Composite materials, due to their advantages such as high strength, low weight, and corrosion resistance, are widely used in various industries, including aerospace, construction, and marine. However, during the production or use of composite materials, it is inevitable that they may suffer damage and degradation, leading to a decrease in material performance and potential safety hazards. Therefore, researching non-destructive testing (NDT) methods to detect the types and extents of damage inside the materials has become a hot topic in recent years. The advantage of Terahertz (THz) technology lies in its sensitivity to the chemical composition and crystal structure of materials. Detailed information about the internal conditions of materials, such as defect types, sizes, and distributions, can be obtained by analyzing the frequency spectrum and phase information of THz waves. This is crucial for quality control and performance assessment of composite materials. First, this paper outlines the basic principles of composite materials, which commonly use NDT and THz techniques. Secondly, it categorizes the defects such as delamination, inclusions, porosity, impact damage, thermal damage, etc., which occur during the manufacturing or use of composite materials and focuses on applying THz technology in detecting different defect types. Then the challenges faced by THz technology in composite defect detection are summarized, including the limited resolution of THz imaging, which makes it difficult to provide sufficient detailed information, the non-uniformity of composite structure that leads to the complexity and variety of THz wave propagation inside the composite material, and the existing defect identification techniques and equipment, which limit the application of THz in composite defect detection; Finally, an outlook on the future development direction is given, which includes improving the imaging system to increase the THz imaging resolution while reducing the detection time, combining artificial intelligence and deep learning techniques to improve the fast and accurate identification of different types of defects, improving the real-time data processing to achieve online inspection of composites, and optimizing the composite defect detection platform. These development directions will further promote the application of THz technology in composite materials, improve detection efficiency and accuracy, and promote the development of composite material manufacturing and application.