AI Generated Image Detection Endpoint

This endpoint is tailored for developers who need to implement automated verification of AI-generated images using advanced detection algorithms.

It allows you to submit images for analysis based on the settings configured in your dashboard, including detection sensitivity and specific content categories to flag or ignore. The AI model will evaluate each image and return a structured response indicating the likelihood of AI generation.

This endpoint enables you to:

Analyze single or multiple images for AI-generated content in a single request
Adjust detection sensitivity and content categories through dashboard settings
Receive analysis results in JSON format by specifying the desired response format in the endpoint URL
Identify detected content types such as deepfakes, synthetic images, and manipulated media
Filter results based on predefined categories (e.g., synthetic, manipulated, AI-generated)
Automatically delete the processed images after analysis to maintain data integrity and privacy

Data Privacy and Security

We strictly comply with European data protection standards, ensuring that all submitted images are not shared, sold, or accessible to third parties. Upon completing the analysis, all uploaded content is immediately and permanently removed from our servers, adhering to the highest standards of data security and user privacy.

Image Scan Request

Here’s a sample request to perform an AI-generated image detection scan:

POSTAPI key required

								https://api.nudescan.io/v1/scan/ai/image

									
curl -X POST https://api.nudescan.io/v1/scan/ai/image \
     -H "Authorization: Bearer YOUR_API_KEY" \
     -H "Transfer-Encoding: chunked" \
     -F "files=@/path/to/photo1.jpg;type=application/octet-stream" \
     -F "files=@/path/to/photo2.jpg;type=application/octet-stream"

									
const axios = require('axios');
const fs    = require('fs');
const FormData = require('form-data');

// Define the API endpoint
const apiUrl = 'https://api.nudescan.io/v1/scan/ai/image';

// Define the function to make the POST request
async function sendPostRequest(photoFiles) {

    try {
        const form = new FormData();

        // Add all files as "files"
        photoFiles.forEach((photo) => {
            form.append('files', fs.createReadStream(photo.path), {
                filename: photo.filename,
                contentType: 'application/octet-stream', // Specify the content type
                Authorization: 'Bearer YOUR_API_KEY' // Add the API key as a Bearer token
            });
        });

        const response = await axios.post(apiUrl, form, {
            headers: {
                ...form.getHeaders()
            }
        });

        const { results } = response.data;

        // Update the photoFiles with the 'abuse' value
        return photoFiles.map((photo, index) => {
            return { ...photo, abuse: results[index] };
        });

    } catch (error) {
        console.error('Error sending photos for classification:', error.message);
        throw error;
    }
}

// Call the function
sendPostRequest();

									
<?php

// API URL
$apiUrl = 'https://api.nudescan.io/v1/scan/ai/image';
$apiKey = 'YOUR_API_KEY';

// Funktion zum Senden des POST-Requests
function sendPostRequest(array $photoFiles) {
    global $apiUrl, $apiKey;

    $curl = curl_init();
    $boundary = uniqid();
    $delimiter = '-------------' . $boundary;
    $eol = "\r\n";

    $headers = [
        "Authorization: Bearer $apiKey",
        "Content-Type: multipart/form-data; boundary=" . $delimiter
    ];

    $body = '';

    foreach ($photoFiles as $index => $photo) {
        $filePath = $photo['path'];
        $filename = $photo['filename'];

        if (file_exists($filePath)) {
            $fileContents = file_get_contents($filePath);

            $body .= "--" . $delimiter . $eol;
            $body .= 'Content-Disposition: form-data; name="files[]"; filename="' . $filename . '"' . $eol;
            $body .= 'Content-Type: application/octet-stream' . $eol . $eol;
            $body .= $fileContents . $eol;
        }
    }

    $body .= "--" . $delimiter . "--" . $eol;

    curl_setopt_array($curl, [
        CURLOPT_URL => $apiUrl,
        CURLOPT_RETURNTRANSFER => true,
        CURLOPT_POST => true,
        CURLOPT_HTTPHEADER => $headers,
        CURLOPT_POSTFIELDS => $body
    ]);

    $response = curl_exec($curl);
    $httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);

    if ($httpCode !== 200) {
        echo "Error sending photos for classification: " . curl_error($curl) . PHP_EOL;
        curl_close($curl);
        return false;
    }

    curl_close($curl);

    $responseData = json_decode($response, true);

    if (isset($responseData['results'])) {
        foreach ($photoFiles as $index => &$photo) {
            $photo['abuse'] = $responseData['results'][$index] ?? null;
        }
    }

    return $photoFiles;
}

// Beispielaufruf
$photos = [
    ['path' => 'path/to/photo1.jpg', 'filename' => 'photo1.jpg'],
    ['path' => 'path/to/photo2.jpg', 'filename' => 'photo2.jpg']
];

$result = sendPostRequest($photos);
print_r($result);

										
import requests

# API URL
api_url = "https://api.nudescan.io/v1/scan/ai/image"
api_key = "YOUR_API_KEY"

def send_post_request(photo_files):
    headers = {
        "Authorization": f"Bearer {api_key}"
    }

    files = [
        ('files', (photo['filename'], open(photo['path'], 'rb'), 'application/octet-stream'))
        for photo in photo_files
    ]

    try:
        response = requests.post(api_url, headers=headers, files=files)
        response.raise_for_status()

        response_data = response.json()

        # Update photo_files with 'abuse' values
        if 'results' in response_data:
            for index, photo in enumerate(photo_files):
                photo['abuse'] = response_data['results'][index] if index < len(response_data['results']) else None

        return photo_files

    except requests.RequestException as e:
        print(f"Error sending photos for classification: {e}")
        raise

# Beispielaufruf
photos = [
    {'path': 'path/to/photo1.jpg', 'filename': 'photo1.jpg'},
    {'path': 'path/to/photo2.jpg', 'filename': 'photo2.jpg'}
]

result = send_post_request(photos)
print(result)

Parameters

files (object) Max 25 files Max 15 MB / File REQUIRED

The file added to FormData is an object representing a file or binary data, typically consisting of properties like name, type, and size.

Response

The API returns a JSON array containing the results of the submitted images.

								
[
  {
    "isAi": true
  }
]

Response Fields

isAi (boolean)

A boolean flag indicating whether any detected category's score has exceeded the predefined AI generation threshold.

Error Responses

Status Code	Description
401	Not authorized - Invalid or missing API key
403	Forbidden - You don’t have permission
404	Not Found - Account or user not found
500	Internal Server Error - An unexpected error occurred
512	Parameter error - Check your sent data