Secure AI agents at the point where reasoning becomes action
Secure enterprise AI agents with least privilege, credential isolation, input boundaries, approval gates, trace evidence, and tested failure behavior.
AI agent security starts with least privilege. Isolate credentials, separate reads from writes, treat retrieved content as untrusted input, validate tool arguments, require approval for consequential actions, cap repetition and spend, and retain traces for investigation.
Protect credentials and tools
Do not place reusable secrets in prompts or model-visible context. Bind credentials to server-side connectors, narrow their scopes, and expose purpose-built operations instead of raw shell, database, or HTTP access whenever possible.
Treat every input as potentially hostile
Prompt injection can arrive through email, web pages, documents, tool results, and the screen of a controlled phone. Retrieved text is evidence, not instruction. Keep system policy outside retrieved content and validate the arguments of every consequential tool call.
- Separate instructions from retrieved data
- Allowlist destinations and action types
- Set iteration, time, cost, and write limits
- Block the agent from changing its own permissions
- Require fresh approval when scope changes
Design for containment and investigation
Use per-workflow identities where possible, record tool calls and approvals, and provide a fast global disable path. Test partial failures, duplicate delivery, stale state, and replay attacks. Security depends on what happens when the model or a dependency behaves unexpectedly, not only on the happy path.
Frequently asked questions
Can prompt injection be solved with a stronger prompt?
No. Prompts help, but effective protection also requires permission boundaries, untrusted-input handling, tool validation, approval gates, and containment.
Should an agent receive a user's full permissions?
Usually not. Give the workflow the smallest permissions needed for its specific task and lifetime.
Where should AI agent credentials live?
Credentials should be stored and used outside model-visible text, ideally in a managed secret store or server-side connector with narrow scope and auditability.
