Didit Passive Liveness API

Overview

Verifies that a user is physically present by analyzing a single captured image — no explicit movement or interaction required.

Key constraints:

• Supported formats: JPEG, PNG, WebP, TIFF
• Maximum file size: 5MB
• Image must contain exactly one clearly visible face
• Original real-time photo only (no screenshots or printed photos)

Accuracy: 99.9% liveness detection accuracy, <0.1% false acceptance rate (FAR).

Capabilities: Liveness scoring, face quality assessment, luminance analysis, age/gender estimation, spoof detection (screen captures, printed copies, masks, deepfakes), duplicate face detection across sessions, blocklist matching.

Liveness methods: This standalone endpoint uses PASSIVE method (single-frame CNN). Workflow mode also supports ACTIVE_3D (action + flash, highest security) and FLASHING (3D flash, high security).

API Reference: https://docs.didit.me/standalone-apis/passive-liveness Feature Guide: https://docs.didit.me/core-technology/liveness/overview

Authentication

All requests require x-api-key header. Get your key from Didit Business Console → API & Webhooks, or via programmatic registration (see below).

Getting Started (No Account Yet?)

If you don't have a Didit API key, create one in 2 API calls:

1. Register: POST https://apx.didit.me/auth/v2/programmatic/register/ with {"email": "you@gmail.com", "password": "MyStr0ng!Pass"}
2. Check email for a 6-character OTP code
3. Verify: POST https://apx.didit.me/auth/v2/programmatic/verify-email/ with {"email": "you@gmail.com", "code": "A3K9F2"} → response includes api_key

To add credits: GET /v3/billing/balance/ to check, POST /v3/billing/top-up/ with {"amount_in_dollars": 50} for a Stripe checkout link.

See the didit-verification-management skill for full platform management (workflows, sessions, users, billing).

Endpoint

POST https://verification.didit.me/v3/passive-liveness/

Headers

| Header | Value | Required | |---|---|---| | x-api-key | Your API key | Yes | | Content-Type | multipart/form-data | Yes |

Request Parameters (multipart/form-data)

| Parameter | Type | Required | Default | Constraints | Description | |---|---|---|---|---|---| | user_image | file | Yes | — | JPEG/PNG/WebP/TIFF, max 5MB | User's face image | | face_liveness_score_decline_threshold | integer | No | — | 0-100 | Scores below this = Declined | | rotate_image | boolean | No | — | — | Try rotations to find upright face | | save_api_request | boolean | No | true | — | Save in Business Console | | vendor_data | string | No | — | — | Your identifier for session tracking |

Example

python
import requests

response = requests.post(
    "https://verification.didit.me/v3/passive-liveness/",
    headers={"x-api-key": "YOUR_API_KEY"},
    files={"user_image": ("selfie.jpg", open("selfie.jpg", "rb"), "image/jpeg")},
    data={"face_liveness_score_decline_threshold": "80"},
)

typescript
const formData = new FormData();
formData.append("user_image", selfieFile);
formData.append("face_liveness_score_decline_threshold", "80");

const response = await fetch("https://verification.didit.me/v3/passive-liveness/", {
  method: "POST",
  headers: { "x-api-key": "YOUR_API_KEY" },
  body: formData,
});

Response (200 OK)

json
{
  "request_id": "a1b2c3d4-...",
  "liveness": {
    "status": "Approved",
    "method": "PASSIVE",
    "score": 95,
    "user_image": {
      "entities": [
        {"age": 22.16, "bbox": [156, 234, 679, 898], "confidence": 0.717, "gender": "male"}
      ],
      "best_angle": 0
    },
    "warnings": [],
    "face_quality": 85.0,
    "face_luminance": 50.0
  },
  "created_at": "2025-05-01T13:11:07.977806Z"
}

Status Values & Handling

| Status | Meaning | Action | |---|---|---| | "Approved" | User is physically present | Proceed with your flow | | "Declined" | Liveness check failed | Check warnings. May be a spoof or poor image quality |

Error Responses

| Code | Meaning | Action | |---|---|---| | 400 | Invalid request | Check file format, size, parameters | | 401 | Invalid API key | Verify x-api-key header | | 403 | Insufficient credits | Top up at business.didit.me |

Response Field Reference

| Field | Type | Description | |---|---|---| | status | string | "Approved" or "Declined" | | method | string | Always "PASSIVE" for this endpoint | | score | integer | 0-100 liveness confidence (higher = more likely real). null if no face | | face_quality | float | 0-100 face image quality score. null if no face | | face_luminance | float | Face luminance value. null if no face | | entities[].age | float | Estimated age | | entities[].bbox | array | Face bounding box [x1, y1, x2, y2] | | entities[].confidence | float | Face detection confidence (0-1) | | entities[].gender | string | "male" or "female" | | warnings | array | {risk, log_type, short_description, long_description} |

Warning Tags

Auto-Decline (always)

| Tag | Description | |---|---| | NO_FACE_DETECTED | No face detected in image | | LIVENESS_FACE_ATTACK | Potential spoofing attempt (printed photo, screen, mask) | | FACE_IN_BLOCKLIST | Face matches a blocklisted entry | | POSSIBLE_FACE_IN_BLOCKLIST | Possible blocklist match detected |

Configurable (Decline / Review / Approve)

| Tag | Description | Notes | |---|---|---| | LOW_LIVENESS_SCORE | Score below threshold | Configurable review + decline thresholds | | DUPLICATED_FACE | Matches another approved session | — | | POSSIBLE_DUPLICATED_FACE | May match another user | Configurable similarity threshold | | MULTIPLE_FACES_DETECTED | Multiple faces (largest used for scoring) | Passive only | | LOW_FACE_QUALITY | Image quality below threshold | Passive only | | LOW_FACE_LUMINANCE | Image too dark | Passive only | | HIGH_FACE_LUMINANCE | Image too bright/overexposed | Passive only |

Common Workflows

Basic Liveness Check

1. Capture user selfie
2. POST /v3/passive-liveness/ → {"user_image": selfie}
3. If "Approved" → user is real, proceed
   If "Declined" → check warnings:
     - NO_FACE_DETECTED → ask user to retake with face clearly visible
     - LOW_FACE_QUALITY → ask for better lighting/positioning
     - LIVENESS_FACE_ATTACK → flag as potential fraud

Liveness + Face Match (combined)

1. POST /v3/passive-liveness/ → verify user is real
2. If Approved → POST /v3/face-match/ → compare selfie to ID photo
3. Both Approved → identity verified

Utility Scripts

bash
export DIDIT_API_KEY="your_api_key"

python scripts/check_liveness.py selfie.jpg
python scripts/check_liveness.py selfie.jpg --threshold 80