CVE-2026-42557 — jupyterlab
CVE-2026-42557 is a Cross-site Scripting (XSS) vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.
jupyterlab: Command linker attributes in HTML enable one-click command execution from untrusted content
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-2026-42557.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
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
JupyterLab's HTML sanitizer allowlists data-commandlinker-command and data-commandlinker-args on button elements, while CommandLinker listens for all click events on document.body and executes the named command without checking whether the element came from trusted JupyterLab UI. A notebook with a pre-saved HTML cell output containing a deceptive button can trigger arbitrary JupyterLab commands - including arbitrary code execution - on a single user click, without any code being submitted for execution by the user.
Impact
An attacker who shares a notebook or a Markdown file - via email, GitHub, or a Binder link - can invoke an arbitrary command upon a single click by the victim. The button can be rendered inside the output area and be visually indistinguishable from a legitimate widget. No kernel needs to start; the HTML output is stored in the notebook file and displayed immediately on open.
Single-click impact
An attacker convincing the victim to click on a single button or link can:
- execute arbitrary code in the available kernels,
- delete files leading to information loss; in principle the loss could be unrecoverable, depending on server configuration and attack complexity,
- open multiple kernels/terminals at once, or create multiple files at once, putting significant stress on the server and thus deny availability for other users when using standalone multi-tenant jupyter-server deployment, and to a lesser degree impact availability on JupyterHub deployments.
The arbitrary code execution will be immediately visible to the user; and can be halted by the timely user intervention. The deletion of files can be silent and go unnoticed for some time.
Multi-click attacks
An attacker who convinces the victim to click on multiple buttons in specific order and to grant access to clipboard (or in scenarios where the user already granted keyboard access) can obtain full access to the terminal and execute arbitrary commands in the environment with access scope that might exceed that of available kernels. Only users of Chromium-based browsers are susceptible to this expanded variant of the attack.
The execution of commands in the terminal would be immediately visible to the user.
Impact of third-party extensions
The impact described above assumes a plain JupyterLab/Notebook installation. In environments with frontend extensions that contribute additional commands the attack surface is increased by the functionality covered by these commands.
Patches
JupyterLab 4.5.7
Workarounds
No workarounds are available for end-users.
Downstream applications inheriting from JupyterFrontEnd or JupyterLab can effectively disable the CommandLinker by passing commandLinker: new CommandLinker({ commands: new CommandRegistry() }) option in the initialization options.
Hardening
The patched versions include a toggle to disable the command linker functionality altogether, for example via overrides.json:
{
"@jupyterlab/apputils-extension:sanitizer": {
"allowCommandLinker": false
}
}
Resources
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | jupyterlab | all versions | 4.5.7pip install --upgrade 'jupyterlab==4.5.7' |
| 🐍PyPI | notebook | ≥ 7.0.0&&< 7.5.6 | 7.5.6pip install --upgrade 'notebook==7.5.6' |
Affected Products
jupyterlabjupyternotebookjupyterDetection & 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 4.5.7 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-42557 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 vulnerability in JupyterLab allows arbitrary code execution through a deceptive button embedded in a notebook's HTML output. When a user clicks this specially crafted button, the CommandLinker component executes unauthorized JupyterLab commands, bypassing security validation. This can lead to compromise…
Users should avoid opening or interacting with JupyterLab notebooks from untrusted sources. Exercise caution and verify the origin of any notebook before clicking buttons within its output, as this action could lead to the execution of arbitrary commands.Source: Red Hat security advisory for CVE-2026-42557 (CC BY 4.0)
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat Migration Toolkit for Applications 8.2 | mta/mta-solution-server-rhel9:1784109883 | RHSA-2026:43038 |
| Red Hat OpenShift AI 3.4 | rhoai/odh-th06-cpu-torch210-py312-rhel9:1787076778 | RHSA-2026:60520 |
Frequently Asked Questions
Is CVE-2026-42557 in your dependencies?
Find it across PyPI, including transitive dependencies.