Technical Library
AI Security Patterns
Deployment-grade AI requires security that is embedded into the infrastructure layer. These patterns define how to secure AI systems without sacrificing operational control.
Zero-trust access enforced across model endpoints.
Prompt injection detection with policy-driven response.
Data residency gates at ingestion and inference.
Immutable audit logs for every model decision path.
Release governance with staged rollouts and rollback.
Continuous monitoring for anomaly and drift detection.
Security controls must be deterministic. That means enforced access, auditable execution, and clear escalation paths. Security cannot be a reactive layer when AI systems control operational outcomes.
Governance and security are inseparable. Each security pattern must align with a governance rule, and each governance rule must be enforceable by infrastructure.
The best security posture is one that enables deployment. It does not slow operations. It hardens them.