This paper presents a unique mathematical model, SAEIQRS, to understand the dynamics of cybercrime propagation in response to the growing danger of cybercrime. The model combines epidemiological principles with cyber-attack dynamics to capture the complexities of cyber threats. Assessing the impact on vulnerable individuals, asymptomatic illnesses, exposures, and organizational vulnerabilities are among the goals. Questions about infection phases, workplace dynamics, and external sources are investigated. Simulations using deSolve, ggplot2, dplyr, and R libraries reveal detailed patterns that relate cyber-attacks to diseases and organizational weaknesses. The model’s adaptability in scenario research is highlighted by key findings, which identify vital periods and sensitive sectors. The research yields useful insights for cybersecurity policy and intervention plans.