Agricultural modernization is the foundation and pillar of national modernization, and its security should not be ignored. However, the traditional efficiency assessment does not take security factors into account. To improve this work, we tried to embed multidimensional security issues into the assessment framework of agricultural modernization efficiency (AME) and analyzed its efficiency levels, regional differences, and dynamic evolution using the Super-EBM model, Dagum Gini coefficient, and spatial Markov chain model. We found that: (1) At the national level, the agricultural operation efficiency (AOE) and agricultural service efficiency (ASE) were generally lower than the agricultural production efficiency (APE), with significant potential for improvement. The spatial characteristics exhibited evident spatial clustering, and the spatial differences in AME, AOE, and ASE were similar. (2) The overall Gini coefficient of AME fluctuates in the range of 0.1168–0.1334 from 2006 to 2020, and the differences in AME were dominated by inter-area differences, with an average contribution rate of 68.72%. (3) The spatial pattern of AME was relatively stable, with prominent “club convergence” characteristics, and spatial factors had adverse spillover effects on the evolution toward convergence. Policymakers should strive to fill the shortcomings of agricultural operations and agricultural services, formulate differentiated agricultural strategies for development and promote knowledge exchange and technological diffusion. These are important for building a modern agricultural system and promoting the spatially balanced development of modernized agriculture.