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Didit Id Verification

Verified

@rosasalberto

npx machina-cli add skill @rosasalberto/didit-id-verification --openclaw
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Didit 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:

  1. Intelligent capture & document type detection
  2. OCR text extraction + MRZ/barcode parsing
  3. Template matching, security feature validation, tamper detection
  4. 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

HeaderValueRequired
x-api-keyYour API keyYes
Content-Typemultipart/form-dataYes

Request Parameters (multipart/form-data)

ParameterTypeRequiredDefaultConstraintsDescription
front_imagefileYesJPEG/PNG/WebP/TIFF, max 5MBFront image of ID document
back_imagefileNoSame as aboveBack image (when applicable)
save_api_requestbooleanNotrueSave in Business Console Manual Checks
vendor_datastringNoYour 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

StatusMeaning
"Approved"Document verified successfully
"Declined"Verification failed (see warnings)
"In Review"Requires manual review

Error Responses

CodeMeaningAction
400Invalid requestCheck file format, size, parameters
401Invalid API keyVerify x-api-key header
403Insufficient creditsTop up at business.didit.me

Response Field Reference

FieldTypeDescription
statusstring"Approved", "Declined", "In Review"
document_typestring"Passport", "Identity Card", "Driver's License", "Residence Permit"
document_numberstringDocument ID number
personal_numberstringPersonal/national ID number
first_name, last_name, full_namestringExtracted name fields
date_of_birthstringYYYY-MM-DD
ageintegerCalculated age
genderstring"M", "F", "U"
nationality, issuing_statestringISO 3166-1 alpha-3
expiration_date, date_of_issuestringYYYY-MM-DD
portrait_imagestringBase64-encoded portrait from document
mrzobjectMachine Readable Zone data
parsed_addressobjectGeocoded address: {city, region, postal_code, country, street_1}
warningsarray{risk, log_type, short_description, long_description}

Warning Tags

Auto-Decline (always)

TagDescription
ID_DOCUMENT_IN_BLOCKLISTDocument in blocklist (previously flagged)
PORTRAIT_IMAGE_NOT_DETECTEDNo portrait found on document
DOCUMENT_EXPIREDDocument expiration date has passed
DOCUMENT_NOT_SUPPORTED_FOR_APPLICATIONDocument type not accepted

Configurable (Decline / Review / Approve)

CategoryTags
Document livenessSCREEN_CAPTURE_DETECTED, PRINTED_COPY_DETECTED, PORTRAIT_MANIPULATION_DETECTED
MRZ issuesMRZ_NOT_DETECTED, MRZ_VALIDATION_FAILED, MRZ_AND_DATA_EXTRACTED_FROM_OCR_NOT_SAME
Data issuesNAME_NOT_DETECTED, DATE_OF_BIRTH_NOT_DETECTED, DOCUMENT_NUMBER_NOT_DETECTED, DATA_INCONSISTENT
DuplicatesPOSSIBLE_DUPLICATED_USER
Expected mismatchFULL_NAME_MISMATCH_WITH_PROVIDED, DOB_MISMATCH_WITH_PROVIDED, GENDER_MISMATCH_WITH_PROVIDED
GeolocationDOCUMENT_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

Source

git clone https://clawhub.ai/rosasalberto/didit-id-verificationView on GitHub

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

  1. Step 1: Obtain your API key from the Didit Business Console.
  2. 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.
  3. 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.

Frequently Asked Questions

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