Malware Analysis of Data Theft Untilizing PDF File - Muin, Yasir (JATISI, 2025)
The increased use of PDF files as a medium for cyberattacks has created significant challenges in data security, especially in terms of detection and mitigation of malware threats designed for data theft. This research aims to analyze malware threats in PDF files using static and dynamic analysis approaches to identify patterns that characterize malicious activity that could result in sensitive information leakage. Through static analysis, this research identifies specific elements in the PDF file structure, such as metadata, signatures, as well as malicious indicators that are usually hidden within scripts and encapsulated objects. On the other hand, dynamic analysis is performed by utilizing a sandbox environment to monitor the runtime behavior of PDF files, including network activity, file system access. The results show that the combination of static and dynamic analysis is able to provide more comprehensive detection, where static analysis is effective in quickly identifying signs of malware, while dynamic analysis provides deeper insights into malware behavior patterns that are not detected by static analysis alone.This research provides a static and dynamic analysis-based framework for malware identification on PDF files, as well as providing insights into the effectiveness of these methods in the context of modern data security. The findings of this research have the potential to support the development of security systems