Patterns
Implementation control library
Find the implementation control behind the gap.
138 implementation controls mapped to architecture, obligations and evidence. Search the problem; open implementation depth only when you need it.
Adversarial Input Defence
Adversarial Input Defence addresses a class of attacks specifically designed to manipulate AI model behaviour through…
AI Data Classification
AI Data Classification defines the automated detection, labelling, and enforcement architecture that ensures data ente…
AI Gateway
The AI Gateway pattern establishes a centralised, enterprise-grade control plane through which all AI traffic flows —…
AI Output Filtering
AI Output Filtering is the post-generation inspection and transformation pipeline that evaluates every LLM response be…
LLM Input Sanitisation
LLM Input Sanitisation is a pre-processing pipeline that transforms raw application inputs into safe, compliant, and p…
Model Isolation
Model Isolation defines the architectural pattern for constraining the execution environment of AI models — whether ho…
Prompt Firewall
The Prompt Firewall is an inline defensive layer that inspects every user input and system-constructed prompt before i…
Secrets Management for AI
Secrets Management for AI addresses one of the most prevalent and consequential security failures in enterprise AI dep…
Secure Tool Invocation
Secure Tool Invocation defines the security architecture for AI agents that can call external tools, APIs, databases,…
Zero-Trust AI Pipeline
The Zero-Trust AI Pipeline applies the "never trust, always verify" security architecture principle to the complete AI…