Binimise Biometric SDK
A fully offline, zero-latency Flutter SDK for Android & iOS. Eliminate identity fraud, proxy check-ins, and liveness bypass attacks. Our advanced passive 3D face liveness detection cannot be bypassed using iPhone Live Photos, 3D printed frames, or video screen playbacks, keeping verification 100% secure.
Bypass-Proof 3D Liveness
Verify user presence in < 300ms. Blocks advanced bypass tricks like iPhone Live Photos, screen replays, and 3D frames.
Offline Face Matching
Extract 512-dimension face vectors and run 1:1 or 1:N templates match locally in < 1ms.
Bypass-Proof Passive Liveness Protection
Rejects identity spoofing attempts silently in under 300ms. Ordinary liveness systems can be easily bypassed using iPhone Live Photos, 3D printed frames, or screen playbacks. Binimise uses deep passive 3D analysis to detect real human depth, rendering it fully un-bypassable.
Local Face Identification
Our 1:N face matching engine extracts 512-dimension vectors to map unique landmarks. Matches check-ins offline in under 1ms, eliminating proxy entries and streamlining workforce rosters.
Single-Camera Verification Journey
Maximize flow rates and minimize user drop-offs. The SDK performs both face classification and passive liveness checks within the same camera frame session—eliminating double prompts or secondary actions.
- Zero User Action: No voice requests or facial movement prompts required.
- Flexible Orientation: Detects targets under extreme head tilts, low lighting, and glasses.
Platform Support & Specs
Lightweight binaries built for cross-platform mobile frameworks.
| Platform | Support | Minimum Version | Architectures / Targets |
|---|---|---|---|
| Android | âś… Supported | API 24+ (Android 7.0) | arm64-v8a, armeabi-v7a, x86_64 |
| iOS | âś… Supported | iOS 14.0+ | Physical Devices (arm64) & Simulators (arm64, x86_64) |
Advanced Anti-Spoofing & Liveness Detection
Ensure absolute identity integrity with offline, multi-layered spoof protection. Our technology halts presentation attacks and compromised devices at the edge.
Video Playback Prevention
Blocks all high-quality recorded video attacks.
3D Frame & Silicone Mask Prevention
Detects advanced physical spoofs like 3D printed frames, paper cutouts, and silicone face masks that attempt to simulate 3D facial depth.
Bypass-Proof Live Photo & Screen Defense
Blocks bypass attacks using Apple Live Photos, high-definition video playbacks, and 4K/8K monitors that typically trick standard liveness models.
Rooted Device Blocking
Automatically restricts access from rooted or compromised devices to ensure maximum security.
Advanced Depth Mapping
Projects 50,000 data points onto the face for ultra-secure, precision 3D biometric authentication.
Unified Pipeline
On-Device Processing Pipeline
In-app video frame processing that finishes locally in milliseconds.
Frame Capture
The SDK opens the front camera and streams raw video frames locally inside the container widget.
Edge AI Inference
Lightweight, encrypted TFLite neural networks detect faces, analyze passive 3D depth landmarks, and check spoof features.
Biometric Vector Validation
Matches the face against the local enrolled template hash. Emits clean matching scores and results immediately.