POST https://api.copyleaks.com/v2/writer-detector/source-code/{scanId}/check

Deprecation Notice

AI Code Detection will be discontinued on August 29, 2025. Please remove AI code detection integrations before the sunset date.

Use Copyleaks AI Content Detection to differentiate between human-written and AI-written source code.

This endpoint will receive submitted source code to be checked. At the end of the processing stage, the result will be shown as classifications. Source code classification is divided into sections. Each section may have a different classification.

Authentication Required

You need to login with a user and api key in order to access this method. Add this HTTP header to your request:

Authorization: Bearer < Your-Login-Token >

Need Help?

Not sure how to generate your login token? Read here.

Request

Path Parameters

scanId string required

A unique scan id provided by you. We recommend you use the same id in your database to represent the scan in the Copyleaks database. This will help you to debug incidents. Using the same ID for the same file will help you to avoid network problems that may lead to multiple scans for the same file. learn more about the criteria for creating a Scan ID.

>= 3 characters <= 36 characters

Match pattern: [a-z0-9] !@$^&-+%=_(){}<>';:/.",~|

Headers

Content-Type: application/json
Authorization: Bearer YOUR_LOGIN_TOKEN

Request Body

The request body is a JSON object containing the source code to scan.

text string required

A text string. Supported Languages:

• Ruby
• javascript
• typescript
• python
• C++
• C
• Java
• C#
• PHP

>= 255 characters <= 25000 characters

filename string required

The name of the file. Make sure to include the right extension for your file type.

Example: Myfile.py

sandbox boolean default: "false"

Use sandbox mode to test your integration with the Copyleaks API for free.

code object

comments boolean default: "false"

When set to true, the scan will ignore comments in the source code.

Responses

200

200 OK

The command was executed.

Response Schema

The response contains the following fields:

modelVersion string

The version of the AI detection model used.

results array<object>

An array of classification results for different sections of the code. See AI Detection Response for more details.

summary object

A summary of the overall classification (human vs. AI).

scannedDocument object

Metadata about the scan. See Scanned Document for more details.

explain object

Data for the AI Logic feature, explaining the classification. See AI Logic for more details.

Example Response

A typical response from this endpoint:

Show full example (115 lines)

{
  "modelVersion": "v5",
  "results": [
    {
      "classification": 2,
      "probability": 1,
      "matches": [
        {
          "text": {
            "chars": {
              "starts": [
                0
              ],
              "lengths": [
                1509
              ]
            },
            "words": {
              "starts": [
                0
              ],
              "lengths": [
                221
              ]
            }
          }
        }
      ]
    }
  ],
  "summary": {
    "human": 0,
    "ai": 1
  },
  "scannedDocument": {
    "scanId": "check",
    "totalWords": 221,
    "totalExcluded": 0,
    "actualCredits": 1,
    "expectedCredits": 1,
    "creationTime": "2023-01-10T10:07:58.9459512Z"
  },
  "explain": {
    "patterns": {
      "statistics": {
        "aiCount": [
          15.9636,
          39.5495,
          84.7079,
          119.871,
          9.9233,
          185.667,
          14.4536,
          19.1995
        ],
        "humanCount": [
          0.8076,
          1.5076,
          3.8228,
          8.5071,
          0.3769,
          4.2536,
          0.3231,
          1.1845
        ]
      },
      "text": {
        "chars": {
          "starts": [
            31,
            55,
            303,
            909,
            961,
            987,
            1129,
            1775
          ],
          "lengths": [
            23,
            32,
            23,
            33,
            25,
            30,
            30,
            19
          ]
        },
        "words": {
          "starts": [
            5,
            9,
            45,
            135,
            144,
            148,
            169,
            257
          ],
          "lengths": [
            4,
            6,
            3,
            6,
            4,
            5,
            5,
            3
          ]
        }
      }
    }
  }
}

{
  "modelVersion": "v5",
  "results": [
    {
      "classification": 2,
      "probability": 1,
      "matches": [
        {
          "text": {
            "chars": {
              "starts": [
                0
              ],
              "lengths": [
                1509
// ... truncated

400

400 Bad Request

Bad request.

Example Response

A typical response from this endpoint:

{
  "ErrorMessage": "Language not supported",
  "ErrorCode": "unsupported-lang"
}

401

401 Unauthorized

Authorization has been denied for this request.

Example Response

A typical response from this endpoint:

{
  "type": "https://tools.ietf.org/html/rfc9110#section-15.5.2",
  "title": "Unauthorized",
  "status": 401,
  "traceId": "00-ef0db7690ced98431ac97782051edc77-2c4194d74ae6c08b-00"
}

429

429 Too Many Requests

Too many requests have been sent. The request has been rejected.

Example Response

A typical response from this endpoint:

{
  "error": "Rate limit exceeded",
}

Examples

HTTP

POST https://api.copyleaks.com/v2/writer-detector/source-code/my-scan-123/check
Content-Type: application/json
Authorization: Bearer YOUR_LOGIN_TOKEN

{
  "text": "import sqlite3 def connect_to_database(): return sqlite3.connect(\"pharmacy.db\") def retrieve_medication_data(medication_id): connection = connect_to_database() cursor = connection.cursor() cursor.execute(\"SELECT * FROM medications WHERE id=?\", (medication_id,)) medication_data = cursor.fetchone() connection.close() return medication_data # Example usage medication_data = retrieve_medication_data(\"ABC123\") print(medication_data)",
  "filename": "MyFile.py"
}

cURL

curl --request POST \
  --url https://api.copyleaks.com/v2/writer-detector/source-code/my-scan-123/check \
  --header 'Authorization: Bearer YOUR_LOGIN_TOKEN' \
  --header 'Content-Type: application/json' \
  --data '{
    "text": "import sqlite3 def connect_to_database(): return sqlite3.connect(\"pharmacy.db\") def retrieve_medication_data(medication_id): connection = connect_to_database() cursor = connection.cursor() cursor.execute(\"SELECT * FROM medications WHERE id=?\", (medication_id,)) medication_data = cursor.fetchone() connection.close() return medication_data # Example usage medication_data = retrieve_medication_data(\"ABC123\") print(medication_data)",
    "filename": "MyFile.py"
  }'

Next Steps

AI Text Detection Learn how to use the AI Detection API for natural language.

AI Logic Understand how AI logic can help you interpret the results of AI text detection.

Technical Specifications Review the technical specifications for supported file types and other limits.