Topic starter
23/06/2026 7:21 pm
TL;DR: Existing gateway and WAF models assume payloads are understandable without semantic context, which autonomous workflows break, and Kong’s partnership with Noma centers on agentic AI runtime protection, combining traffic orchestration with AI-native guardrails to govern agents, MCP tools, and LLM flows in real time, according to Kong.
Editorial analysis by NHI Mgmt Group, based on content published by Kong: “Kong + Noma: Advanced Agentic AI Security and Runtime Protection”.
Key questions
Q: How should security teams govern AI agents that can choose tools at runtime?
A: Security teams should govern runtime agent choice as an access event, not as a simple application action.
Q: Why do existing WAF and API gateway controls fall short for agentic systems?
A: WAFs and API gateways were designed for narrower traffic patterns than modern AI systems produce.
Q: What are the signs that agentic AI governance is too focused on the agent and not the system?
A: Common signs include strong controls around individual identities but weak oversight of orchestration, action chaining, and inter-agent trust.
Practitioner guidance
- Define runtime authorization points for every agent flow Separate A2A, MCP, and LLM paths so each has explicit policy checks, logging, and owner accountability before any autonomous action is allowed to complete.
- Inventory unauthorized model and tool connections Look for shadow AI by mapping where developers or business teams have created unapproved LLM links, MCP access paths, or agent integrations outside central control.
- Move from payload filtering to context-aware decisioning Use controls that can evaluate the intent, tool choice, and downstream effect of an agent action instead of relying only on prompt or traffic inspection.
Bottom line: Agentic AI introduces a governance problem that conventional traffic inspection cannot solve because the risky decision happens at runtime, not at receipt.
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25/06/2026 3:18 am
Runtime security has become the new identity boundary for agentic AI. The article is not really about gateways versus WAFs, but about where enforcement must sit when agents can make tool decisions in flight. Once autonomous workflows can move from model to MCP tool to output without a stable human checkpoint, the control point shifts from static access design to live runtime governance. Practitioners should read this as a structural change in where identity security now has to operate.
A few things that frame the scale:
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What should teams do in the first 24 to 72 hours after discovering a compromised AI agent runtime?
A: Contain the instance, disable external access, rotate all reachable secrets, and review whether any scheduling, configuration, or file-write paths were abused. Then hunt for adjacent instances using the same plugin chain or access pattern. The first response objective is to stop the agent from continuing to act as an attacker-controlled identity.
👉 Read our full editorial: Kong and Noma target runtime security gaps in agentic AI