Identity & access
Use authenticated identities, least privilege, scoped service permissions, approval boundaries and periodic access review.
TRUST · SECURITY
Security controls shaped around the real system boundary.
Enterprise AI security starts with understanding identities, data flows, integrations, permissions, secrets, environments and failure paths—not with the model in isolation.
Data & secrets
Keep sensitive information, credentials and secrets out of uncontrolled prompts, logs and client-side code; use approved stores and explicit handling rules.
Integration boundaries
Define which systems can be read, which actions can be executed and where approvals, validation or transaction limits are required.
Monitoring & resilience
Capture useful audit events, errors and operational signals; plan safe failure, rollback, rate limits, incident response and dependency outages.
SECURITY REVIEW
Questions to make explicit before production.
- Which identities can access the system and with what privileges?
- Which data may enter prompts, stores, logs and third-party services?
- Which external systems can the solution read from or act on?
- How are secrets, tokens, credentials and environment configuration protected?
- What is logged, monitored and reviewed after deployment?
- What happens if a dependency, model, integration or approval step fails?
SCOPE
Security requirements depend on the actual deployment.
This page describes engineering principles, not a claim of certification, compliance status or universal control coverage. Engagement-specific security requirements should be validated against the customer's architecture, policies and applicable obligations.
BRING SECURITY INTO DISCOVERY