UI-Based Defense Against Prompt Injection: From Gentle Guidance to Mandatory Re-education

Prompt injection attacks remain a persistent security challenge in AI systems, with traditional technical defenses often bypassed through social engineering and template distribution. This paper proposes a novel defense strategy that shifts the battleground from technical barriers to user behavior modification through UI design. Drawing parallels to traffic safety education, we present a graduated response system that treats template-based prompts as "unlicensed operation" and provides mandatory educational interventions before system compromise occurs. The proposed solution is cost-effective, platform-agnostic, and intentionally patent-free to encourage widespread adoption.Co-written by Viorazu. and Claude ( Sonnet 4.5, Anthropic)共著:Viorazu. & Claude( Sonnet 4.5、Anthropic)