. For agents, this is the meaningful control boundary because the tool name and parameters often define the risk.
• Delegation Chain: The sequence of authority transfers that links a human, an agent, and downstream services. In agent governance, the chain matters because each hop can widen, preserve, or obscure the original intent, which changes how audit and approval must work.
• Session-Aware Policy: An authorisation rule that evaluates current workflow state, prior actions, and the initiating identity before allowing the next step. This is essential for agents because their risk is shaped by what has already happened in the session, not just by the latest request.

Deepen your knowledge

Agentic gateway design, tool-level authorisation, and session-aware policy enforcement are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If your team is moving from API governance to agent governance, the course is a practical next step.

This post draws on content published by Pomerium: What Is an Agentic Gateway? Definition, Architecture, and Why It's Different from an API Gateway. Read the original.