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Building Voreenth: An AI Runtime Security Gateway

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About Building Voreenth: An AI Runtime Security Gateway

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🖥️ Live Application https://voreenth.streamlit.app 📂 GitHub Repository https://github.com/Jibril-ctrl/voreenth 🌐 Website https://jibrilctrl.com/ 💼 LinkedIn https://www.linkedin.com/in/jibril-anifowoshe --- As organizations rapidly adopt Large Language Models (LLMs), AI copilots, and agentic AI workflows, a new attack surface has emerged: The prompt. In this video, I demonstrate **Voreenth**, an open-source AI Runtime Security Gateway that inspects prompts before they reach a Large Language Model. Rather than relying on the model itself to determine whether a request is safe, Voreenth performs runtime inspection, detects security threats, assigns risk scores, and enforces policy decisions before inference occurs. ## Throughout this demonstration, you'll see Voreenth inspect, classify, score, and enforce security controls against: • Prompt Injection • System Prompt Extraction • Environment Reconnaissance • Secret & API Key Exposure • Sensitive Data (DLP-like) Detection • Credential Extraction Attempts • Runtime Risk Scoring & Policy Enforcement --- ## 🛠️ Technology Stack 🐍 Python ⚡ Streamlit 🗄️ SQLite 🦙 Ollama 🧠 Qwen 3 ☁️ Cloud LLM ⚙️ Custom Runtime Policy Engine --- ## 🏛️ Enterprise Architecture Although demonstrated locally, the same architectural pattern can be positioned in front of: • Azure OpenAI • Azure AI Foundry • Anthropic Claude • Google Vertex AI • Amazon Bedrock • Self-hosted Open-Source Models • Enterprise AI Platforms The objective is simple: Inspect. Score. Enforce. ...before requests ever reach the model. --- If you found this project valuable, consider starring the GitHub repository, trying the live application, and subscribing for future enterprise AI security builds. Thank you for watching. — **Jibril Anifowoshe** #AI #AISecurity #LLMSecurity #CyberSecurity #PromptInjection #ArtificialIntelligence #GenerativeAI #Python #Streamlit #Ollama #ZeroTrust #SecurityArchitecture #OpenSource #AgenticAI

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