
Guni is a robust security middleware designed to protect AI agents from various online threats. It acts as a protective layer between your AI agent and the web pages it interacts with, ensuring that potential threats are detected and neutralized before execution. Key features include real-time scanning, prompt injection detection, phishing protection, and clickjacking prevention. Guni's multi-vector scanning capability ensures that every page visited by your agent undergoes a comprehensive security check in under 0.001 seconds. How it works: Guni employs a two-layer approach combining fast heuristics and LLM reasoning to catch known and novel attacks. The system parses raw HTML to extract visible text, hidden elements, forms, and scripts, running all eight detectors simultaneously. When a threat is flagged, Guni's LLM analyzes the intent to catch reworded attacks. Security layers include prompt injection, phishing forms, UI deception, malicious scripts, goal hijacking, clickjacking, CSRF & token theft, and open redirects. Guni is built for real browser workflows, protecting autonomous browsing sessions and sensitive workflows like finance and procurement. The product offers a free tier for self-hosted usage and a hosted API with customer portal for advanced needs. Open source under the MIT license, Guni provides a free heuristics layer and self-host path for technical evaluation, with the source code available on GitHub.
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