Liveness

Fast, convenient, and accurate liveness detection

Veriff’s Liveness solution uses AI and biometric facial analysis to verify a user with a quick selfie image. It is fast and user-friendly, and gives you confidence that spoofs or deepfakes are detected and prevented.

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Ensure your remote users are real people

Veriff’s AI-powered biometric liveness solution makes it quick and efficient to verify that remote users are real people, instantly. Our solution conforms with ISO/IEC 301070-3 for presentation attack detection.

Streamlined user experience

Passive liveness delivers a faster, smoother user experience. It eliminates the need to perform actions such as blinking, smiling, or nodding, enabling users to effortlessly verify they are real people.

Speed and scalability

Sub-second decisions ensure your users are never left waiting. Our proven scalability handles high-volume processing and operates globally.

Multi-layered detection

Our cutting-edge technology and integrated fraud signals detect and prevent even the most sophisticated threats. This includes streamed or pre-recorded videos, synthetic or manipulated images, and AI-generated deepfakes.

Accurate and reliable

Engineered to capture high-quality selfies in real-time, even in low light or motion blur. If necessary, Veriff’s Assisted Image Capture steps in to guide users on how to take an optimal selfie.

How Veriff liveness works

Add Veriff Liveness as part of onboarding or ongoing verification checks to make it quick and easy for genuine users to confirm they are real people. Protect against evolving threats such as deepfakes and injected media attacks.

Just a quick selfie is all it takes. Veriff’s real-time feedback provides instant guidance if needed, and with passive liveness users do not need to perform unnecessary actions.

Conducts real-time liveness detection of the user’s selfie, including image quality, behavioral, device and network risk signals to detect fraudulent activity. This enables you to approve genuine users with confidence.

Get clear, actionable results with detailed explanations of the events that occurred during the session. This empowers you to make an informed final decision—whether to allow or deny access, or request additional verification.

Passive liveness detection

Veriff validates that the user is real and present during the session without requiring the end user to complete any additional or unnatural actions. Our liveness models are capable of detecting spoof attempts such as presentation attacks using masks or presented screens, or an AI-generated selfie.

Video-based analysis

Optional background video recording enables advanced fraud prevention checks with minimal input from your users.

Presentation attack prevention

Our liveness solution conforms to ISO/IEC 30107-3 Level 1 and 2 Presentation Attack Detection (PAD) through independent testing by the NIST/NVLAP-accredited iBeta lab. This certification solidifes that Veriff’s solution meets the highest standard of biometric security with protection from spoofing methods such as printed photos, mask, or video screen.

Advanced deepfake and injected media detection

Multi-layered defense analyzes face, device, sensor, timestamp, and behavioral data to detects injected media such as via emulators, virtual camera, or other tampering techniques.

User-centred design

Our fully automated solution provides a response in under a second, enabling your users to verify themselves instantly with a simple selfie.

Assisted image capture

Veriff uses machine-learning technology to assess sessions in real-time and guide users during the photo capture process. Clear and actionable user feedback due to poor lighting, glare, and obstructed facial images are just a few examples of how Assisted Image Capture pre-validates images and boosts first-time pass rates.

Cross-platform

Users can capture a selfie on any device and platform of their choice that has a user-facing camera. Veriff supports iOS, Android™, mobile web, and web SDK or API.