Design and Architecture of a Cloud-based Malware Analysis Sandbox

Abstract

Malware remains one of the most adaptive and severe Cyber threats, challenging the security of systems from individual devices to enterprise infrastructures. As malware attacks evolve, traditional detection methods, heavily reliant on signature-based approaches, are increasingly bypassed by sophisticated malware employing evasion techniques. In response, this study presents a comprehensive design and implementation of a cloud-based malware analysis sandbox, offering a scalable, secure, and adaptable solution for analyzing and mitigating advanced malware threats. The system enables users to upload files for static, dynamic, and behavioral analyses across major operating systems, including Windows, Linux, and Android. Leveraging cloud infrastructure, the sandbox combines key components such as virtual machines, a signature database, realtime RDP connections, and a user-friendly web application to facilitate interactive malware analysis. The architecture is tailored to address sandbox evasion techniques, optimize resource allocation, and enhance scalability, making it a robust solution for malware detection and analysis in modern Cybersecurity landscapes.