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02/09/2026 3:57 pm
TL;DR: AI agent access breaks into three separate controls: identity, authorization, and evidence, according to Highflame. The real governance gap is the assumption that request inspection can substitute for agent identity and session-aware authority, and that gateways alone cannot answer who is calling, what it may do, or what can be proved after the fact.
NHIMG editorial — based on content published by Highflame: AI agent gateways do not solve identity, authority, or evidence
By the numbers:
- When AWS credentials are exposed publicly, attackers attempt access within an average of 17 minutes, and as quickly as 9 minutes in some cases.
Questions worth separating out
Q: What breaks when AI gateways are treated as the source of trust for agents?
A: Trust collapses because gateways can inspect traffic, but they cannot prove who the agent is, who authorized it, or whether the action is permitted at that moment.
Q: Why do agentic systems need session-aware authorization instead of request-by-request checks?
A: Because harmful behaviour often emerges from a sequence of individually valid actions.
Q: How should security teams govern multi-hop agent delegation chains?
A: Security teams should govern multi-hop delegation as a chain of explicit authorisations, not as a series of disconnected API calls.
Practitioner guidance
- Separate identity, policy, and evidence Assign agent identity to a verifiable credential, authorization to the action boundary, and evidence to a signed receipt so no single gateway decision has to do all three jobs.
- Eliminate shared service accounts for agents Replace shared non-human credentials with agent-specific identities that preserve delegation history, so logs can distinguish the agent from the human principal behind it.
- Enforce chain-bound delegation Require each downstream credential to be narrower than the upstream principal, and cap delegation depth so a sub-agent cannot silently expand authority.
What's in the full article
Highflame's full analysis covers the operational detail this post intentionally leaves for the source:
- How Highflame Identity separates agent credentials from shared service accounts in production workflows
- How Highflame Shield evaluates tool calls, file access, shell commands, and MCP connections at the moment they run
- How the signed receipt format records principal, agent, session, action, and outcome for offline verification
- How the delegation chain and revocation model behave across multi-agent task branches
👉 Read Highflame's analysis of AI agent identity, authorization, and evidence →
AI agent gateways: are your controls answering the real questions?
Explore further
02/09/2026 3:58 pm
Identity, authorization, and evidence are separate control problems, not variations of the same one. Agentic AI breaks the old shortcut where traffic inspection stands in for trust. Once an agent can choose its own tools and execution path, the credential, the policy decision, and the receipt must each carry distinct meaning. The implication is that IAM programmes have to design for three control planes, not one.
A few things that frame the scale:
- The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
- Only 44% of developers are reported to follow security best practices for secrets management, which shows how behaviour gaps persist even when teams believe controls are in place.
A question worth separating out:
Q: What evidence should exist after an AI agent makes a sensitive decision?
A: There should be a signed receipt that binds the human principal, the agent, the session, the action, and the outcome. Without that record, auditors and responders cannot reconstruct what happened or prove that approval was actually granted. Evidence is part of the control, not an afterthought.
👉 Read our full editorial: Agent access needs identity, authority, and evidence, not just gateways
