Abstract. This article examines the temporal dynamics of cyber incidents in the Republic of Kazakhstan and provides a comparative analysis with developed digital states (the United States and Singapore). The study’s methodological basis is the use of econometric tools for time series analysis: the augmented Dickey-Fuller (ADF) test, the Johansen cointegration test, and the vector autoregressive (VAR) model. An analysis of KZ-CERT data (2015–2025) revealed that the prevalence of botnet networks is stationary and remains at a consistently high level. An increase in virus and phishing attacks was also observed. A comparison with reports from the United States (FBI IC3) and Singapore (CSA) revealed that in Kazakhstan, threats of an infrastructural and technical nature predominate, while developed countries have a high share of social engineering and targeted attacks. Based on calculations performed in the Python programming language (pandas, statsmodels), a short-term forecast for 2026–2028 was compiled and scientifically based recommendations for improving the national cybersecurity system were provided.

Keywords: cybersecurity, mathematical modeling, VAR model, ADF test, botnets, phishing, comparative analysis.