LLM App Security

Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.

majiayu000 Updated 567 repo stars

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LLM Application Security

Harden chatbots and AI features embedded in web and mobile products.

Baseline Security Checklist

  • Validate and classify all user-provided context.
  • Separate system prompts from user content strictly.
  • Add moderation for toxic, harmful, and policy-violating outputs.
  • Enforce tenant boundaries in retrieval and memory layers.
  • Rate-limit high-cost endpoints.

Secure RAG Pattern

  1. Ingest content with malware and secret scanning.
  2. Tag documents by tenant and access policy.
  3. Filter retrieval candidates by user authorization.
  4. Add provenance metadata in final responses.

Related Skills

majiayu000/claude-skill-registry-data/tree/main/security/llm-app-security commit 6f1d3440a5

Frequently asked questions

npx skillmds@latest add majiayu000/llm-app-security