Unveiling The Detection of File Less Malware from Dark Web: A Stealthy Arsenal for Web Application Exploitation

Abstract

The proliferation of fileless malware poses a significant threat to web application security, especially when sourced from the dark web. This paper presents a novel detection tool designed to identify and mitigate fileless malware sourced from the dark web, specifically targeting web applications. Leveraging advanced anomaly detection and behavioral analysis techniques, the tool monitors real-time traffic and user interactions, enabling the early detection of malicious activities. Additionally, the tool integrates seamlessly with threat intelligence sources, enhancing its ability to recognize emerging threats. A user-centric alerting system ensures that administrators are promptly notified of potential security breaches, allowing for immediate remediation actions. The tool's adaptability and continuous enhancement mechanisms ensure that it stays ahead of evolving threats. By employing this detection tool, organizations can bolster their web application security posture and protect sensitive data from sophisticated fileless malware attacks.