Advanced Persistent Threat (APT) malware poses a significant cybersecurity challenge due to its stealthy propagation and ability to remain dormant before activation. Conventional epidemic models may not adequately capture this latent behavior or the heterogeneity of organizational networks. This paper develops a mathematical model for APT malware propagation in two interacting populations, Client and Server, by incorporating a latent compartment and distinguishing the transmission and recovery characteristics of the two groups. The basic reproduction number is derived, and the equilibrium points, stability properties, and control conditions are analyzed. Numerical simulations are conducted to investigate the propagation dynamics under different parameter settings. The results demonstrate that the proposed framework can capture both malware persistence and elimination regimes and highlight the effects of network connectivity and recovery capability on propagation dynamics. The framework provides an interpretable mathematical approach for analyzing and controlling APT malware propagation in heterogeneous organizational networks.

APT malware,Simulation