Threat Intelligence Database

A missing await in JupyterLab's PyPIExtensionManager.install() method caused the allowlist/blocklist check to not be enforced for direct callers. This issue affects only custom extensions or downstream integrations that call install() directly with untrusted input and rely on this method to enforce package restrictions. The default JupyterLab HTTP API and UI are not affected as they perform their own awaited checks. The vulnerability is low severity and has been patched in JupyterLab versions 4.6.2 and 4.5.10.

JupyterLab's plugin manager has a vulnerability that allows authenticated users to bypass administrator-imposed plugin lock rules via direct API requests. This bypass affects child plugins of multi-plugin extensions and scenarios where administrators issued a 'lock all' command. The flaw can undermine data integrity and circumvent restrictions implemented through locked plugins. Patches addressing this issue are available in JupyterLab versions 4.6.2 and 4.5.10. Users of dependent applications like Notebook v7+ should also update the jupyterlab package. As a workaround, administrators can manually lock all plugins that require restriction using documented plugin identifiers.

JupyterLab's PyPI extension manager has a vulnerability in its blocklist enforcement due to weaker string normalization compared to PyPI package-name canonicalization. An authenticated user can bypass blocklist restrictions by requesting a PyPI-equivalent package name variant, allowing installation of otherwise blocked packages. This affects deployments using custom allow/block lists with the default PyPI Extension Manager enabled and kernels/terminals disabled or remote. The vulnerability enables untrusted users to impact the integrity and availability of their single-user jupyter-server instance by installing arbitrary extensions, though it does not grant new read access to other users' data.

JupyterLab's image viewer contains a cross-site scripting (XSS) vulnerability that can be triggered by opening a specially crafted image file and then opening it in a new browser tab. This vulnerability can lead to remote code execution on the JupyterLab server. Fixed versions 4.6.2 and 4.5.10 address this issue. A workaround is to disable the image viewer plugin.

JupyterLab versions 3.3.0 through before 4.5.10 and 4.6.0 through before 4.6.2 contain a vulnerability where crafted settings files (overrides.json) can execute code when imported or automatically loaded. This cross-site scripting (XSS) flaw arises because certain notebook display settings are not properly validated, allowing embedded code execution with the user's privileges. Attackers with write access to shared settings directories can plant malicious files applied automatically, while users can also be tricked into importing malicious settings files. The vulnerability enables attackers to read, modify notebooks and files, and execute code on behalf of the user. Official patches are available in versions 4.5.10 and 4.6.2. No workarounds exist, but administrators should restrict write permissions on shared settings directories and establish trusted configuration distribution processes.