DERIV
Every company deploying AI agents faces the same invisible threat: prompt injection. Traditional WAFs detect SQL injection and XSS, but LLM attacks are plain English — no signatures to match. AEGIS WAF solves this with 5 independent defense layers running in parallel: Pattern Detection catches known attack signatures in ~2ms, Intent Analysis uses LLM-powered classification to understand malicious intent, Semantic Guard matches against known attack vectors, Context Tracking monitors multi-turn session behavior, and Output Guard scans LLM responses for data leaks and policy violations before they reach the user. The platform includes a real-time security dashboard, interactive demo where users can test attacks live, Slack integration for instant threat alerts, complete audit logging, and configurable security policies. Built with Next.js 15, TypeScript, and deployed on Vercel, AEGIS integrates into any LLM application in just 3 lines of code. Named after the shield of Zeus in Greek mythology, AEGIS provides divine protection for AI — making agents safe to deploy on the public internet.
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