The ability to detect spoofed faces has become a critical concern in various applications, such as face recognition systems, banking, and security measures. Thisresearchpresentsa simple system that can detect whether a facein video stream is spoofed or real using pre-trained models for face detection and anti-spoofing. The system uses a continuous loop to read each frame of the video stream, to assess whether a face image is real or spoof, first detect faces using the pre-trained face detection model, then crop and resize the face image. If the model predicts that the face is fake, the system draws a red rectangle around the face and displays the label "spoof." If the model predicts that the face is real, the system draws a green rectangle around the face and displays the label "real." The proposed system achieved a high accuracy rate in detecting spoofed faces, making it suitable for real-world applications.

Keywords : Facebiometric, liveness detection, Anti-spoofing, Fraud prevention, Face Spoofing detection, Convolutional neural networks.