Can your AI application be talked into acting outside its boundaries?
Adding AI changes how an application behaves. Instructions can arrive through user prompts or through content the model retrieves, while connected tools may give the model access to information or actions far beyond the conversation itself. Traditional application testing does not always reveal these paths because it assumes the software behaves only as it was explicitly programmed to behave.
We test the AI component together with the application, data sources, permissions and integrations around it. This includes direct and indirect prompt injection, unintended disclosure, manipulation of model behaviour and what connected tools allow once the model has been influenced.
Findings are demonstrated in context, then traced back to the control that can contain them, whether that sits in the prompt, the data flow, the permissions or the design of the feature itself.
- Demonstrated AI-specific attack paths and test results
- A review of prompts, retrieval, permissions and integrations
- Clear evidence of what data or actions could become exposed
- Priorities based on the consequence of each demonstrated behaviour
- Recommendations placed at the control point where they can be effective
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