Optimization of Malware Code Insertion Using MD5 Collision - Fauzi Abdurrachman; Bambang Suharjo; Yudhi Biantoro (Mathematics Education Study Program, 2025)
The contemporary digital landscape relies heavily on the MD5 hash algorithm for ensuring data integrity, yet its susceptibility to collision attacks raises concerns about its security in modern cybersecurity practices. This study delves into the weaknesses of MD5 collisions, particularly focusing on the Unicoll technique. By embedding malicious code into files while preserving their original MD5 hash values, the research aims to demonstrate the potential security risks associated with MD5 collisions. The experiment successfully generates collisions between modified files containing malware and their unaltered counterparts, showcasing MD5's vulnerability to collision attacks. Moving forward, future research could explore methods for embedding malware that evades detection by anti-malware solutions, expand embedding techniques to encompass various file formats, and investigate alternative collision generation methods for improved efficiency and effectiveness. These endeavors offer promising directions for advancing cybersecurity measures and mitigating malware threats in the digital landscape.