/api/v1/liveness/checkProtect your platform from spoofing attacks. Our multi-model liveness engine detects paper photos, screen replays, 3D masks, and deepfakes with sub-second response times.
REQUEST
curl -X POST https://api.faceguard.io/api/v1/liveness/check \ -H "X-API-Key: fg_live_your_key_here" \ -F "file=@face.jpg"
{
"is_live": true,
"confidence": 0.97,
"spoof_type": null,
"models": {
"onnx": { "is_live": true, "score": 0.96 },
"deepface": { "is_live": true, "score": 0.98 }
},
"processing_time_ms": 420
}Everything you need from a production-ready Liveness Detection API.
Combines ONNX MiniFASNet and DeepFace models with majority voting for maximum accuracy.
Optimised for real-time use cases — average response under 800ms on standard images.
Identifies whether a spoof is a photo, screen replay, or 3D mask.
Every result includes a confidence score so you can tune your own acceptance threshold.
Integrate in minutes with our developer-friendly REST API.
POST a face image (JPG, PNG) to the liveness endpoint with your API key.
Two independent models analyse the image for texture, depth, and reflection cues.
Receive a live/spoof verdict with a confidence score in under a second.
Data Output
All data returned as structured JSON — map directly to your database schema.
is_liveconfidencespoof_typemodels.onnxmodels.deepfaceprocessing_time_ms{
"is_live": true,
"confidence": 0.97,
"spoof_type": null,
"models": {
"onnx": { "is_live": true, "score": 0.96 },
"deepface": { "is_live": true, "score": 0.98 }
},
"processing_time_ms": 420
}Create a free account. Get 50 test API requests instantly — no credit card required.