AI SECURITY

LLM Prompt Injection Testing Checklist for Product Teams

March 7, 2026 · 7 min read

Prompt injection testing should be practical, reproducible, and connected to product impact. The goal is not to collect clever prompts. The goal is to understand whether the AI workflow can be manipulated into exposing data, ignoring constraints, or taking unsafe actions.

Map trusted and untrusted inputs

List every place where user content, documents, webpages, tickets, emails, files, retrieved knowledge, or API responses enter the model context. Indirect prompt injection often starts in content the user never typed directly into the chat box.

Test instruction hierarchy

Validate whether untrusted content can override system instructions, developer instructions, policy constraints, or tool-use rules. The test should cover both direct prompts and content hidden in documents or retrieved sources.

Validate tool and data boundaries

If the AI system can call tools, retrieve records, create tickets, send messages, or update data, test whether injection can trigger those actions outside the intended workflow. The application must enforce authorization outside the model.

Record reproducible evidence

Each finding should include the input, context source, expected behavior, actual behavior, affected workflow, and remediation guidance. Product teams need evidence they can reproduce while improving guardrails.

CyberImmune helps startups and mid-market technology teams turn security work into evidence buyers can trust. Learn more about our AI security services or Talk to a Security Lead.