Case study · Technology
Security testing of a customer-facing AI assistant
A company launching a generative-AI assistant needed assurance it could not be manipulated into leaking data or performing unsafe actions.
The challenge
What was at stake
A company launching a generative-AI assistant needed assurance it could not be manipulated into leaking data or performing unsafe actions.
The organisation needed a partner that could understand its environment quickly, prioritise the risks that mattered most and deliver measurable improvement without disrupting day-to-day operations.
Our approach
What we did
- AI threat model (OWASP LLM Top 10)
- Prompt-injection and jailbreak testing
- Data-leakage and tool-use abuse testing
- Guardrail and monitoring recommendations
Outcomes
The results
14
AI-specific issues found
100%
high-risk issues fixed pre-launch
1
AI governance policy adopted
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