A Cybersecurity Checklist for AI-Enabled Applications
Protect prompts, data, tools and users with practical controls across the full AI application—not only the model endpoint.
By Gristip Security Team
AI applications introduce new input and action paths, but the security fundamentals remain familiar: minimize access, validate untrusted data, monitor behavior and plan for failure. The model is one component in a wider application threat model.
How to threat-model an AI feature
Map the data entering the system, the context added to prompts, the tools the model can call and every place an output is used. Treat retrieved documents, web content and user prompts as untrusted input.
- Separate instructions from untrusted content.
- Authorize every tool action outside the model.
- Redact secrets and sensitive data before logging.
- Rate-limit expensive and high-impact operations.
Test controls continuously
Security tests should cover prompt injection, data leakage, excessive agency, insecure output handling and denial-of-wallet scenarios. Re-run the suite when models, prompts, retrieval sources or connected tools change.
How Gristip helps clients secure AI products
Gristip includes threat modelling, least-privilege integration, validation and auditability in the delivery process. We help clients establish practical release checks so AI security becomes repeatable engineering work rather than a one-time review.