What we solve
AI systems introduce risks such as context leakage, prompt injection, incorrect agent actions, and changes in quality that are hard to see. Assessment must cover the model, data, tools, permissions, and human oversight together.
What you get
The work produces a threat model, a test suite, a list of validated issues, and recommended controls. The team receives rules for access, logging, change releases, and incident response.
What is included
- A map of AI components, data, and permissions
- A threat model and misuse scenarios
- Selection of a red-teaming team
- Testing of safeguards and system behavior
- Governance processes, a report, and remediation plan
How we work
- Identify critical actions and data.
- Agree a safe test environment and methods.
- Run tests and reproduce findings.
- Build controls into development and operations.
Optional additions
- A suite of AI regression tests
- Quality and misuse monitoring
- Training for the product team
- A retest after changes
Important considerations
Testing cannot eliminate all risk. System boundaries, permitted data, AI authority, and mandatory human approval of critical actions are defined before launch.