Don’t Rank the Guardrails: Map Prompt-Injection Defenses to the Stack
TL;DR for operators Prompt-injection defense should not be procured as a leaderboard winner. A systematic review of 88 studies finds defenses distributed across several parts of the LLM system, from training and prompt handling to document boundaries, tool execution, output filtering, and continuous testing.1 Fifty-six of those 88 approaches, or 63.63%, are model-agnostic: they can operate around different models without changing model weights or architecture. That matters for teams building on proprietary APIs. ...