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Legacy liveness detection validates behavior, not provenance, and injection attacks replace the camera stream itself. Device-based PAD assumes the video feed is genuine, but attackers now use virtual cameras, driver emulators, and signal-level manipulation that sits outside what PAD inspects. Despite this, many organizations underestimate how quickly synthetic identity fraud has escalated. We created this report to expose the fraud landscape, document why traditional liveness fails, and provide a defense framework that IDV providers can deploy to maintain trust and meet regulatory requirements.
This report includes the three-tier fraud landscape (generative AI, advanced presentation, sensor spoofing), operational and compliance risk breakdowns, case studies from KnowBe4 incident and dark web operations, defense strategy frameworks with forensic analysis and multimodal biometrics, regulatory response timelines for EU AI Act and U.S. statutes, and operational benchmarks for accuracy, speed, user experience, injection resilience, and auditability. Access the complete framework for protecting IDV systems against escalating synthetic identity fraud.





