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Liveness detection remains the default defense for most IDV systems, but attackers now bypass it at every stage of the pipeline. Organizations rely on motion-based PAD, challenge-replay protocols, and biometric matching without realizing these methods collapse under real-world spoofing conditions. Despite this, many vendors still claim "liveness detection" as sufficient protection. We created this report to expose the evidence behind liveness failures and demonstrate why forensic analysis, multi-modal biometrics, and adaptive models are required to outpace adversaries.
This brief includes the full biometric attack flow diagram, documented bypass evidence from cross-database and motion-based PAD testing, forensic advantage breakdowns for pixel-level analysis and GAN fingerprinting, and engineering burden calculations for retraining costs and adversarial ensembles. Access the technical framework for evaluating liveness vulnerabilities and implementing multi-modal defenses.
