GHSA-cw7p-q79f-m2v7 is a low-severity (CVSS 3.5) CWE-613 vulnerability in jupyterhub. A fix is available for jupyterhub — see the affected versions and patch details below.
incomplete JupyterHub logout with simultaneous JupyterLab sessions
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-cw7p-q79f-m2v7 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 377,166 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
jupyterhubReal-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
Users of JupyterLab with JupyterHub who have multiple JupyterLab tabs open in the same browser session, may see incomplete logout from the single-user server, as fresh credentials (for the single-user server only, not the Hub) reinstated after logout, if another active JupyterLab session is open while the logout takes place.
Patches
Upgrade to JupyterHub 1.5. For distributed deployments, it is jupyterhub in the user environment that needs patching. There are no patches necessary in the Hub environment.
Workarounds
The only workaround is to make sure that only one JupyterLab tab is open when you log out.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterhub | ≥ 1.0.0&&< 1.5.0 | 1.5.0pip install --upgrade 'jupyterhub==1.5.0' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterhub, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update jupyterhub to 1.5.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-cw7p-q79f-m2v7 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-cw7p-q79f-m2v7 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-cw7p-q79f-m2v7. 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-cw7p-q79f-m2v7 in your dependencies?
O3 Security finds GHSA-cw7p-q79f-m2v7 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.