Cybersecurity: Smart Malware Detection Tool

Cybersecurity threats like malware are becoming more advanced in today's digital world. These can be dangerous for people, businesses, and governments. Old antivirus systems, which relied on virus signatures, are not enough anymore. They struggle against new threats known as zeroday threats, such as changing viruses or ones not seen before. This project explains how tomake a smart tool that finds malware using machine learning. It uses a Random Forest Classifier, examining file characteristics like size, patterns, entropy, and hash signatures to determine if a file is harmful or safe. There is also a simple web interface where users can upload files, get quick scan results, and download detailed reports.We used tools like Python, Scikit-learn, Flask, and Joblib to create this platform. Tests show it finds malware accurately, over 94% of the time, with strong precision and recall. Unlike traditional antivirus software, this system offers clear risk scoring and detailed reports, which help everyone, whether they're tech-savvy or not. It's easy to use, can grow as needed, and makes digital spaces more secure. In the future, we may improve it by adding features that monitor malware behaviour live, connect to real-time threat updates, and use cloud technology to enhance its power.