In the never-ending battle against rising malware threats, cybersecurity professionals were constantly challenged by malware researchers. Businesses and institutions that have fallen prey to these threats that have suffered significant financial losses and enormous disruption to countless lives. As a result, security approaches have evolved to include preemptive measures such as the widespread use of HoneyPots. However, data-driven decision-making was required to improve the effectiveness of such approaches. Therefore, this paper describes a quantitative analysis that assesses various malware samples using system metrics and network log data. The goal is to properly visualise this information and analyse if it can aid in decision-making processes, ultimately leading to the construction of more robust and secure networks. To help with this research, a dashboard application was created that allows the installation of virtual machines, the configuration of virtual networks, and the collection of system metric data from outside sources. The findings of this paper can help greatly improve network security and stay ahead of threats in the cat-and-mouse game.