High-definition (HD) map data plays a critical role in intelligent connected vehicle systems, yet existing regulatory frameworks often fail to address security risks across its full lifecycle. To bridge this gap, this paper introduces a Three-Stage End-to-End Security Regulatory Model tailored for vehicle-road-cloud integration scenarios. The model is structured around pre-event constraints, in-event monitoring, and post-event traceability, and incorporates a three-tier classification and grading system based on an “impact object–impact severity” evaluation mechanism. We leverage automated data element extraction alongside expert reviews to improve classification accuracy, and perform a comprehensive lifecycle risk assessment to inform targeted regulatory interventions. This work lays a theoretical and methodological foundation for achieving manageable, controllable, traceable, and preventable HD map data security. The proposed model offers a systematic path forward for secure map data governance, aligning technological capabilities with evolving security demands in intelligent mobility ecosystems.