In-depth analysis of the characteristics and influencing factors of the spatial network of tourism ecological security has significant and far-reaching significance for promoting the sustainable development of ecotourism, optimizing the spatial layout of tourism, and realizing the long-term healthy development of the tourism industry and the harmonious coexistence of the ecological environment. Based on China’s inter-provincial panel data from 2005 to 2021, this study applies the improved entropy value method to measure the development level of tourism ecological security in 30 provinces (autonomous regions and municipalities), and combines the modified gravitational model, the social network analysis method, and the QAP regression model to deeply explore their spatial correlation network characteristics and influencing factors. The results show that: ① China’s inter-provincial tourism ecological security links have broken the traditional pattern of geographic proximity and become spatially connected with non-neighboring provinces (autonomous regions and municipalities), but with strong volatility, a stable development pattern and the most ideal state have not yet been formed, and there is still great potential for improvement; ②The regional differences and imbalances in China’s tourism ecological security spatial association network were more obvious, in which the eastern region occupied the core position by virtue of its high degree of centrality and played an important role in regulating and controlling the spatial associations of tourism ecological security among other regions, while the western region was in the periphery of the network, and had less influence on the other regions; In addition, the COVID-19 epidemic had a significant impact on the pattern of the spatial associations of the tourism ecological security network;③Beijing, Tianjin, Jiangsu, Zhejiang and Shanghai constituted the “net beneficiary” segment characterized by significant benefits, while Guangdong and Fujian played an important intermediary role in the “broker” segment. Meanwhile, 23 provinces and regions, including Hubei, Hunan and Guangxi, were categorized as “net spillover” sectors with obvious spillover effects. ④Urbanization, geographic proximity, the structure of the tourism industry, technological innovation, and the level of tourism development have collectively contributed to the formation and evolution of the spatial network structure of tourism ecological security in China. Starting from the perspective of spatial correlation network, the study reveals the dynamic evolution characteristics of the spatial network structure of tourism ecological security in a panoramic way at a larger scale, and analyzes the influencing factors of tourism ecological security at a deeper and more detailed level, which provides important theoretical support and practical guidance for the formulation and implementation of tourism ecological protection strategies.