Threat Guard AI: A Multi-Domain System for Intelligent Fraud Detection Using Machine Learning

Abstract: In the era of rapid digital transformation, cyber threats such as phishing, QR code manipulation, UPI fraud, and PDF malware have become increasingly sophisticated. Threat Guard AI is a comprehensive, multi-domain fraud detection system designed to counter these threats using artificial intelligence and machine learning. The platform integrates specialized modules to analyze UPI transactions, QR codes, PDF documents, and phishing links. Through a user-centric Streamlit interface and a robust Flask backend, it provides real-time analysis, prediction, and alerts. Each module is powered by trained models using Scikit-learn and OpenCV, with MongoDB for scalable data storage. Threat Guard AI not only enhances the precision of fraud detection but also ensures actionable insights, unified visualization, and extensibility to new threat domains. This paper presents the architecture, implementation methodology, and system performance analysis of Threat Guard AI, demonstrating its capability to provide intelligent, real-time digital threat mitigation