Secrets Management for AI Agents
How autonomous agents should hold, scope, rotate and use credentials — least privilege per agent, short-lived tokens, secret managers over hardcoding, and keeping secrets out of prompts, logs and model context.
An agent is only as trustworthy as the credentials it carries. Because agents act autonomously — calling APIs, spending money, touching third-party systems — a leaked or over-scoped credential converts a software bug into an unauthorized action at machine speed. This reference covers the credential lifecycle for agentic systems: issuance, scoping, storage, rotation, use, and revocation.
Issuance: one identity per agent
Issue a distinct credential to every agent instance (or every tenant's agent), never a shared key. Distinct identities are what make audit trails meaningful (which agent did this?), what make revocation surgical (revoke the misbehaving one without breaking the fleet), and what let you attach spend limits and rate ceilings per principal. Where the upstream system supports it, prefer OAuth-style delegated authorization with narrowly scoped, short-lived access tokens over static API keys; the token exchange itself becomes an auditable event, and stolen tokens expire on their own.
Storage: managers and injection, not hardcoding
The OWASP Secrets Management Cheat Sheet is the baseline: secrets belong in a purpose-built store (a cloud secret manager, Vault-style system, or platform KV with access controls), injected at runtime — not hardcoded in source, committed to repositories, baked into container images, or passed as plain command-line arguments where they land in process listings. The Twelve-Factor App principle that config lives in the environment remains the right default; agents add the twist that their environment includes whatever the model can see, which changes the rules below.
The agent-specific rule: keep secrets out of model context
A secret that enters a prompt, a retrieved document, a tool result, or a log line the model can read must be treated as disclosed. Models summarize, quote and echo context in unpredictable ways, and context gets logged, cached, and shipped to providers. Practical defenses:
- Resolve credentials server-side, at tool-execution time — the model passes a resource identifier, never the key itself
- Redact known secret formats from anything flowing into model context (prefix detection for common key shapes, bearer tokens, PEM blocks)
- Never paste credentials into system prompts for convenience; that copies them into every session transcript
- Treat provider-side prompt and caching stores as sharing the sensitivity class of the secrets themselves
The OWASP GenAI security project tracks this failure class under sensitive-information-disclosure risks for LLM applications.
Rotation, limits and revocation
Short lifetimes cap the blast radius of any leak: rotate static keys on a schedule and immediately on suspicion. Attach spend ceilings and rate ceilings to each credential at issuance time so a compromised key is also a bounded key. And test revocation end to end — an agent that caches a credential past its expiry turns your rotation program into decoration. For the buyer-facing side of this contract (what a key unlocks, how to verify it), see /resources/access-and-pricing and /resources/api-key-issuance-for-agents; for broader hygiene, /resources/agentic-security-checklist and /resources/prompt-injection-design-patterns.