AI feature security checklist — LLMs, RAG, agents

The security checklist for adding AI features to your app. Prompt injection, tool-scope, RAG poisoning, rate limits, cost control.

For: Teams adding LLM / agent / RAG features

Prompt injection

  • Untrusted input delimited explicitly in prompts
  • Destructive tools never reachable from untrusted contentcritical
  • Prompt-injection regression corpus in CI

Tool scope

  • Each tool has minimum required permissions
  • Tool schemas typed and validated
  • Tool calls logged with originating prompt

RAG

  • Retrieved content treated as untrusted
  • Vector DB access scoped by tenant
  • Retrieval sources allowlisted

Cost + quota

  • Per-user rate limit on every inference endpointcritical
  • Per-key daily spend cap at provider (OpenAI, Anthropic)
  • Abuse-detection monitors for sudden spend spikes

Transparency

  • AI Bill of Materials (AIBOM) published
  • Model card for each model in inference path
  • Human oversight documented for high-stakes decisions