AI Security Assessment

The Problem

The rush to adopt AI is creating massive security blind spots. Employees are pasting sensitive company data into public LLMs. Development teams are integrating third-party AI APIs without proper access controls, and new AI features are being shipped without testing for novel vulnerabilities like prompt injection.

Traditional security assessments often miss these AI-specific risks, leaving your data and infrastructure exposed.

Who It's For

• SaaS companies building generative AI features into their products.
• Enterprises developing internal LLMs or RAG (Retrieval-Augmented Generation) applications.
• Organisations concerned about "Shadow AI" and employee data leakage via ChatGPT or similar tools.
• Companies looking to establish secure AI governance policies.

What's Included

We assess both the human and technical elements of your AI adoption strategy.

• AI Application Security: Testing internal AI apps for prompt injection, sensitive data disclosure, and access control bypasses.
• API & Integration Security: Reviewing how your applications communicate with third-party LLM providers (e.g., OpenAI, Anthropic).
• Shadow AI & Data Leakage: Assessing controls preventing employees from exposing intellectual property or customer data to public models.
• AI Governance: Reviewing your Acceptable Use policies regarding AI tools.

Final scope is tailored depending on whether you are building AI applications or simply trying to manage employee usage.

What You Receive

• Executive summary of your AI risk exposure.
• Detailed technical report on vulnerabilities in your AI integrations.
• Analysis of potential data leakage paths.
• Practical recommendations for securing AI pipelines and establishing governance.

Why This Matters

Innovation shouldn't compromise security. By understanding your AI risk, you can confidently deploy new features, empower your employees to use AI tools safely, and protect your intellectual property from unintended exposure.

FAQs