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A Secure AI audit is needed when the company already has an AI pilot, RAG, chatbot or the use of external AI services, but there is no confidence in security, data and risk management.
What's included
Data
What is transmitted to the AI, where requests and responses are stored.
access rights
Roles, administrators, users, sources and rights.
Architecture
Models, RAGs, Integrations, Logs, Loops and Operations.
Risks
PD, trade secret, hallucinations, prompt injection, vendor lock-in.
If the audit shows that the scenario can be put into commercial operation, the next step is design secure AI automation: architecture, roles, logs, human-in-the-loop and rules of operation of AI agents.
Artifacts at the output
| Artifact | Why is it needed? |
|---|---|
| Risk register | Priorities and risks of the AI environment. |
| Safety Checklist | Control requirements for data, access and logs. |
| Architectural Notes | Notes on the current architecture. |
| Roadmap to Elimination | Correction and development plan. |
Team composition
Pentest of AI/API environment
If the AI solution publishes an API, widget, callback point, proxy, or integration with external services, a pentest may be required after the Secure AI audit. It does not check the model as such, but web/API, authorization, access rights, file handling, prompt and API abuse scenarios, and secure loop boundaries.
Frequently asked questions
Is this a model code audit?
No. The main focus is enterprise architecture, data, integrations, access and operation of AI.
Suitable for external AI services?
Yes, if you need to understand what data and processes fall into the external loop.
Can it be combined with a pilot?
Yes, secure audit can go before the pilot or in parallel with him.
External AI services and attack surface
If AI scripts use public APIs, web widgets, proxies, cloud storage, callback points, or external LLM services, they should be considered part of the external attack surface. As part of the Secure AI audit, RESTART checks not only data and roles, but also which technical points of the AI environment are visible to the outside and how they are controlled.
After the audit: pilot in the laboratory
Secure AI audit shows risks and breaks in the AI environment. If, after an audit, you need to check a specific measure - masking, logs, access rights, DLP, SIEM/SOAR, API protection or secure RAG, the next step can be carried out in the information security laboratory on a limited set of scenarios.
Email us
Write to us at info@restart.re or click the button below. For the first letter, it is sufficient to briefly describe the outline, the role of the organization, current systems, limitations and the desired outcome.
Email usLet's discuss your environment
Describe the task, current systems, constraints, and expected results. We will offer a practical first step: diagnostics, pilot, audit, roadmap or project team.
