Abstract: Understanding the impacts of different types of sudden events on shipping networks and their recovery mechanisms is of critical importance for ensuring maritime stability and advancing the sustainable development of ports. This study takes the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of China’s most economically dynamic regions, as a case to systematically analyze the structural vulnerabilities and resilience mechanisms of its shipping network under various disruptive scenarios. Drawing on complex network theory, the GBA shipping network is constructed, and key topological metrics such as network efficiency, connectivity, and the number of independent paths are quantified, providing a rigorous framework for evaluating network performance under stress. Four disruption scenarios are designed to simulate potential real-world shocks: degree-based attack (DA), betweenness-based attack (BA), strength-based attack (SA), and random attack (RA). The results indicate that the ports of Hong Kong, Shenzhen, and Guangzhou serve as core nodes, and their resilience directly shapes the overall stability of the network. Although the initial network exhibits high connectivity and efficiency (connectivity: 10.300; efficiency: 0.295), the failure of these core ports substantially degrades both metrics, demonstrating that network vulnerability is highly concentrated in critical hubs. In particular, attacks targeting node degree and strength cause the most pronounced declines in network performance, underscoring the system’s dependence on highly connected or high-throughput ports. During the recovery phase, four strategies are evaluated: degree-based recovery (DR), betweenness-based recovery (BR), strength-based recovery (SR), and random recovery (RR). The analysis shows that under DA disruptions, the SR strategy proves most effective, achieving network connectivity resilience of 0.76 and independent path resilience of 0.54. Conversely, under BA and SA scenarios, the BR strategy performs better, particularly in restoring network efficiency, with resilience reaching 1.00 and 0.83, respectively. These results suggest that recovery strategies should be tailored to the type of disruption, and that prioritizing the restoration of critical nodes is more effective than random or uniform recovery in strengthening network resilience. Furthermore, the exponential random graph model (ERGM) is employed to examine the network’s formation and evolution mechanisms. The findings reveal that the GBA shipping network is shaped by a combination of endogenous structural effects, node attribute effects, and exogenous relational effects. Structural tendencies such as reciprocity and clustering highlight the importance of bilateral cooperation between ports and the emergence of a “core–periphery” hierarchy, in which core ports like Hong Kong and Guangzhou radiate connections to secondary ports, facilitating efficient cargo flows and reducing redundant routes. The network also exhibits negative transitivity, consistent with practical shipping strategies that prioritize direct routes to minimize multi-hop transit time and handling costs. Node attribute analysis indicates that ports with similar shares of international cargo are more likely to cooperate, while throughput alone does not significantly influence edge formation. Geographic proximity and international partnerships further reinforce collaborative ties, demonstrating that spatial and strategic factors jointly shape network resilience. The dual mechanisms of route optimization and port cooperation are central to enhancing network robustness. By reducing the vulnerability of multi-hop transportation and fostering reciprocal cooperation between core and secondary ports, the network establishes multi-level redundant paths, improving its capacity to withstand systemic risks. These findings provide scientific guidance for port management, route optimization, and regional emergency recovery planning, emphasizing the importance of prioritizing and rapidly restoring core ports, optimizing shipping routes, and strengthening cooperative frameworks to build adaptive and resilient maritime systems. Such insights are particularly valuable for responding to global trade fluctuations, natural disasters, and operational disruptions. Overall, the study not only elucidates the structural and functional dynamics of the GBA shipping network but also establishes a transferable analytical framework applicable to other regional and global shipping systems.