Table of Contents
The Gateway Is Not the Identity: Attested Trust for Agentic AI
TL;DR: Secure AI agent access starts with verifiable identity. This paper explains how workload attestation, delegated authority, deterministic policy, and short-lived credentials establish trust for agent actions, while gateways and other enforcement points apply those decisions across enterprise systems.
Ken Huang
AI Security Researcher
Published Oct 2026
Updated Oct 2026
50:1
Non-human to human identities
18
Agent threat classes mapped
0
Long-lived secrets required
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Table of Contents
The Gateway Is Not the Identity: Attested Trust for Agentic AI
AI agents introduce an unusual access problem. Their actions are selected dynamically at runtime, yet the systems they reach still need deterministic answers about identity, authority, and permission.
In this white paper, AI security expert Ken Huang examines the trust architecture required to make those decisions defensible. He looks at how enterprises can verify the agent itself, preserve the identity of the human or process behind it, evaluate access at the time of action, and issue credentials that carry only the authority required.
You’ll Learn
- How workload attestation establishes that an AI agent is the approved software running in the expected environment.
- Why secure agent access may need to preserve both the agent identity and the human, process, or upstream agent behind it.
- How delegated authority, policy context, and short-lived credentials reduce broad standing access.
- Where AI gateways, MCP infrastructure, identity providers, credential services, and target applications fit within the architecture.
- How Aembit provides identity, policy, and credentials while allowing enforcement to occur across multiple existing control points.
FAQs
You have questions? We have answers.
What is attested identity for an AI agent?
Attested identity uses verifiable evidence from the agent’s runtime environment to establish that the software requesting access is the approved workload. That evidence can come from sources such as cloud metadata, Kubernetes service-account tokens, OIDC, Kerberos, VMware, or another trusted attestor.
What is blended identity for AI agents?
Blended identity combines an agent’s attested workload identity with the identity of the human directing it. This allows access policy to consider both the software actor and the person behind the request rather than attributing every action to only one of them.
Why are short-lived credentials important for AI agents?
AI agents can select different tools and actions at runtime, so broad static credentials can create unnecessary standing privilege. Short-lived, audience-bound credentials limit access to a particular target and period and can be tied back to the policy decision that authorized them.
What role does an AI gateway play in agent security?
An AI gateway can route, inspect, rate-limit, log, and block agent traffic. It serves as an important enforcement point, but the underlying identity, attestation, delegated authority, and policy evidence must be established elsewhere before the gateway can make a defensible access decision
How do Aembit and existing AI gateways work together?
Aembit supplies attested identity, policy context, and time-limited credentials. Enforcement can occur through Aembit’s MCP Identity Gateway or through existing infrastructure such as Kong, Apigee, Agentgateway, service meshes, and proxies, allowing organizations to keep a consistent trust layer across multiple enforcement points.
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