Install
$ agentstack add skill-didit-protocol-skills-didit-liveness-detection ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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:
- Register:
POST https://apx.didit.me/auth/v2/programmatic/register/with{"email": "you@gmail.com", "password": "MyStr0ng!Pass"} - Check email for a 6-character OTP code
- Verify:
POST https://apx.didit.me/auth/v2/programmatic/verify-email/with{"email": "you@gmail.com", "code": "A3K9F2"}→ response includesapi_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
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"},
)
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)
{
"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
export DIDIT_API_KEY="your_api_key"
python scripts/check_liveness.py selfie.jpg
python scripts/check_liveness.py selfie.jpg --threshold 80
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: didit-protocol
- Source: didit-protocol/skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.