Building a Framework for AI Red-Teaming: Why Scope and Controls Matter

Most security teams lack structured methodologies for red-teaming AI systems, relying instead on traditional approaches that fail to address LLM-specific vulnerabilities. This article establishes a practical framework—from defining scope and threat models to systematically testing both direct and indirect prompt injection—that emphasizes control-layer validation as the true attack surface. Understanding how to evaluate system prompts, content filters, and output validation in concert, rather than hunting for single bypasses, marks the evolution toward enterprise-grade AI security practices.