Prompt and model-interface security
Test direct and indirect prompt injection, system-prompt extraction, memory behaviour and the controls surrounding model inputs and outputs.
AI / 05New
AI governance and security that puts AI risk inside clear boundaries
Assess AI and LLM applications across prompt injection, RAG isolation, sensitive-data leakage, autonomous-agent permissions and governance controls—without treating one test as proof of complete compliance.
Plain answer
What is AI governance and security?
AI governance and security is the discipline of putting verifiable boundaries around AI systems: knowing what a model can access, what an agent is permitted to do, where sensitive data could leak and who owns each risk as the system evolves. Assessment covers direct and indirect prompt injection, system-prompt extraction, RAG retrieval permissions and tenant isolation, sensitive-data leakage, and the downstream APIs and tools that autonomous agents can call—mapped against frameworks including OWASP LLM/GenAI, MITRE ATLAS, NIST AI RMF and the EU AI Act. One test is never treated as proof of complete compliance. The output is an AI-system threat model, verified abuse cases and a control plan with named owners and a regression cadence, so governance keeps pace as models, data sources and integrations change.
Practical outcome
An AI-system threat model, verified abuse cases and an accountable control plan for safer deployment and continuous oversight.
- 01AI and LLM threat modelling
- 02Direct and indirect prompt-injection testing
- 03RAG authorisation and tenant isolation
- 04System prompt and sensitive-data leakage review
- 05Autonomous-agent permission testing
- 06Governance and lifecycle control assessment
Service detail
What is included
The scope is adapted to your environment, while the underlying evidence and reporting standards stay consistent.
RAG and data boundaries
Review retrieval permissions, vector-store isolation and sensitive-data handling across documents, tenants, users and connected knowledge sources.
Agent permissions
Validate what autonomous or semi-autonomous agents can call, change or disclose through downstream APIs, tools and business workflows.
Governance through the lifecycle
Connect verified technical risk to ownership, policy, monitoring, change control and repeatable regression testing as systems and models evolve.
- OWASP LLM/GenAI
- MITRE ATLAS
- NIST AI RMF
- EU AI Act
Team capability
Certifications and platforms represented across our team
- CEH
- OSCP
- CISSP
- IBM QRadar
- Splunk
- CrowdStrike
- Fortinet
- Microsoft
How it works
A bounded path from scope to action
A mapped path from system understanding to owned, repeatable controls.
01 Map the AI system
Confirm models, data flows, roles, integrations, trust boundaries, permitted actions and emergency stop conditions.
02 Validate abuse cases
Test prompt, retrieval, data-leakage and agent-permission scenarios against the agreed system and safety boundaries.
03 Build the control plan
Separate application defects, model limitations and governance gaps, then assign owners and a regression cadence.
Service FAQ
Common questions about AI governance and security.
What does an AI security assessment test?+
Direct and indirect prompt injection, system-prompt extraction, RAG retrieval permissions and tenant isolation, sensitive-data leakage, and what autonomous agents can call or change through downstream APIs and tools.
Does one assessment make us EU AI Act compliant?+
No—and we will not claim it does. A single test is evidence, not proof of complete compliance. The output connects verified technical risk to ownership, policy and a regression cadence that keeps pace as the system evolves.
Which frameworks do you map against?+
OWASP LLM/GenAI, MITRE ATLAS, NIST AI RMF and the EU AI Act—applied to your actual system and threat model rather than as a checkbox exercise.
When should we assess an AI system?+
Before production deployment, after material changes to models, data sources or agent permissions, and on a repeatable regression cadence in between—AI risk moves whenever the system moves.
Baltic capability
Need coordinated delivery in Latvia?
For a Latvian scope or a wider Baltic engagement, review the corresponding BR2SEC capability. The responsible entity and delivery boundary are confirmed before work begins.
Start with the decision
Ready to discuss AI governance and security?
Tell us what is changing, what needs assurance, or where visibility is incomplete. We will help define a proportionate first scope.