Threat-model the AI system
Document model providers, prompts, retrieval data, tools, agents, identities, outputs and decision authority.
Solution · AI security & governanceMODEL TEST CONTROL GOVERN
Move fast without making AI risk invisible.
Secure AI systems by mapping data, model, tool, identity and human decision boundaries—then testing the abuse cases that matter.
Validate realistic abuse cases
Assess prompt injection, indirect injection, sensitive-data handling, excessive agency and unsafe tool use.
Design layered guardrails
Use least privilege, validation, isolation, monitoring, approval gates and fail-safe behaviour.
Create reviewable evidence
Record intended use, owners, risk decisions, evaluation results, changes and incident paths.
Standards and references
- OWASP Top 10 for LLM Applications and Agentic AI guidance.
- NIST AI Risk Management Framework.
- Provider-specific security and data-handling documentation.
- Applicable privacy, sector and contractual requirements.
Turn the next security decision into a clear scope.
Tell us what you need to protect, prove or improve. We will define the evidence, boundaries and next action before work begins.