Retrieve Analysis
curl --request GET \
--url https://api.deepidv.com/v1/deepfake-detection/{id}import requests
url = "https://api.deepidv.com/v1/deepfake-detection/{id}"
response = requests.get(url)
print(response.text)const options = {method: 'GET'};
fetch('https://api.deepidv.com/v1/deepfake-detection/{id}', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.deepidv.com/v1/deepfake-detection/{id}",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.deepidv.com/v1/deepfake-detection/{id}"
req, _ := http.NewRequest("GET", url, nil)
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.get("https://api.deepidv.com/v1/deepfake-detection/{id}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.deepidv.com/v1/deepfake-detection/{id}")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
response = http.request(request)
puts response.read_body{
"id": "da_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"status": "completed",
"file_name": "bank_statement_jan2025.pdf",
"file_type": "document",
"external_id": "doc-review-789",
"created_at": "2025-01-15T10:30:00.000Z",
"completed_at": "2025-01-15T10:30:18.000Z",
"result": {
"is_ai_generated": true,
"confidence_score": 87.3,
"risk_level": "critical",
"detection_details": [
{
"signal_type": "FONT_INCONSISTENCY",
"confidence": 91.2,
"description": "Multiple font rendering engines detected within the same document, indicating post-creation editing"
},
{
"signal_type": "METADATA_INCONSISTENCY",
"confidence": 84.5,
"description": "Document creation metadata conflicts with content dates — file created 2025-01-14 but contains transactions dated 2025-01-31"
},
{
"signal_type": "PIXEL_MANIPULATION",
"confidence": 78.9,
"description": "Image layer analysis reveals pixel-level modifications in transaction amount regions"
}
],
"file_metadata": {
"creator": "Google Chrome",
"creation_date": "2025-01-14T22:15:00.000Z",
"modification_date": "2025-01-14T23:42:00.000Z",
"page_count": 3,
"encrypted": false
}
}
}
Deepfake Detection
Retrieve Analysis
Retrieve the results of a deepfake detection analysis
GET
/
v1
/
deepfake-detection
/
{id}
Retrieve Analysis
curl --request GET \
--url https://api.deepidv.com/v1/deepfake-detection/{id}import requests
url = "https://api.deepidv.com/v1/deepfake-detection/{id}"
response = requests.get(url)
print(response.text)const options = {method: 'GET'};
fetch('https://api.deepidv.com/v1/deepfake-detection/{id}', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.deepidv.com/v1/deepfake-detection/{id}",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.deepidv.com/v1/deepfake-detection/{id}"
req, _ := http.NewRequest("GET", url, nil)
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.get("https://api.deepidv.com/v1/deepfake-detection/{id}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.deepidv.com/v1/deepfake-detection/{id}")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
response = http.request(request)
puts response.read_body{
"id": "da_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"status": "completed",
"file_name": "bank_statement_jan2025.pdf",
"file_type": "document",
"external_id": "doc-review-789",
"created_at": "2025-01-15T10:30:00.000Z",
"completed_at": "2025-01-15T10:30:18.000Z",
"result": {
"is_ai_generated": true,
"confidence_score": 87.3,
"risk_level": "critical",
"detection_details": [
{
"signal_type": "FONT_INCONSISTENCY",
"confidence": 91.2,
"description": "Multiple font rendering engines detected within the same document, indicating post-creation editing"
},
{
"signal_type": "METADATA_INCONSISTENCY",
"confidence": 84.5,
"description": "Document creation metadata conflicts with content dates — file created 2025-01-14 but contains transactions dated 2025-01-31"
},
{
"signal_type": "PIXEL_MANIPULATION",
"confidence": 78.9,
"description": "Image layer analysis reveals pixel-level modifications in transaction amount regions"
}
],
"file_metadata": {
"creator": "Google Chrome",
"creation_date": "2025-01-14T22:15:00.000Z",
"modification_date": "2025-01-14T23:42:00.000Z",
"page_count": 3,
"encrypted": false
}
}
}
GET /v1/deepfake-detection/{id}
Request
Headers
| Header | Required | Description |
|---|---|---|
x-api-key | Yes | Your API key |
Path parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
id | string | Yes | The analysis ID (returned when the analysis was created) |
Example request
curl -X GET https://api.deepidv.com/v1/deepfake-detection/da_a1b2c3d4-e5f6-7890-abcd-ef1234567890 \
-H "x-api-key: YOUR_API_KEY"
const response = await fetch(
"https://api.deepidv.com/v1/deepfake-detection/da_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
{
headers: { "x-api-key": "YOUR_API_KEY" },
}
);
const data = await response.json();
import requests
response = requests.get(
"https://api.deepidv.com/v1/deepfake-detection/da_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
headers={"x-api-key": "YOUR_API_KEY"},
)
Response
200 — Success
| Field | Type | Description |
|---|---|---|
id | string | Unique analysis identifier |
status | string | processing, completed, or failed |
file_name | string | Original filename |
file_type | string | Detected file type category |
external_id | string | Your external ID (if provided) |
created_at | string | ISO 8601 creation timestamp |
completed_at | string | ISO 8601 completion timestamp (null if processing) |
result | object | Analysis results (only present when status is completed) |
result object
| Field | Type | Description |
|---|---|---|
is_ai_generated | boolean | Whether the content is determined to be AI-generated |
confidence_score | number | Confidence score (0—100) that the content is AI-generated or manipulated |
risk_level | string | low, medium, high, or critical |
detection_details | array | Array of specific detection findings |
file_metadata | object | Format-specific metadata extracted from the file |
detection_details array items
| Field | Type | Description |
|---|---|---|
signal_type | string | Type of detection signal (e.g., GAN_ARTIFACTS, METADATA_INCONSISTENCY, PIXEL_MANIPULATION) |
confidence | number | Confidence for this specific signal (0—100) |
description | string | Human-readable description of the finding |
file_metadata object
Varies by file type.
| Field | Type | Description |
|---|---|---|
creator | string | Software that created the file |
creation_date | string | File creation date from metadata |
modification_date | string | Last modification date |
page_count | number | Number of pages (documents only) |
dimensions | object | Width and height (images only) |
duration_seconds | number | Duration (audio/video only) |
codec | string | Codec information (audio/video only) |
Error responses
| Status | Description |
|---|---|
400 Bad Request | Invalid analysis ID format |
401 Unauthorized | Missing or invalid API key |
403 Forbidden | Analysis belongs to a different organization |
404 Not Found | Analysis ID does not exist |
429 Too Many Requests | Rate limit exceeded |
{
"id": "da_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"status": "completed",
"file_name": "bank_statement_jan2025.pdf",
"file_type": "document",
"external_id": "doc-review-789",
"created_at": "2025-01-15T10:30:00.000Z",
"completed_at": "2025-01-15T10:30:18.000Z",
"result": {
"is_ai_generated": true,
"confidence_score": 87.3,
"risk_level": "critical",
"detection_details": [
{
"signal_type": "FONT_INCONSISTENCY",
"confidence": 91.2,
"description": "Multiple font rendering engines detected within the same document, indicating post-creation editing"
},
{
"signal_type": "METADATA_INCONSISTENCY",
"confidence": 84.5,
"description": "Document creation metadata conflicts with content dates — file created 2025-01-14 but contains transactions dated 2025-01-31"
},
{
"signal_type": "PIXEL_MANIPULATION",
"confidence": 78.9,
"description": "Image layer analysis reveals pixel-level modifications in transaction amount regions"
}
],
"file_metadata": {
"creator": "Google Chrome",
"creation_date": "2025-01-14T22:15:00.000Z",
"modification_date": "2025-01-14T23:42:00.000Z",
"page_count": 3,
"encrypted": false
}
}
}
⌘I
