CVE-2026-73417 — jupyterlab
Fix: jupyterlab/jupyterlab@9365f02CVE-2026-73417 is a Cross-site Scripting (XSS) vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.
JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)
Exploitation Status
No confirmed exploitation observed yet
- A successful exploit gives an attacker total control of the affected component, not partial access.
- 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 CVE-2026-73417.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
Real-World Exposure
jupyterlab🐍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
JupyterLab 4.5+ allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor.
Certain notebook display settings were not properly validated before being applied. As a result, a crafted settings file could contain hidden instructions that run as code inside JupyterLab when imported, instead of only changing a display preference.
Because importing a settings file appears harmless, a user could import a file shared by another party without realizing it could do more. On multi-tenant file systems without proper permission control, another user could plant a malicious overrides.json.
CVE assignment pending, GitHub CNA is experiencing severe backlog
Impact
When a malicious settings file is applied, the embedded code runs with the same access as the affected user. This could allow an attacker to read or modify that user's notebooks and files, and to run code on the user's behalf through the notebook server, including on any connected kernel.
User Interaction vs Privileges Required
Write access to a loaded settings location
If an attacker can write to a directory JupyterLab loads settings from (e.g. on shared or multi-tenant file system), they could place a crafted overrides.json that is applied to another user automatically at startup. This requires high privilages but no action by the victim.
User-imported settings file
A user can import a crafted overrides.json through the Import button in the Settings Editor, having received it from another party. This requires no privileges but a deliberate action by the victim, who reasonably expects a settings file to change preferences rather than run code.
Patches
JupyterLab 4.6.2 and 4.5.10 were patched.
Workarounds
None
Hardening
- Treat a settings file as something that can affect how JupyterLab behaves, not only how it appears. Administrators are encouraged to establish a trusted process for distributing configuration rather than relying on ad-hoc importing of shared files.
- On multi-tenant or shared file systems, restrict write permissions on the application settings directory and other Jupyter configuration paths so that one user cannot place an
overrides.json(or other configuration) readable by another user. A settings file in these locations is applied automatically, without an import step, so directory permissions are the primary control against cross-user tampering.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterlab | ≥ 4.6.0&&< 4.6.2 | 4.6.2pip install --upgrade 'jupyterlab==4.6.2' |
| 🐍PyPI | jupyterlab | ≥ 3.3.0&&< 4.5.10 | 4.5.10pip install --upgrade 'jupyterlab==4.5.10' |
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 4.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-73417 is resolved across your whole dependency graph.
Workarounds
Escape or sanitise the affected output on the server side rather than relying on client-side filtering, and add a Content-Security-Policy that blocks inline script execution so injected markup cannot run even if it reaches the page.
Fixing This On Your OS
If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.
This Important cross-site scripting (XSS) flaw in JupyterLab allows arbitrary code execution when processing a specially crafted overrides.json file. An attacker could either plant a malicious settings file in a shared location, leading to automatic execution, or trick a user into importing one. This grants the…
Users should avoid importing `overrides.json` files from untrusted sources. Additionally, ensure that shared settings locations are secured to prevent unauthorized modification by attackers.Source: Red Hat security advisory for CVE-2026-73417 (CC BY 4.0)
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat OpenShift AI 2.25 | rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1788315638 | RHSA-2026:65126 |
Frequently Asked Questions
Is CVE-2026-73417 in your dependencies?
Find it across PyPI, including transitive dependencies.