Didit Id Verification
Verified@rosasalberto
npx machina-cli add skill @rosasalberto/didit-id-verification --openclawDidit ID Verification API
Overview
Verifies identity documents by submitting images of the front and back sides. Performs OCR extraction, MRZ parsing, authenticity checks, and document liveness detection.
Key constraints:
- Supported formats: JPEG, PNG, WebP, TIFF
- Maximum file size: 5MB per image
- All document corners must be visible, full-color, no glare/shadows
- Original real-time photos only (no screenshots, scans, or digital copies)
Coverage: 4,000+ document types, 220+ countries, 130+ languages. Supports passports, national ID cards, driver's licenses, and residence permits.
Processing pipeline:
- Intelligent capture & document type detection
- OCR text extraction + MRZ/barcode parsing
- Template matching, security feature validation, tamper detection
- Document liveness (detects screen captures, printed copies, portrait manipulation)
API Reference: https://docs.didit.me/reference/id-verification-standalone-api
Authentication
All requests require x-api-key header. Get your key from Didit Business Console → API & Webhooks.
Endpoint
POST https://verification.didit.me/v3/id-verification/
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 |
|---|---|---|---|---|---|
front_image | file | Yes | — | JPEG/PNG/WebP/TIFF, max 5MB | Front image of ID document |
back_image | file | No | — | Same as above | Back image (when applicable) |
save_api_request | boolean | No | true | — | Save in Business Console Manual Checks |
vendor_data | string | No | — | — | Your identifier for session tracking |
Example
import requests
response = requests.post(
"https://verification.didit.me/v3/id-verification/",
headers={"x-api-key": "YOUR_API_KEY"},
files={
"front_image": ("front.jpg", open("front.jpg", "rb"), "image/jpeg"),
"back_image": ("back.jpg", open("back.jpg", "rb"), "image/jpeg"),
},
data={"vendor_data": "user-123"},
)
const formData = new FormData();
formData.append("front_image", frontImageFile);
formData.append("back_image", backImageFile);
formData.append("vendor_data", "user-123");
const response = await fetch("https://verification.didit.me/v3/id-verification/", {
method: "POST",
headers: { "x-api-key": "YOUR_API_KEY" },
body: formData,
});
Response (200 OK)
{
"request_id": "a1b2c3d4-...",
"id_verification": {
"status": "Approved",
"document_type": "Identity Card",
"document_number": "YZA123456",
"personal_number": "X9876543L",
"first_name": "Elena",
"last_name": "Martínez Sánchez",
"full_name": "Elena Martínez Sánchez",
"date_of_birth": "1985-03-15",
"age": 40,
"gender": "F",
"nationality": "ESP",
"issuing_state": "ESP",
"issuing_state_name": "Spain",
"expiration_date": "2030-08-21",
"date_of_issue": "2020-08-21",
"address": "Calle Mayor 10, Madrid",
"formatted_address": "Calle Mayor 10, 28013 Madrid, Spain",
"place_of_birth": "Valencia",
"portrait_image": "<base64>",
"front_document_image": "<base64>",
"back_document_image": "<base64>",
"mrz": {
"surname": "MARTINEZ SANCHEZ",
"given_name": "ELENA",
"document_type": "I",
"document_number": "YZA123456",
"country": "ESP",
"nationality": "ESP",
"birth_date": "850315",
"expiry_date": "300821",
"sex": "F"
},
"parsed_address": {"city": "Madrid", "region": "...", "postal_code": "28013", "country": "ES"},
"warnings": []
},
"created_at": "2025-05-01T13:11:07.977806Z"
}
Status Values
| Status | Meaning |
|---|---|
"Approved" | Document verified successfully |
"Declined" | Verification failed (see warnings) |
"In Review" | Requires manual review |
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", "Declined", "In Review" |
document_type | string | "Passport", "Identity Card", "Driver's License", "Residence Permit" |
document_number | string | Document ID number |
personal_number | string | Personal/national ID number |
first_name, last_name, full_name | string | Extracted name fields |
date_of_birth | string | YYYY-MM-DD |
age | integer | Calculated age |
gender | string | "M", "F", "U" |
nationality, issuing_state | string | ISO 3166-1 alpha-3 |
expiration_date, date_of_issue | string | YYYY-MM-DD |
portrait_image | string | Base64-encoded portrait from document |
mrz | object | Machine Readable Zone data |
parsed_address | object | Geocoded address: {city, region, postal_code, country, street_1} |
warnings | array | {risk, log_type, short_description, long_description} |
Warning Tags
Auto-Decline (always)
| Tag | Description |
|---|---|
ID_DOCUMENT_IN_BLOCKLIST | Document in blocklist (previously flagged) |
PORTRAIT_IMAGE_NOT_DETECTED | No portrait found on document |
DOCUMENT_EXPIRED | Document expiration date has passed |
DOCUMENT_NOT_SUPPORTED_FOR_APPLICATION | Document type not accepted |
Configurable (Decline / Review / Approve)
| Category | Tags |
|---|---|
| Document liveness | SCREEN_CAPTURE_DETECTED, PRINTED_COPY_DETECTED, PORTRAIT_MANIPULATION_DETECTED |
| MRZ issues | MRZ_NOT_DETECTED, MRZ_VALIDATION_FAILED, MRZ_AND_DATA_EXTRACTED_FROM_OCR_NOT_SAME |
| Data issues | NAME_NOT_DETECTED, DATE_OF_BIRTH_NOT_DETECTED, DOCUMENT_NUMBER_NOT_DETECTED, DATA_INCONSISTENT |
| Duplicates | POSSIBLE_DUPLICATED_USER |
| Expected mismatch | FULL_NAME_MISMATCH_WITH_PROVIDED, DOB_MISMATCH_WITH_PROVIDED, GENDER_MISMATCH_WITH_PROVIDED |
| Geolocation | DOCUMENT_COUNTRY_MISMATCH |
Common Workflows
Basic ID Verification
1. POST /v3/id-verification/ → front_image (+ back_image if applicable)
2. If "Approved" → extract first_name, last_name, date_of_birth, document_number
If "Declined" → check warnings:
DOCUMENT_EXPIRED → ask for valid document
SCREEN_CAPTURE_DETECTED → ask for real photo of physical document
MRZ_VALIDATION_FAILED → ask for clearer image
Full Identity Verification Pipeline
1. POST /v3/id-verification/ → verify document
2. POST /v3/passive-liveness/ → verify real person
3. POST /v3/face-match/ → compare selfie to document portrait
4. POST /v3/aml/ → screen extracted name/DOB/nationality
5. All Approved → fully verified identity
Utility Scripts
export DIDIT_API_KEY="your_api_key"
python scripts/verify_id.py front.jpg
python scripts/verify_id.py front.jpg back.jpg --vendor-data user-123
Overview
Didit ID Verification API validates identity documents by submitting front and back images, performing OCR extraction, MRZ parsing, authenticity checks, and document liveness detection. It supports 4,000+ document types across 220+ countries and 130+ languages, covering passports, national IDs, driver’s licenses, and residence permits.
How This Skill Works
The processing pipeline starts with intelligent capture and document type detection, followed by OCR text extraction and MRZ/barcode parsing. It then performs template matching, security feature validation, and tamper detection, and finally runs document liveness to detect screenshots, printed copies, or portrait manipulation.
When to Use It
- Onboarding new users in fintech or regulated apps that require strong identity verification (KYC).
- Verifying customer IDs for cross-border services, such as travel, banking, or remittance platforms.
- Processing residence permits or national IDs for housing, visa, or tenancy workflows.
- Automated document checks on gig economy platforms to ensure legitimate identity.
- Compliance workflows requiring document authenticity and liveness checks for high-risk accounts.
Quick Start
- Step 1: Obtain your API key from the Didit Business Console.
- Step 2: Send a multipart/form-data request with front_image (required), optional back_image, and vendor_data to https://verification.didit.me/v3/id-verification/ using the x-api-key header.
- Step 3: Process the 200 OK response and use the id_verification object for status, document_type, and personal details.
Best Practices
- Require and submit both front_image and back_image when applicable to improve accuracy.
- Ensure images meet constraints: JPEG/PNG/WebP/TIFF, max 5MB, full color, no glare or shadows, and visible corners.
- Capture real-time photos (not screenshots or scans) to avoid spoofed documents.
- Include vendor_data to help session tracking and audit trails in the Didit Console.
- Securely manage your x-api-key, test in a safe environment, and validate results before making decisions.
Example Use Cases
- A fintech onboarding flow uses Didit to verify a passport during account creation.
- A ride-hailing app confirms a Spanish driver's license for driver eligibility and background checks.
- A property rental platform verifies a residence permit to support international tenants.
- A crypto exchange performs KYC by validating a national ID with liveness checks.
- An airline uses Didit to verify passports and perform fraud checks during check-in.