Docs / AI Content Detection / AI-Generated Video Detection

AI-Generated Video Detection

genai

Detect if a video was generated with an AI model such as Sora, Veo, Runway, Pika and more.

This page describes AI video detection. AI image detection is also available.

Overview

The AI-Generated Video Detection Model can help you determine if a video was entirely generated by an AI model, or if it is a real video. This model was trained on millions of artificially-created and human-created videos spanning all sorts of content such as real life, art, cartoons and more.

The Model works by analyzing the visual (pixel) content of the video. No meta-data is used in the analysis. Tampering with meta-data such as EXIF data therefore has no effect on the scoring.

The Model was trained to detect videos created by the main generators currently in use: Veo, Sora, Runway, Pika, MidJourney, Kling... Additional generators will be added over time as they become available.

Use cases

Tag AI-generated videos as such, to limit the spread of misinformation and fake news
Implement stricter moderation rules on AI-generated videos
Detect potential fraud with fake video verifications
Limit AI-generated spam
Enact bans on AI-generated videos

Related model

For AI-image detection, you can use the AI-image detection model.

Generator-specific information

Sightengine's AI detection models compute per-generator confidence scores alongside a global AI probability score. For every image or video analyzed, the API response includes individual scores for each supported generator, giving you a complete fingerprint of the content.

The list of supported generators spans both images and videos, covering major commercial tools, open-source models, and older GAN-based architectures:

Video generators

Generator	Creator	Example versions detected
Higgsfield	Higgsfield AI	Higgsfield 1.0, Higgsfield Soul Cinema...
Kling	Kuaishou	Kling 1.0, Kling 1.5, ...
Midjourney	Midjourney	Midjourney Video, ...
Pika	Pika	Pika 1.0, Pika 1.5, ...
Runway	Runway	Gen-2, Gen-3, Gen-4...
Seedance	ByteDance	Seedance 1.5, Seedance 2.0, ...
Sora	OpenAI	Sora, Sora 2, ...
Veo	Google	Veo 1, Veo 2, Veo 3, ...
Wan	Alibaba	Wan 2.1, Wan 2.2, ...
Other generators	Various	Demamba, HotShot, LaVie, Hunyuan, Ray...

And more, new generators are added continuously as they appear in the wild.

Image generators

Generator	Creator	Example versions detected
DALL-E	OpenAI	DALL-E 2, DALL-E 3, ...
Firefly	Adobe	Firefly 2, Firefly 3, ...
Flux	Black Forest Labs	Flux.1 Dev, Flux.1 Schnell, Flux Pro, ...
GPT image generation	OpenAI	GPT-4o, GPT-1.5 image...
Grok Imagine	xAI	Imagine, Imagine Pro...
Higgsfield	Higgsfield AI	Higgsfield Soul...
Ideogram	Ideogram	Ideogram 2.0, Ideogram 3.0, ...
Imagen	Google	Imagen 2, Imagen 3, ...
Kling	Kuaishou	Kling 2.0, Kling 3.0, ...
Midjourney	Midjourney	Midjourney v5, v6, v7, ...
Nano Banana	Google	Nano Banana 2, Nano Banana Pro, ...
Qwen	Alibaba	Qwen2-VL, ...
Recraft	Recraft	Recraft V3, ...
Reve	Reve	Reve Image 1.0, ...
Seedream	ByteDance	Seedream 2.0, Seedream 3.0, ...
Stable Diffusion	Stability AI	SD 1.5, SD 2.1, SDXL, SD3, ...
StyleGAN	NVIDIA	StyleGAN2, StyleGAN3, ...
Z-image	Alibaba	Z-image, Z-image Turbo, ...
Other generators	Various	Generators with a smaller audience

And more, new generators are added continuously as they appear in the wild.

Use the model

If you haven't already, create an account to get your own API keys.

Detect if a video was AI-generated

Option 1: Short video

Here's how to proceed to analyze a short video (less than 1 minute):


curl -X POST 'https://api.sightengine.com/1.0/video/check-sync.json' \
  -F 'media=@/path/to/video.mp4' \
  -F 'models=genai' \
  -F 'api_user={api_user}' \
  -F 'api_secret={api_secret}'


# this example uses requests
import requests
import json

params = {
  # specify the models you want to apply
  'models': 'genai',
  'api_user': '{api_user}',
  'api_secret': '{api_secret}'
}
files = {'media': open('/path/to/video.mp4', 'rb')}
r = requests.post('https://api.sightengine.com/1.0/video/check-sync.json', files=files, data=params)

output = json.loads(r.text)


$params = array(
  'media' => new CurlFile('/path/to/video.mp4'),
  // specify the models you want to apply
  'models' => 'genai',
  'api_user' => '{api_user}',
  'api_secret' => '{api_secret}',
);

// this example uses cURL
$ch = curl_init('https://api.sightengine.com/1.0/video/check-sync.json');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $params);
$response = curl_exec($ch);
curl_close($ch);

$output = json_decode($response, true);


// this example uses axios and form-data
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

data = new FormData();
data.append('media', fs.createReadStream('/path/to/video.mp4'));
// specify the models you want to apply
data.append('models', 'genai');
data.append('api_user', '{api_user}');
data.append('api_secret', '{api_secret}');

axios({
  method: 'post',
  url:'https://api.sightengine.com/1.0/video/check-sync.json',
  data: data,
  headers: data.getHeaders()
})
.then(function (response) {
  // on success: handle response
  console.log(response.data);
})
.catch(function (error) {
  // handle error
  if (error.response) console.log(error.response.data);
  else console.log(error.message);
});

See request parameter description

Parameter	Type	Description
media	file	image to analyze
models	string	comma-separated list of models to apply
interval	float	frame interval in seconds, out of 0.5, 1, 2, 3, 4, 5 (optional)
api_user	string	your API user id
api_secret	string	your API secret

Option 2: Long video

Here's how to proceed to analyze a long video. Note that if the video file is very large, you might first need to upload it through the Upload API.


curl -X POST 'https://api.sightengine.com/1.0/video/check.json' \
  -F 'media=@/path/to/video.mp4' \
  -F 'models=genai' \
  -F 'callback_url=https://yourcallback/path' \
  -F 'api_user={api_user}' \
  -F 'api_secret={api_secret}'


# this example uses requests
import requests
import json

params = {
  # specify the models you want to apply
  'models': 'genai',
  # specify where you want to receive result callbacks
  'callback_url': 'https://yourcallback/path',
  'api_user': '{api_user}',
  'api_secret': '{api_secret}'
}
files = {'media': open('/path/to/video.mp4', 'rb')}
r = requests.post('https://api.sightengine.com/1.0/video/check.json', files=files, data=params)

output = json.loads(r.text)


$params = array(
  'media' => new CurlFile('/path/to/video.mp4'),
  // specify the models you want to apply
  'models' => 'genai',
  // specify where you want to receive result callbacks
  'callback_url' => 'https://yourcallback/path',
  'api_user' => '{api_user}',
  'api_secret' => '{api_secret}',
);

// this example uses cURL
$ch = curl_init('https://api.sightengine.com/1.0/video/check.json');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $params);
$response = curl_exec($ch);
curl_close($ch);

$output = json_decode($response, true);


// this example uses axios and form-data
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

data = new FormData();
data.append('media', fs.createReadStream('/path/to/video.mp4'));
// specify the models you want to apply
data.append('models', 'genai');
// specify where you want to receive result callbacks
data.append('callback_url', 'https://yourcallback/path');
data.append('api_user', '{api_user}');
data.append('api_secret', '{api_secret}');

axios({
  method: 'post',
  url:'https://api.sightengine.com/1.0/video/check.json',
  data: data,
  headers: data.getHeaders()
})
.then(function (response) {
  // on success: handle response
  console.log(response.data);
})
.catch(function (error) {
  // handle error
  if (error.response) console.log(error.response.data);
  else console.log(error.message);
});

See request parameter description

Parameter	Type	Description
media	file	image to analyze
callback_url	string	callback URL to receive moderation updates (optional)
models	string	comma-separated list of models to apply
interval	float	frame interval in seconds, out of 0.5, 1, 2, 3, 4, 5 (optional)
api_user	string	your API user id
api_secret	string	your API secret

Option 3: Live-stream

Here's how to proceed to analyze a live-stream:


curl -X GET -G 'https://api.sightengine.com/1.0/video/check.json' \
    --data-urlencode 'stream_url=https://domain.tld/path/video.m3u8' \
    -d 'models=genai' \
    -d 'callback_url=https://your.callback.url/path' \
    -d 'api_user={api_user}' \
    -d 'api_secret={api_secret}'


# this example uses requests
import requests
import json

params = {
  'stream_url': 'https://domain.tld/path/video.m3u8',
  # specify the models you want to apply
  'models': 'genai',
  # specify where you want to receive result callbacks
  'callback_url': 'https://your.callback.url/path',
  'api_user': '{api_user}',
  'api_secret': '{api_secret}'
}
r = requests.post('https://api.sightengine.com/1.0/video/check.json', data=params)

output = json.loads(r.text)


$params = array(
  'stream_url' => 'https://domain.tld/path/video.m3u8',
  // specify the models you want to apply
  'models' => 'genai',
  // specify where you want to receive result callbacks
  'callback_url' => 'https://your.callback.url/path',
  'api_user' => '{api_user}',
  'api_secret' => '{api_secret}',
);

// this example uses cURL
$ch = curl_init('https://api.sightengine.com/1.0/video/check.json');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $params);
$response = curl_exec($ch);
curl_close($ch);

$output = json_decode($response, true);


// this example uses axios and form-data
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

data = new FormData();
data.append('stream_url', 'https://domain.tld/path/video.m3u8');
// specify the models you want to apply
data.append('models', 'genai');
// specify where you want to receive result callbacks
data.append('callback_url', 'https://your.callback.url/path');
data.append('api_user', '{api_user}');
data.append('api_secret', '{api_secret}');

axios({
  method: 'post',
  url:'https://api.sightengine.com/1.0/video/check.json',
  data: data,
  headers: data.getHeaders()
})
.then(function (response) {
  // on success: handle response
  console.log(response.data);
})
.catch(function (error) {
  // handle error
  if (error.response) console.log(error.response.data);
  else console.log(error.message);
});

See request parameter description

Parameter	Type	Description
stream_url	string	URL of the video stream
callback_url	string	callback URL to receive moderation updates (optional)
models	string	comma-separated list of models to apply
interval	float	frame interval in seconds, out of 0.5, 1, 2, 3, 4, 5 (optional)
api_user	string	your API user id
api_secret	string	your API secret

Moderation result

The Moderation result will be provided either directly in the request response (for sync calls, see below) or through the callback URL your provided (for async calls).

Here is the structure of the JSON response with moderation results for each analyzed frame under the data.frames array:

            
                  
{
  "status": "success",
  "request": {
    "id": "req_gmgHNy8oP6nvXYaJVLq9n",
    "timestamp": 1717159864.348989,
    "operations": 40
  },
  "data": {
    "frames": [
      {
        "info": {
          "id": "med_gmgHcUOwe41rWmqwPhVNU_1",
          "position": 0
        },
        "type": {
          "ai_generated": 0.99,
        }
      },
      ...
    ]
  },
  "media": {
    "id": "med_gmgHcUOwe41rWmqwPhVNU",
    "uri": "yourfile.mp4"
  },
}

You can use the classes under the type object to detect AI-generated parts in the video.

On this page

AI-Generated Video Detection

Overview

Use cases

Related model

Generator-specific information

Video generators

Image generators

Use the model

Detect if a video was AI-generated

Option 1: Short video

Option 2: Long video

Option 3: Live-stream

Moderation result