Agriculture is considered one of the most critical domains for human beings. Currently, agriculture and supply chain businesses are becoming increasingly reliant on technology and interconnectivity. However, this inevitable necessity also brings about potential risks. Due to the widespread use of new technologies to improve productivity in agriculture, cybersecurity risks have inevitably emerged. To proactively mitigate the risks related to cybersecurity, it is important to understand the attack vectors, such as malware. Thus, malware analysis is indispensable for understanding the characteristics and behaviors of malware and developing defense strategies against malicious attacks based on data collected from the results.In the literature, two different techniques have been widely used to analyze malware: Static Analysis and Dynamic Analysis. While Static Analysis aims to investigate the structure of the malicious software at a low level, Dynamic Analysis focuses on the behavior of the malware when it is being executed. As executing malware may harm the host system, an isolated environment should be established for Dynamic Analysis.This study focuses on Malware Analysis in terms of the dynamic analysis approach. Additionally, an isolated, automated dynamic analysis platform was developed, and analysis was implemented in a virtual environment using Cuckoo and VirtualBox to collect data from analyzing various malware behaviors. This data can be used to create a partial test dataset that may contribute to developing defense strategies against malware.