This paper focuses on Chinese Overprotective and Derogatory Language (CPCL), a type of implicitly discriminatory and harmful language targeting vulnerable groups on Chinese video platforms. To address the lack of existing datasets, which cannot accurately understand video content and fail to detect some CPCL videos, we build a new dataset, PCLMMPLUS, containing 103,000 comment entries, and propose the CPCLDetector model, which features alignment selection and knowledge-enhanced comment content modules. Experimental results show that the proposed CPCLDetector outperforms existing state-of-the-art (SOTA) performance and achieves higher performance on PCLMMPLUS, contributing to content moderation and the protection of vulnerable groups by more accurately detecting CPCL videos. The code and dataset are available on GitHub.