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A1-lex/salamanet-bot

Domain:

digital infrastructure

Record type:

software
Creator:
A1-
Host:
An AI-Powered Cyber Threat Detection & Monitoring System for African Digital Infrastructure . πŸ” SalamaNET AI AI-Powered Cybersecurity for Africa's Education & Public Sectors SalamaNET AI is a smart, context-aware cybersecurity system built to detect threats, monitor anomalies, and prevent phishing attacks across public and educational institutions in Africa. Our goal is to enhance digital safety through real-time, automated, and locally-relevant AI solutions. 🚨 Problem Statement "Increased cyberthreats due to poor cyber hygiene." Educational and public sector systems in Africa β€” especially in countries like Kenya β€” are facing a surge in cyberattacks. Most institutions lack active monitoring tools, suffer from poor password practices, and are unaware of phishing tactics. 🌍 Why It Matters Kenyan examples: Public agency data breaches Schools disrupted by ransomware Leaked citizen data due to weak security practices These events reflect a growing crisis that demands an affordable, intelligent, and homegrown solution. πŸ€– The Solution: SalamaNET AI SalamaNET AI is an AI-based platform designed to: πŸ›‘οΈ Detect phishing attempts in real time πŸ“‘ Learn continuously from user feedback βœ‰οΈ Empower institutions with actionable visibility into threats βš™οΈ How It Works (MVP / Phase 1) Right now, the MVP (Minimum Viable Product) focuses on phishing detection and learning: User enters message β†’ Model predicts "safe" or "phishing" + confidence β†˜ User feedback (correct/incorrect) β†˜ Feedback logged & used for retraining Key Features: βœ… Message classification (phishing/safe + confidence score) βœ… User feedback system (mark predictions as correct/incorrect) βœ… Retraining loop (model improves once enough new feedback is collected) βœ… Admin log viewer (daily summaries, filter by model version, view history) πŸ“‚ Project Structure salamanet_ai/ │── app.py # Flask web app │── retrain_if_needed.py # CLI helper for retraining │── train_sklearn.py # Training script (TF-IDF + Logistic Regression) │── predictions_log.csv # Saved predictions │── feed …