AI agents should never treat their prompts, memory, or general-purpose logs as a credential store. Give each agent a distinct, least-privilege identity, and let a trusted runtime or service supply only the credentials needed for a specific task. Keep credentials out of model-visible content wherever the architecture allows, and enforce authorization outside model-generated text.
Why an AI agent needs its own identity
An agent that uses a human’s broad account inherits access the task may not require, and actions can become difficult to attribute. Instead, identify each agent or agent workload separately. Bind its entitlements to the user or system operating it and to the task it is performing.
NIST’s 2026 article on agent identity describes agents as first-class entities with their own identifiers, credentials, and entitlements, bound to the identity of the user or system operating them. In enterprise environments, OAuth 2.0, SPIFFE, Rich Authorization Requests, Transaction Tokens, and AuthZen are among the mechanisms discussed for identity and delegated authorization. These are mechanisms to evaluate, not a single settled standard that fits every agent deployment.
Keep credentials outside prompts and memory
Prompts, conversation history, retrieved documents, model memory, environment variables, configuration, and protocol logs can all become unintended places where secrets persist or are exposed. OWASP’s MCP01:2025 guidance warns about credential exposure through these paths and recommends preventing sensitive persistence, using ephemeral contexts for credential operations, and redacting logs and telemetry.
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Prefer a design in which the model selects an allowed action or connector, while a trusted runtime, broker, connector, or consuming service handles authentication. The service can retrieve the required secret directly, so the orchestrator or pipeline need not hold it. The key property is that the raw credential stays outside model-visible content wherever possible; simply storing it in a vault does not ensure this if an agent can retrieve and disclose it without effective controls.
Choose a narrow scope and a short lifetime
Grant only the access needed for the task, and make the scope attributable. Where the system supports it, constrain access by agent, tool, resource, action, and session. Separate read from write permissions when that meaningfully reduces risk. Avoid broad wildcard tool permissions.
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Prefer short-lived, task- or session-scoped credentials over long-lived static tokens. Dynamic secrets can reduce credential reuse where they are feasible. Set expiry and renewal behavior deliberately, and rotate or invalidate credentials after suspected exposure. OWASP’s secrets-management guidance names systems such as AWS Secrets Manager, Azure Key Vault, Google Secret Manager, HashiCorp Vault, Conjur, and Keeper as examples of secrets-management options; using one is not a substitute for limiting what an agent can retrieve or do.
| Design axis | Weaker pattern | Stronger pattern to evaluate |
|---|---|---|
| Identity | Reuse a person’s broad credentials | Distinct agent identity with delegated, attributable rights |
| Credential lifetime | Long-lived static token | Short-lived or dynamic task/session credential |
| Secret boundary | Place a raw secret in a prompt, memory, or broadly exposed tool context | Trusted runtime retrieval or consumer-side access that keeps the raw secret out of model context |
| Permissions and audit | Broad scope with unclear ownership | Narrow resource/action scope, expiry, attribution, rotation, and monitored use |
The stronger pattern reduces exposure opportunities but does not make a system safe by itself. Any component allowed to retrieve and use a credential can still be abused if its authorization checks, tools, or outbound data paths are too broad.
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Keep authorization decisions out of model-generated text
Treat user input, web pages, emails, retrieved documents, tool responses, and messages from other agents as untrusted. Malicious instructions embedded in that content can try to steer an agent into unintended actions. NIST’s January 2025 evaluation article describes this kind of indirect prompt injection as agent hijacking.
A model’s statement that an action is authorized is not authorization. Enforce policy in the execution boundary: validate tool arguments, allow only necessary tools, and check the requested action against the agent’s identity and granted scope. For sensitive or irreversible operations, separate decision-making from execution and require independent validation or approval.
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For a human’s interactive sign-in, two-factor authentication may be part of the provider’s supported flow. Do not make the agent a repository for a person’s password or one-time code. Use an approved delegated-authorization or approval path instead of copying interactive credentials into a prompt or memory.
Isolate context and redact operational data
- Keep agent memory isolated by user and session; review sensitive information before persisting it and apply expiration limits.
- Redact secrets before writing logs or telemetry, including tool and protocol traces.
- Keep live credentials and customer data out of security-test fixtures.
- Review what the runtime, connector, and consuming service can see or emit, not only what the model interface displays.
Test whether the controls hold under abuse
Agent behavior and tool access can change as models, prompts, retrieval setup, and policies change. Maintain repeatable adversarial tests and regression cases that check both expected denials and allowed actions. NIST recommends task-specific, adaptive evaluation that tries multiple attempts; a single successful refusal does not establish that a control reliably holds.
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- Attempt to extract credentials through direct requests, prompt overrides, retrieved content, tool output, and inter-agent messages.
- Try unauthorized tools, privilege escalation, recursive tool use, and data exfiltration.
- Test memory poisoning, cross-user or cross-session leakage, and approval bypass.
- Record the tested model and configuration, tool policies, retrieval setup, abuse cases, and observed allow/deny outcomes.
- Require current test evidence before changing high-risk scopes or approval logic.
OWASP’s agent-security guidance recommends constraining tools and permissions; NIST’s evaluation guidance emphasizes adaptive, task-specific testing. These recommendations are architecture-level: they do not establish that a particular vault, model, connector, framework, or deployment is secure.
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