AI Systems Security Assessments

The goal of technical security testing of AI systems is to identify vulnerabilities such as prompt injection, bypass attempts, data leakage risks, the generation of harmful or unwanted responses, and other technical deficiencies affecting the security of the application and the underlying AI solution. The testing provides a practical picture of the application’s resilience in realistic attack and misuse scenarios.
Technical testing of an AI system answers the question: is the entire AI-powered application and its implementation secure?

Security review of the AI system architecture, covering:

• AI system configurations to account for AI usage
• Access rights
• Other security-related matters

We assess business and other operational risks associated with the use of AI solutions from a cybersecurity perspective.
The review covers, for example:

• Incorrect responses
• Uncontrolled automation
• Inadequate monitoring
• Data quality
• The impact of the governance model on business operations

The goal is to form a practical understanding of the boundaries within which the solution can be used safely, and in which situations stronger controls or human approval are required.

We also implement vendor-specific solutions, such as Microsoft Purview deployment planning and consulting, which in many cases is a recommended prerequisite before rolling out a large-scale AI solution in Microsoft M365 environments.