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Fencer Vulns
high 7.1

CVE-2023-47115 json

Label Studio XSS Vulnerability on Avatar Upload

published 2024-01-23 2 y ago modified 2026-09-10 1 mo ago also GHSA-q68h-xwq5-mm7x , PYSEC-2024-126 , EUVD-2024-0082

cvss
7.1
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
1.4%
EPSS 1.4% chance of exploitation in 30 days, percentile 73%
public exploits
0
none known, plus a Nuclei check

Summary

Label Studio is an a popular open source data labeling tool. Versions prior to 1.9.2 have a cross-site scripting (XSS) vulnerability that could be exploited when an authenticated user uploads a crafted image file for their avatar that gets rendered as a HTML file on the website. 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.

The file `users/functions.py` lines 18-49 show that the only verification check is that the file is an image by extracting the dimensions from the file. Label Studio serves avatar images using Django's built-in `serve` view, which is not secure for production use according to Django's documentation. The issue with the Django `serve` view is that it determines the `Content-Type` of the response by the file extension in the URL path. Therefore, an attacker can upload an image that contains malicious HTML code and name the file with a `.html` extension to be rendered as a HTML page. The only file extension validation is performed on the client-side, which can be easily bypassed.

Version 1.9.2 fixes this issue. Other remediation strategies include validating the file extension on the server side, not in client-side code; removing the use of Django's `serve` view and implement a secure controller for viewing uploaded avatar images; saving file content in the database rather than on the filesystem to mitigate against other file related vulnerabilities; and avoiding trusting user controlled inputs.

Patch / fix

  • pypi label-studio 1.9.2
  • humansignal label_studio 1.9.2

CISA SSVC

Exploitation
Proof of concept is public
Automatable
no
Technical impact
partial
Assessed
18 mo ago

Exploit prediction

1.45% chance of exploitation in the next 30 days, higher than 73% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • Nuclei template Label Studio - Cross-Site Scripting nuclei detection template
  • github.com https://github.com/HumanSignal/label-studio/security/advisories/GHSA-q68h-xwq5-mm7x referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:L
NVD 3.1 5.4 CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N
GitHub 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:L
OSV 3.1 5.4 CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N

Affected packages

ecosystem package affected fixed in
pypi label-studio
<1.9.2
1.9.2

Affected products

  • HumanSignal label-studio

Classification

Weakness
  • CWE-79 Improper Neutralization of Input During Web Page Generation

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.