TrapScan — AI Agent Trap Detector

TrapScan is a browser-native AI security tool designed to detect adversarial web content targeting AI agents in real time. As AI assistants increasingly browse websites, summarize information, and execute tasks autonomously, the web itself is becoming an attack surface. Attackers can embed hidden instructions inside webpages that are invisible to humans but fully readable by AI systems. These attacks can manipulate AI reasoning, inject malicious prompts, override safeguards, or trigger unauthorized actions. Inspired by Google DeepMind’s “AI Agent Traps” research, TrapScan implements detection for six major AI agent attack categories, including prompt injection, semantic manipulation, jailbreak attempts, hidden behavioral control patterns, and systemic adversarial traps. TrapScan combines fast local browser detection with AI-powered classification using Gemma 4 (gemma-4-26b-a4b-it). The Chrome extension scans HTML, CSS, metadata, JSON-LD schema, hidden DOM elements, and suspicious prompt patterns directly inside the browser. Suspicious findings are then analyzed by Gemma 4, which classifies threats, assigns risk scores, filters false positives, and explains attacks in plain English. The project includes: * A Manifest V3 Chrome extension * Real-time threat analysis UI * Browser risk indicators * Scan history and downloadable audit reports * A live Vercel-hosted web demo for instant testing TrapScan represents a new category of browser-native defense tooling focused specifically on protecting AI agents from manipulation on the open web.