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While previous literatures have analyzed the vulnerability of high-speed rail network (HSRN), they rarely consider its service feature. Obviously, one of the key features of HSRN is offering passengers fast travel services. This study selects the passenger flow and travel time to describe the service feature of HSRN, and constructs a multiple-weight HSRN. Then, the service performance is taken as the indicator of HSRN's vulnerability by innovatively integrating complex network theory and reliability theory. Using the daily operation data of China's HSRN (CHSRN) merged with the coordinate data and statistics data in November 2018, this study assesses its vulnerability under natural hazards and manmade accidents. Afterwards, the critical component and critical area within CHSRN are identified by the spatially localized failures (SLFs) model. Comparing with the results obtained by previous methods, this study finds that the vulnerability of CHSRN is always overestimated, and some critical components are overlooked regardless of its service feature. Furthermore, we also find that the critical areas within CHSRN mostly lie on the Yangtze River Delta as considering the service feature, while they are scattered along Beijing-Guangzhou railway line or Beijing-Shanghai railway line as ignoring the feature. These findings can help administrators develop different strategies to better prioritize the allocation of limited maintenance resources and mitigate the vulnerability of HSRN. • Select travel time and passenger flow to describe the service feature. • Describe HSRN as a multiple-weight network. • Take service performance as the indicator of HSRN's vulnerability. • Investigate the impacts of service feature on vulnerability analysis. • Identify critical components and critical areas within HSRN. [ABSTRACT FROM AUTHOR]