SERVICE 11

AI Security

Assess AI applications, LLM workflows and governance controls for prompt injection, data leakage, model risk and emerging threats.

AI and LLM security illustration
WHAT WE COVER

Specialised workstreams inside this service

Build the right scope by selecting the areas most relevant to your environment and risk.

AI Application Security Assessment

Generative AI and LLM Security Testing

AI Model Vulnerability Assessment

Prompt Injection and Data Leakage Testing

AI Governance and Compliance

Continuous AI Threat Monitoring

WHAT YOU GET

Evidence that helps your team make decisions.

Every engagement is designed to move from technical observations to prioritised action.

AI attack-surface assessment
Prompt injection findings
Data leakage risks
Model and integration weaknesses
AI governance gap report
AI threat monitoring plan
ENGAGEMENT METHOD

A clear, repeatable security workflow

The exact scope adapts to your environment, but our engagements follow a practical sequence from context to validation.

STEP 01AI architecture mapping
STEP 02Trust-boundary review
STEP 03Prompt attack testing
STEP 04Data-flow testing
STEP 05Control assessment
STEP 06Governance roadmap
BUILT FOR ACTION

Security findings your technical team can use

We focus on evidence, exploitability, business impact and remediation clarity. The objective is not simply to produce findings - it is to help you reduce risk.

Risk-focused prioritisation

High-impact weaknesses are separated from low-value noise.

Clear security reporting

Reports include evidence, context and practical next steps.

Remediation validation

Where applicable, retesting verifies fixes and reduces uncertainty.

AI Security assessment workflow
Example engagement signals
AI Application Security AssessmentIn scopeReview
Generative AI and LLM Security TestingIn scopeReview
AI Model Vulnerability AssessmentIn scopeReview
FAQ

Questions about this service

Yes. We assess direct and indirect prompt injection, unsafe tool use, sensitive data exposure and relevant application-layer weaknesses.
Yes. We can assess governance, roles, risk ownership, model inventory, data handling and control readiness.
Continuous monitoring can be designed around AI-related security events, misuse signals and exposed attack surface.