IDLive Doc is a document liveness detection solution that analyzes identity documents in real time to determine whether they are physically present and genuine, or fraudulent reproductions. It is designed to prevent presentation attacks during digital identity verification and KYC onboarding workflows. The product uses AI-based passive image analysis to detect a range of document spoofing techniques without requiring any active user interaction. A single API call is sufficient to verify an already-captured document image, making it compatible with existing verification pipelines. IDLive Doc addresses the following attack types: - Screen replay attacks: detects IDs displayed on monitors, tablets, or phones - Printed copy attacks: identifies fake IDs produced by printing digital images, including cut-to-size paper counterfeits - Substitution/portrait attacks: detects altered portrait photos, overlays, swaps, and signs of physical forgery The solution is document-agnostic and does not rely on templates or document-specific training. It supports passports, national IDs, and driver's licenses globally. Input requirements include portrait or landscape images at FHD (1920×1080) resolution and JPEG compression in the 70–100 range. IDLive Doc is positioned as a complement to facial liveness detection, focusing specifically on the document rather than the individual presenting it. It reduces the need for manual review by replacing human judgment with automated AI-based detection.