CVE-2023-47115
HIGHLabel Studio XSS Vulnerability on Avatar Upload
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
label-studioReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
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.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | label-studio | all versions | 1.9.2 |
Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for label-studio. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update label-studio to 1.9.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2023-47115 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether CVE-2023-47115 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to CVE-2023-47115. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is CVE-2023-47115 in your dependencies?
O3 detects CVE-2023-47115 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.