The Problem Enterprises are aggressively adopting AI tools, but they face a massive blind spot: no one is watching what employees send to these models. Every day, sensitive data—client financial figures, AWS credentials, and confidential M&A details—is accidentally leaked into public LLMs. Traditional Data Loss Prevention (DLP) tools rely on outdated, static regex patterns and completely miss the semantic context of natural language. The Solution: SentinelLens SentinelLens is an autonomous Agentic Security Firewall built for the TechEx Hackathon. Powered by Google Gemini 2.5 Flash Lite, it acts as a Trust Layer proxy sitting between your employees and external AI systems. Key Features: 1. Intelligent Prompt Interception: When an employee submits a prompt, SentinelLens intercepts it. Gemini semantically analyzes the text, detects sensitive entities (PII, IP, Credentials), assigns a risk score (0-100), and autonomously decides whether to ALLOW, SANITIZE, or BLOCK the request. 2. Real-Time SOC Dashboard: Security teams get a premium, dark-mode dashboard providing live telemetry on risk distributions, actions taken, and departmental AI usage. 3. Knowledge Gap Engine: Instead of just blocking users, SentinelLens groups unsafe queries to identify organizational training gaps (e.g., "15 employees leaked GDPR data -> Trigger Compliance Training"). 4. Natural Language Policy Studio: Security engineers can type rules in plain English (e.g., "Block all AWS keys"), and Gemini instantly converts them into structured YAML firewall rules. Hackathon Track Alignment: Track 1 (Agent Security): We built a purpose-built AI governance agent that intercepts, sanitizes, and audits enterprise AI traffic. Track 2 (Google AI Studio): We utilized Gemini 2.5 Flash Lite as the core reasoning engine for deep prompt inspection and zero-shot entity detection.
Category tags: