secure-ai
Secure AI
Overview
Secures AI integration layers through multi-layered defense, structural isolation, and zero-trust orchestration. Covers prompt injection defense, model output validation, agentic security, secure server actions, supply chain integrity, MCP tool security, and audit protocols for applications that interact with LLMs.
Aligned with the OWASP Top 10 for LLM Applications 2025 and the NIST AI Risk Management Framework (AI RMF 1.0). Provides coverage for all ten OWASP LLM risks with concrete defense patterns.
When to use: Securing LLM-powered features against prompt injection, validating and sanitizing model outputs before downstream use, implementing zero-trust for autonomous agents, hardening server actions for AI endpoints, securing MCP tool integrations, managing AI supply chain risks, auditing AI access patterns.
When NOT to use: General web application security without AI components, frontend-only security concerns, non-AI API hardening, basic authentication or authorization without AI involvement.
Quick Reference
| Pattern | Approach | Key Points |
|---|---|---|
| Structural isolation | Separate system/user message roles | Never mix instructions and user data in one string |
| Input boundaries | Delimit user data with markers | Helps models identify where untrusted data begins/ends |
| Guardian model | Pre-scan input with a fast classifier | Detect injection patterns before main reasoning model |
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