Injection Attack Detection: Stopping Deepfakes in Biometric Verification

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In 2026, biometric verification systems must address both presentation and injection attacks, with advancements in deepfake technology and virtual camera software making both threat classes prominent. Presentation attacks involve presenting a false artefact, such as a photo or mask, in front of a camera, while injection attacks bypass the camera by inserting synthetic video streams directly into the software pipeline, posing a significant challenge. Didit employs a comprehensive defense strategy against these threats by combining Presentation Attack Detection (PAD) certified liveness with over 200 fraud signals per session, including device and session integrity checks to detect virtual camera injections. While Didit's PAD is certified at iBeta Level 1 for presentation attacks, injection defense relies on analyzing various signals to identify anomalies indicative of fraud. The system's effectiveness is crucial for sectors like crypto exchanges, fintech, iGaming, and high-value re-authentication, where both attack types are prevalent and could lead to significant security breaches.

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