The article proposes a conceptually new approach to assessing cybersecurity in modern communication networks, which is based on taking into account specialized determinants — sociotechnical parameters that reflect the structural and functional complexity of network interactions. Such determinants include the centrality of nodes, the level of mutual support, the intensity of information exchange, the degree of community connectivity, user popularity, and other non-trivial characteristics that traditional protection mechanisms based on static models ignore. The central idea of the study is to formalize the dynamic stability of the cybersecurity system by building a nonlinear mathematical model that takes into account the nonlinear relationships between these determinants and the general state of network security. Methodologically, the problem is reduced to the formulation of a system of ordinary differential equations that describes the evolution of the system state under the influence of external and internal disturbances, in particular, cyberattacks. For the analytical study of stability, the method of exceptions and solution of the corresponding homogeneous characteristic equation was used, which allows for to identification the conditions of asymptotic stability. Numerical modeling was performed in the MATLAB/Multisim environment, where phase portraits were synthesized, which clearly demonstrate the stable behavior of the system even in the maximum load mode and in the presence of large-scale attacks. The obtained quantitative results confirm that the proposed model adequately reproduces the dynamics of cyber defense and provides the ability to predict the state of the system under conditions of variable network parameters. The key scientific contribution is the development of methodological principles that combine the theory of nonlinear dynamical systems, graph theory, and sociotechnical analysis to form an adaptive, predictive architecture of cyber defense, focused on complex, evolutionary communication networks.