In this paper, we consider a population of digital nodes (such as phones, computers, etc.) that are under the attack of two competing malware. These malware infect the nodes in order to exploit their computational resources for specific purposes such as mining crypto-currency, cloud computing, etc. We suppose that each virus spreads following the susceptibleinfected-susceptible (SIS) compartmental model. Additionally, we assume that the malware designers can tune the percentage of resource utilization from their host nodes. A higher resource utilization implies a higher instantaneous profit but will also lead to faster detection and elimination (node recovery) of the malware. Once the malware is detected, complete protection of the infected node by means of anti-malware software is also possible at a smaller rate. The proposed setup results in a non-cooperative game between the two players (the malware designers) trying to maximize their profit i.e., the resources utilized from the infected nodes. We characterize and analyze the Nash equilibrium for such a game using a timescale separation approximation. Finally, we numerically validate the approximation and we compute the price of anarchy.