CYBERATTACK PREVENTION THROUGH THE DEVELOPMENT OF A MULTI-VULNERABILITY SCANNER

Abstract

The growing number of cyber threats, especially malware and phishing, poses serious risks to both personal and sensitive information in today’s digital world. This research aims to develop a user-oriented web application to assist individuals in identifying and mitigating cybersecurity threats originating from various digital inputs such as URLs, emails, and file attachments. The system was developed using the Agile methodology, which enabled iterative development, continuous user feedback, and flexible refinement throughout the project lifecycle. The system combines machine learning, reputation analysis, and external service integration to detect suspicious behaviour effectively. Designed to be accessible for all users, the application provides a simple interface and clear, interactive scan results. It also helps users recognize threats hidden in the digital content they commonly interact with. Testing shows that the system can detect different types of threats accurately and supports user awareness of digital security.