SpoofSense Face is a facial liveness detection solution that uses AI-based 3D passive detection to determine whether a face presented during an authentication or identity verification process is real or a spoofing attempt. The system captures a single image frame from a camera input (mobile, desktop, or webcam), analyzes it using AI algorithms for signs of liveness, and delivers a real/spoof decision in under 2 seconds — without requiring active user interaction such as blinking or head turning. Attack Coverage: - 3D masks: Detects hyper-realistic masks made from silicone, latex, resin, or wax - Digital replays: Detects pre-recorded video playback on device screens - Printed/2D masks: Detects flat printed images used to mimic a real face Accuracy & Fairness: - Ultra-low False Rejection Rate (FRR) to minimize friction for legitimate users - Trained across diverse skin tones, genders, and ethnicities - Functions across varying lighting conditions (low light to bright outdoors) - Handles variations in facial expressions, angles, and natural movement Compliance: - iBeta Level-1 and Level-2 compliant - ISO/IEC 30107-3 certified for Presentation Attack Detection (PAD) Deployment Options: - Plug-and-play REST API integration - Cross-device compatible (mobile, desktop, webcam) - On-premises deployment via Docker