AI Security Assessments & Advisory
Assess AI-enabled systems across model, application, data, supply-chain, and deployment risks.
Securing non-deterministic systems requires an intimate understanding of both AI/ML and cyber system fundamentals. We perform system threat modelling, technical assessments, and security architecture advisory for organisations deploying AI at scale.
When To Engage Us
- Teams moving AI prototypes into production
- Organisations integrating third-party models or AI services
- Programs requiring defensible AI security decisions
What We Cover
- Prompt injection and unsafe tool use
- Model, data, and supply-chain integrity
- Identity, authorisation, and information boundaries
- Threat modelling and ACSC guidance alignment
Clear Outputs
Typical Engagement Outputs
Final outputs are agreed during scoping so they support the decisions your team needs to make.
- System-specific threat model
- Technical assessment findings
- Architecture and control recommendations
- Prioritised security uplift plan
Define The Right Boundary
How We Scope It
A useful engagement begins with a clear assurance question. For this service, scoping normally considers:
- The AI use case, users, decisions, impacts, and current lifecycle stage
- Model and service providers, deployment architecture, data sources, and supply-chain dependencies
- Tools, memory, external integrations, identities, permissions, and autonomous actions
- Sensitive information, threat actors, oversight points, monitoring, rollback, and recovery expectations
From Question To Uplift
How We Work
The approach is adapted to your environment, while keeping communication, evidence handling, and decision points clear.
Map The System
Document models, data, prompts, tools, identities, integrations, trust boundaries, and human decision points.
Threat Model
Examine conventional and AI-specific threats, including injection, unsafe agency, data compromise, and supply-chain risk.
Assess Controls
Test or review the safeguards around access, context, outputs, tools, monitoring, data, and deployment infrastructure.
Prioritise Safe Adoption
Translate findings into practical design, governance, testing, deployment, and operational recommendations.
Common Questions
Before You Engage
Is an AI security assessment just prompt-injection testing?
No. Prompt injection is one concern. A useful assessment also considers identity, permissions, tool use, data provenance, supply chain, deployment infrastructure, monitoring, oversight, and recovery.
Can you assess third-party AI platforms and models?
Yes. The scope focuses on how the service is selected, configured, integrated, supplied with data, granted access, monitored, and governed within your environment.
When should an AI system be assessed?
Threat modelling should begin during design. Technical and architecture assurance is most useful before production, after material model or integration changes, and as autonomy or privileges increase.
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Start With A Conversation
Need help defining the right scope?
Tell us what you are trying to protect or validate. We will help shape an engagement around the outcome you need.
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