AI threat modelling
Map attack paths across data, models, agents, tools and infrastructure.
Output / Threat modelProtection engineered for AI
We protect the data, models, agents, tools and infrastructure that turn AI into an operational system.
Six focused capabilities
Focused controls informed by real AI attack paths—not a generic cyber checklist.
Map attack paths across data, models, agents, tools and infrastructure.
Output / Threat modelDesign behavioural boundaries, safe failure and human intervention.
Output / Safety control setTest prompt injection, data leakage, harmful behaviour and excessive agency.
Output / Assurance evidenceConstrain tool access, permissions, secrets and machine identities.
Output / Agent control modelAssess models, datasets, packages, provenance and deployment artefacts.
Output / Supply-chain baselineMonitor drift, abuse, anomalous actions and AI-specific incidents.
Output / Response playbookFDE delivery path
Security travels with the system from design into operation.
Map assets, trust boundaries and intended agency.
Prioritise realistic adversary paths and harms.
Embed controls in architecture and workflow.
Attack the system before and after release.
Monitor, respond and improve continuously.
What you leave with
Ways to engage
Start with the right decision
Let’s map the real attack surface and engineer controls before scale.
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