MAVEN: Malware Analysis & Vulnerability Exploration Research Group
Description
This project presents a comprehensive approach to understanding and combating the evolving threat of malware in the cybersecurity landscape. It is structured in two parts: the first focuses on imparting fundamental knowledge and skills in malware analysis, while the second explores the integration and impact of emerging AI technologies in this field. The project combines theoretical learning with practical exercises, allowing students to analyze real malware samples and engage with the latest developments in AI. This hands-on approach is designed to equip students with essential cybersecurity skills and encourage them to explore innovative ways AI can enhance malware analysis and defense strategies.
Objectives
- Teach students basic and advanced static & dynamic malware analysis.
- Demonstrate how to set up and configure a safe environment for malware analysis.
- Guide the students in comparing and contrasting analysis output from different malware analysis tools.
- Challenge the students to apply their newly acquired skills by analyzing a new set of malware samples.
- Promote the development of research skills by encouraging students to explore and discover how emerging technologies in AI are reshaping malware analysis.
Metrics
- Successfully build a malware sandbox.
- Apply static and dynamic analysis to the initial set of malware.
- Use PANDA (https://panda.re/) to successfully analyze the initial set of malware, comparing results to previous analysis.
- Given an unknown set of malware, analyze and identify advanced malware techniques (e.g., obfuscation).
- Being able to discuss how emerging technologies in AI can reshape malware analysis.
- Propose a potential solution for malware analysis that uses an emerging technology.
- Stretch goal: Build an initial prototype of the proposed solution.
Members

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Angel K. Vázquez Sánchez – PM
Glorián M. Serrano Ortiz
Raquel M. Quiñones Vélez
Jeimy M. Santiago Morales – Co PM
Samuel A. Maldonado Rodríguez
Arnaldo R. Maisonet Vázquez
Karina López Rodríguez