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CaptchaFox Image Solving

Solve CaptchaFox image challenges with AI-powered recognition. CaptchaFox provides modern CAPTCHA solutions with 99.5% accuracy.

What is CaptchaFox Image?

CaptchaFox is a modern anti-bot solution that offers various challenge types including image grids, object selection, and sliding puzzles. It provides both visual and interactive challenges to verify human users. Our API supports all CaptchaFox challenge types automatically.

Captcha Type

Use the following captcha type identifier in your API requests: 

"type": "CAPTCHAFOX_IMAGE"

Request Format

POST /createTask

Request Parameters

Parameter Type Required Description
auth.token string required Your API key
captcha.type string required Must be "CAPTCHAFOX_IMAGE"
captcha.metadata.siteUrl string required URL where captcha appears
captcha.payload.images array required Array of base64-encoded images
captcha.payload.question string required The question text
captcha.payload.questionType string optional "grid", "click", "drag", or "slide"
captcha.payload.referenceImages array optional Reference images for comparison

Example Request

JavaScript 
const response = await fetch('https://solver-api.mydisct.com/createTask', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'apikey': 'YOUR_API_KEY'
  },
  body: JSON.stringify({
    auth: { token: 'YOUR_API_KEY' },
    context: { source: 'api', version: '1.0.0' },
    captcha: {
      type: 'CAPTCHAFOX_IMAGE',
      metadata: {
        siteUrl: 'https://example.com'
      },
      payload: {
        images: ['base64_image_1', 'base64_image_2'],
        question: 'Select all images with cars',
        questionType: 'grid',
        referenceImages: []
      }
    }
  })
});

const data = await response.json();
console.log('Task ID:', data.task.id);

Python Example

Python 
import requests
import time

def solve_captchafox_image(images, question, site_url, api_key, question_type='grid', reference_images=None):
    """
    Solve CaptchaFox image challenge

    Args:
        images: List of base64-encoded images
        question: Question text
        site_url: URL where captcha appears
        api_key: Your MyDisct Solver API key
        question_type: Challenge type (grid, click, drag, slide)
        reference_images: Optional reference images

    Returns:
        List of selected indices or coordinates
    """

    # Step 1: Create task
    create_response = requests.post(
        'https://solver-api.mydisct.com/createTask',
        headers={
            'Content-Type': 'application/json',
            'apikey': api_key
        },
        json={
            'auth': {'token': api_key},
            'context': {'source': 'api', 'version': '1.0.0'},
            'captcha': {
                'type': 'CAPTCHAFOX_IMAGE',
                'metadata': {'siteUrl': site_url},
                'payload': {
                    'images': images,
                    'question': question,
                    'questionType': question_type,
                    'referenceImages': reference_images or []
                }
            }
        }
    )

    create_data = create_response.json()

    if not create_data['success']:
        raise Exception(create_data['error']['message'])

    task_id = create_data['task']['id']

    # Step 2: Poll for result
    while True:
        time.sleep(3)

        result_response = requests.post(
            'https://solver-api.mydisct.com/fetchResult',
            headers={
                'Content-Type': 'application/json',
                'apikey': api_key
            },
            json={'taskId': task_id}
        )

        result_data = result_response.json()

        if result_data['task']['status'] == 'completed':
            return result_data['task']['result']['answers']
        elif result_data['task']['status'] == 'failed':
            raise Exception('CaptchaFox solving failed')

# Usage
solution = solve_captchafox_image(
    images=['base64_image_1', 'base64_image_2'],
    question='Select all images with cars',
    site_url='https://example.com',
    api_key='YOUR_API_KEY',
    question_type='grid'
)
print(f'Solution: {solution}')

Response Format

Create Task Response

JSON 
{
  "success": true,
  "service": "MyDisct Solver",
  "message": "Captcha is being processed",
  "task": {
    "id": "MyDisctSolver_abc123def456",
    "status": "processing"
  }
}

Fetch Result Response (Processing)

JSON 
{
  "success": true,
  "service": "MyDisct Solver",
  "message": "Captcha is being processed",
  "task": {
    "id": "MyDisctSolver_abc123def456",
    "status": "processing"
  }
}

Fetch Result Response (Completed)

JSON 
{
  "success": true,
  "service": "MyDisct Solver",
  "message": "Captcha solved successfully",
  "task": {
    "id": "MyDisctSolver_abc123def456",
    "status": "completed",
    "result": {
      "answers": [0, 2, 5, 7],
      "timestamp": "2025-11-05T12:34:56.789Z"
    }
  }
}
Understanding the Response

The answers array contains the indices of images that should be selected for grid challenges, or coordinates for click/drag challenges. Indices start from 0 (top-left) for grid layouts.

Best Practices

Recommendations
  • Include the exact question text as displayed
  • Specify the correct questionType for better accuracy
  • Use high-quality images without compression
  • Include reference images when available for click challenges
  • Poll every 3 seconds for results

Common Issues

Issue: Wrong questionType specified

Solution: Ensure you specify the correct questionType (grid, click, drag, or slide) to get accurate results.

Issue: Missing reference images

Solution: For click challenges, include all reference images shown above the main image grid.

Issue: Low accuracy on complex challenges

Solution: CaptchaFox challenges can be complex. Ensure images are captured at full resolution and question text is exact.