<p>In this study, we propose a hybrid epidemic model to analyze the spread of malware in wireless sensor networks (WSNs). We extend classical epidemiological modeling by introducing the notion of mobile infected sensors, along with antivirus maintenance mechanisms, to better capture malware outbreak dynamics in WSNs. Motivated by real-world threats such as mobile compromised devices and the sleep–wake architecture of WSNs, we propose a novel model in which stationary sensors become infected through two distinct pathways: local transmission arising from sensor-to-sensor interactions, and external transmission driven by mobile infected agents. The model captures spatial dynamics through the infection front radius and considers the independent mobility of external infected devices. Next, we enhance the model by integrating a sleep-mode-based anti-virus scheme, where infected sensors are partially cured during maintenance. For both settings, we derive the corresponding mathematical models, determine equilibrium points, and analyze their stability. We characterize outbreak conditions and show how the introduction of anti-virus actions can effectively control malware spread. The results highlight the critical role of mobility and maintenance scheduling in the resilience of WSNs against cyber-epidemics.</p>