GHSA-4m77-cmpx-vjc4 is a medium-severity (CVSS 6.5) Cross-site Scripting (XSS) vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.
JupyterLab vulnerable to SXSS in Markdown Preview
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-4m77-cmpx-vjc4.
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-4m77-cmpx-vjc4 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 377,636 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🐍notebookReal-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 v4.0.11 was patched.
Workarounds
Users can either disable the table of contents extension by running:
jupyter labextension disable @jupyterlab/toc-extension:registry
References
Vulnerability reported via the bug bounty program sponsored by the European Commission and hosted on the Intigriti platform.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterlab | ≥ 4.0.0&&< 4.0.11 | 4.0.11pip install --upgrade 'jupyterlab==4.0.11' |
| 🐍PyPI | notebook | ≥ 7.0.0&&< 7.0.7 | 7.0.7pip install --upgrade 'notebook==7.0.7' |
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 4.0.11 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-4m77-cmpx-vjc4 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-4m77-cmpx-vjc4 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-4m77-cmpx-vjc4. 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-4m77-cmpx-vjc4 in your dependencies?
O3 Security finds GHSA-4m77-cmpx-vjc4 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.