Biometrics recognition has been widely adopted for authentication, such as face, iris, palmprint, palm vein, dorsal hand vein, and fingerprint. Compared with other biometric traits, palmprint has stable and rich line features such as principal lines, wrinkles, textures, and local direction features. Similar to palmprint, dorsal hand vein also has stable characteristics that do not change with age, which can effectively protect against spoofing attacks and impersonation. Recently, hyperspectral imaging technology has attracted more and more considerable research attention. If hyperspectral technology can be utilized in both palmprint and dorsal hand vein imaging, more discriminative and robust information from the palmprint and dorsal hand vein such as the skin, veins, vessels, etc., can be captured in order to improve the recognition performance. In this work, we designed a novel near-infrared (NIR) based multimodal hyperspectral palmprint and dorsal hand vein authentication system. Based on the designed system, we constructed a hyperspectral palmprint and dorsal hand vein dataset to verify the performance. The results demonstrated the effectiveness of the proposed system as a real-world biometric security authentication application.