GHSA-c336-7962-wfj2
Dask Distributed is Vulnerable to Remote Code Execution via Jupyter Proxy and Dashboard
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
distributedReal-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
When Jupyter Lab, jupyter-server-proxy and Dask distributed are all run together it is possible to craft a URL which will result in code being executed by Jupyter due to a cross-side-scripting (XSS) bug in the Dask dashboard.
It is possible for attackers to craft a phishing URL that assumes Jupyter Lab and Dask may be running on localhost and using default ports. If a user clicks on the malicious link it will open an error page in the Dask Dashboard via the Jupyter Lab proxy which will cause code to be executed by the default Jupyter Python kernel.
In order for a user to be impacted they must be running Jupyter Lab locally on the default port (with the jupyter-server-proxy) and a Dask distributed cluster on the default port. Then they would need to click the link which would execute the malicious code.
Patches
This has been fixed in the 2026.1.0 release. All users should upgrade to this version.
Mitigations
There are no known workarounds for this bug. The only complete solution is to upgrade to a newer release of Dask. However, there are a few things you could do to reduce your risk.
It is possible to avoid code execution via Jupyter by uninstalling the jupyter-server-proxy and accessing the Dask dashboard directly at it's URL. However, it is still possible for an attacker to craft a URL that executes JavaScript in the user's browser in the Dask dashboard. Which is still a moderate vulnerability. Therefore we recommend all users upgrade to the latest Dask release.
Another potential mitigation is to ensure both Jupyter and the Dask dashboard are running on non-standard ports. While this doesn't resolve the problem it reduces the chance of this being exploited. If an attacker knew which ports you were using they could still craft a malicious URL, but it would require a more targeted attack.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | distributed | all versions | 2026.1.0 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for distributed. 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 distributed to 2026.1.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-c336-7962-wfj2 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 GHSA-c336-7962-wfj2 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 GHSA-c336-7962-wfj2. 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-c336-7962-wfj2 in your dependencies?
O3 detects GHSA-c336-7962-wfj2 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.