GHSA-9q39-rmj3-p4r2 is a high-severity (CVSS 7.6) Cross-site Scripting (XSS) vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.
HTML injection in Jupyter Notebook and JupyterLab leading to DOM Clobbering
Exploitation Status
No confirmed exploitation observed yet
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for GHSA-9q39-rmj3-p4r2.
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.
How urgent is this, really
GHSA-9q39-rmj3-p4r2 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 379,145 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
jupyterlab🐍notebook🐍jupyterlabReal-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
Impact
The vulnerability depends on user interaction by opening a malicious notebook with Markdown cells, or Markdown file using JupyterLab preview feature.
A malicious user can access any data that the attacked user has access to as well as perform arbitrary requests acting as the attacked user.
Patches
JupyterLab v3.6.8, v4.2.5 and Jupyter Notebook v7.2.2 were patched.
Workarounds
There is no workaround for the underlying DOM Clobbering susceptibility. However, select plugins can be disabled on deployments which cannot update in a timely fashion to minimise the risk. These are:
@jupyterlab/mathjax-extension:plugin- users will loose ability to preview mathematical equations@jupyterlab/markdownviewer-extension:plugin- users will loose ability to open Markdown previews@jupyterlab/mathjax2-extension:plugin(if installed with optionaljupyterlab-mathjax2package) - an older version of the mathjax plugin for JupyterLab 4.x
To disable these extensions run:
jupyter labextension disable @jupyterlab/markdownviewer-extension:plugin
jupyter labextension disable @jupyterlab/mathjax-extension:plugin
jupyter labextension disable @jupyterlab/mathjax2-extension:plugin
To confirm that the plugins were disabled run:
jupyter labextension list
References
None
Notes
This change has a potential to break rendering of some markdown. There is a setting in Sanitizer which allows to revert to the previous sanitizer settings (allowNamedProperties).
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterlab | all versions | 3.6.8pip install --upgrade 'jupyterlab==3.6.8' |
| 🐍PyPI | notebook | ≥ 7.0.0&&< 7.2.2 | 7.2.2pip install --upgrade 'notebook==7.2.2' |
| 🐍PyPI | jupyterlab | ≥ 4.0.0&&< 4.2.5 | 4.2.5pip install --upgrade 'jupyterlab==4.2.5' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlab, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update jupyterlab to 3.6.8 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-9q39-rmj3-p4r2 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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-9q39-rmj3-p4r2 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-9q39-rmj3-p4r2. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-9q39-rmj3-p4r2 in your dependencies?
O3 Security finds GHSA-9q39-rmj3-p4r2 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.