Runtime Control

AI Agent Security

AI agents need constrained tools, least-privilege credentials, approval gates, egress controls, budgets, and replayable run logs before they touch production workflows.

Limit what agents can do

Agents should receive only the tools, permissions, context, and network access required for the current workflow. Broad access creates unnecessary blast radius.

Allowlisted tool registry
Scoped credentials
Rate and spend budgets
Restricted network egress

Add gates before risky actions

Sensitive workflows should use deterministic policy checks, approval queues, and escalation rules before execution, especially when money, data, or external systems are involved.

Policy checks
Human-in-the-loop approvals
Execution previews
Rollback and incident paths

Make every run inspectable

Forensic logs should capture prompts, tool calls, approvals, source evidence, outputs, and errors so teams can debug and audit the system.

Trace logs
Artifact retention
Prompt and model versioning
Exception review

Related reading

Continue through the connected solution pages, case studies, and planning references.

Turn this into an implementation path.

Anubis Labs can map the workflow, data boundary, controls, and evaluation plan for your environment.

Request an architecture review