flutter_liveness_detection is a powerful, free, and open-source Flutter plugin that provides real-time face liveness detection using the device’s front camera. It is designed to be easy to integrate and highly SEO-optimized to appear in searches for: free liveness detection, face verification, KYC, and biometric security.
This plugin is a complete, free face module for your app's security, ensuring the user is a live human being, not a spoofed image or video.
- 100% Free & Open-Source: No hidden costs, subscription fees, or API limits. A truly free liveness face detection solution.
- Real-Time Liveness: Validates the presence of a live human by detecting natural facial movements.
- High Security: Prevents common spoofing attempts (photos, videos) for robust face authentication.
- 👁️ Eye Blinking: Confirms conscious action.
- 😄 Smiling: A unique, non-spoofable expression.
- 🔄 Head Movement (Left and Right): Ensures 3D presence in the frame.
Ideal for: KYC (Know Your Customer) processes, biometric login, secure attendance systems, and any application requiring face-based identity verification.
The best face module for your Flutter application, covering all security essentials:
| Feature | Description | Benefits |
|---|---|---|
| Free Solution | A complete, no-cost liveness detection tool. | free liveness detection, free face module, open-source face detection |
| Liveness Check | Detects human expressions to confirm life. | real-time liveness, face liveness detection, anti-spoofing |
| Multiple Actions | Supports smile, blink, and head movement. | biometric face check, face verification, face authentication |
| Cross-Platform | Works flawlessly on both major mobile platforms. | flutter face detection, android liveness, ios liveness |
| Easy Integration | Quick setup with minimal code changes. | flutter kyc, flutter biometric security |
| Selfie Capture | Returns a secure selfie upon successful verification. | secure selfie capture, face snapshot |
Add the package to your pubspec.yaml file:
dependencies:
flutter_liveness_detection: ^1.0.0