Complex nature of modern challenges and threats, turbulence of the geopolitical situation, financial, economic and energy crises, along with natural and man-made disasters carry significant risks to the national security of any state. The unexpected intensity of the COVID-19, coupled with other hybrid risks, revealed significant deficiencies in the national security risk assessment (NSRA) system. Issues concerning NSRA are becoming more important in academic literature last 20 years as well as new theories to anticipate possible challenges for better public administration. Academic literature on risk assessment in the context of national security is currently presented in four main clusters. Historically, the first consists of articles in the framework of systematic logical analysis that was formed under the influence of a number of researchers from Carnegie Mellon University who use a deliberative risk ranking method, also called the “Carnegie Mellon risk ranking method”. The second part of the approaches to NSRA is based on the verification method of the research which uses mainly quantitative methods (sometimes using a historical approach to forecasting) to assess the components of the national security of the state, including justifying the need to build a technocratic risk assessment system to prevent “state failure”. Development of new technologies and innovations has led to the emergence of a research group on the use of anticipatory mechanisms in predicting risks of new innovative technologies. In this case, Anticipatory Governance is described as a system of institutions, rules and norms that allow the use of foresight in order to reduce risks and increase the ability to respond to events at an early rather than later stages of their development. The final part of academic publications consists of very specific articles in the framework of systematic logical analysis of military strategies and other doctrines which by nature of its risks are understood as hybrid, that is, combining artificial and natural origin.