| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| JupyterLab Desktop is the cross-platform desktop application for JupyterLab. Prior to 4.6.2-1, JupyterLab Desktop for macOS declared the com.apple.security.cs.allow-dyld-environment-variables entitlement, allowing the dynamic linker to honor DYLD_INSERT_LIBRARIES despite the hardened runtime. An attacker who can already execute code as the current user can load an arbitrary dynamic library into the JupyterLab Desktop process and inherit TCC permissions previously granted to the application, including access to protected Documents, Desktop, or Downloads folders without another macOS prompt. Exploitation requires existing local code execution and prior TCC grants; it does not provide initial or remote code execution. Windows and Linux are not affected. This vulnerability is fixed in 4.6.2-1. |
| JupyterLab Desktop is the cross-platform desktop application for JupyterLab. Prior to 4.6.2-1, JupyterLab Desktop exposed getServerInfo to the renderer without confirming that the current page still had the local Jupyter server origin. In a local managed session using JupyterLab before 4.4.8, an attacker can place a crafted MathJax link in an untrusted notebook. If a victim opens the notebook and clicks the link, the existing renderer navigates to an attacker-controlled site while retaining access to the preload bridge. The site can call getServerInfo to obtain the local server URL and authentication token, then use the Jupyter REST API to create and trust a notebook that executes arbitrary code as the victim. Users whose environment already uses JupyterLab 4.4.8 or later are unaffected because the corrected link handling breaks the first step of the chain. This vulnerability is fixed in 4.6.2-1. |
| JupyterLab Desktop is the cross-platform desktop application for JupyterLab. Prior to 4.6.2-1, JupyterLab Desktop for macOS shipped with Electron's RunAsNode fuse enabled, allowing ELECTRON_RUN_AS_NODE to execute arbitrary Node.js code in the application process. An attacker who can already execute code as the current user can therefore run code in JupyterLab Desktop's context and inherit TCC permissions previously granted to the application, including access to protected Documents, Desktop, or Downloads folders without another macOS prompt. Exploitation requires existing local code execution and prior TCC grants; it does not provide initial or remote code execution. Windows and Linux are not affected. This vulnerability is fixed in 4.6.2-1. |
| JupyterLab Desktop is the cross-platform desktop application for JupyterLab. Prior to 4.6.2-1, remote-server URLs were inserted into the server-selection dialog and Welcome view without safe encoding. An attacker who convinces a user to submit a crafted URL can execute JavaScript in the Welcome renderer and abuse its privileged IPC bridge to execute arbitrary code with the user’s privileges. The Welcome view also unsafely renders RSS news-feed titles; exploitation through this separate input path requires control over content delivered through the application’s Jupyter Blog feed or its cached feed data, rather than submission of a remote-server URL. This issue affects all supported platforms and is fixed in version 4.6.2-1. |
| JupyterLab extension template is a `copier` template for JupyterLab extensions. Repositories created using this template with `test` option include `update-integration-tests.yml` workflow which has an RCE vulnerability. Extension authors hosting their code on GitHub are urged to upgrade the template to the latest version. Users who made changes to `update-integration-tests.yml`, accept overwriting of this file and re-apply your changes later. Users may wish to temporarily disable GitHub Actions while working on the upgrade. We recommend rebasing all open pull requests from untrusted users as actions may run using the version from the `main` branch at the time when the pull request was created. Users who are upgrading from template version prior to 4.3.0 may wish to leave out proposed changes to the release workflow for now as it requires additional configuration. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 4.5.0 until 4.5.11 and 4.6.4, from Notebook 7.5.0 until 7.6.3, and from JupyterLite Core 0.7.0 until 0.8.4, the system clipboard cell-paste path accepts attacker-controlled cell JSON without clearing metadata.trusted. When useSystemClipboardForCells is active and pasteCodeCellsWithoutOutput is disabled, a pasted code cell can mark HTML output as trusted, bypass output sanitization, and execute script in the authenticated JupyterLab origin without executing the cell. Markdown and raw cells are not affected because their output is sanitized. This issue is fixed in JupyterLab 4.5.11 and 4.6.4, Notebook 7.6.3, and JupyterLite Core 0.8.4. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 4.0.0 until 4.5.11 and 4.6.4, the PyPI Extension Manager uninstall request reaches ExtensionHandler.post, which validates extension names for installation but passes uninstall names to PyPIExtensionManager.uninstall and python -m pip uninstall without rejecting option-like values. The security impact requires that the PyPI Extension Manager is enabled, the account can call the extension API, and kernels and terminals are disabled or delegated to remote hosts; otherwise the user can already read files and make outbound requests directly. An authenticated user with extension API access can supply a pip requirements option to make the server read a local file or fetch an internal URL, and reflected parse errors can return the first unparsable line or response content. A pip log option can also create or corrupt a chosen path with pip-generated log text, but the requester cannot select an arbitrary disclosed line or arbitrary file content, and the injection does not add code execution or availability impact beyond ordinary package removal. This issue is fixed in JupyterLab 4.5.11 and 4.6.4. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 3.0.0 until 4.5.11 and 4.6.4, and in JupyterLite Core 0.8.3 and earlier, the Plural-Forms header in a selected third-party language pack can append JavaScript after a valid plural rule because prefix-only regular-expression validation accepts a matching prefix without requiring the entire header to match. JupyterLab passes the accepted expression to new Function, so loading the catalogue and translating a plural string executes the appended code in the authenticated JupyterLab origin. Where Jupyter Server kernels, terminals, and APIs are exposed, the code can use authenticated server APIs to read or modify files and run code. Impact is much more limited in JupyterLite because it typically lacks most exposed Jupyter Server surfaces. The default English locale is unaffected because it does not load a translation catalogue. This issue is fixed in JupyterLab 4.5.11 and 4.6.4 and JupyterLite Core 0.8.4. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. Prior to 4.5.7, 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. This vulnerability is fixed in 4.5.7. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 4.0.0 to 4.5.6, the allow-list of extensions that can be installed from PyPI Extension Manager (allowed_extensions_uris) is not correctly enforced by JupyterLab. The PyPI Extension Manager was not contained to packages listed on the default PyPI index. This vulnerability is fixed in 4.5.7. |
| JupyterLab versions >=4.6.0,<=4.6.1 and <=4.5.9 contain an allowlist/blocklist enforcement gap in PyPIExtensionManager.install(). A missing 'await' caused the is_install_allowed coroutine to never execute, so the extension allowlist/blocklist check was not enforced for direct callers of install(). The stock JupyterLab HTTP API and Extension Manager UI are not affected, as they perform a separate, correctly awaited check. The issue affects only deployments where a custom extension or downstream integration imports PyPIExtensionManager and calls install() directly with a package name influenced by untrusted input, an allowlist/blocklist is configured, the PyPI Extension Manager is enabled, and kernels and terminals are disabled or delegated to remote hosts. Fixed in JupyterLab 4.6.2 and 4.5.10. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 4.5.0 until 4.5.10 and 4.6.2, in jupyterlab/extensions/manager.py and jupyterlab/extensions/pypi.py, JupyterLab's PyPI extension manager enforces blocked_extensions_uris by comparing requested install names to blocklist entries with custom normalization that is weaker than PyPI package-name canonicalization. An authenticated user can request a PyPI-equivalent spelling such as JupyterLab.Git for a blocklisted package such as jupyterlab-git, and JupyterLab accepts the install request even though pip resolves the variant to the same package. Security impact requires an allowlist or blocklist intended to restrict package installation, the PyPI Extension Manager, and kernels and terminals that are disabled or delegated to remote hosts. The bypass lets an authenticated user install a prohibited extension, defeat integrity restrictions, and affect availability without gaining new read access. This issue is fixed in versions 4.5.10 and 4.6.2. |
| JupyterLab (pip package 'jupyterlab') versions >=4.1.0,<=4.5.9 and >=4.6.0,<=4.6.1 contain a plugin manager lock-rule enforcement bypass. Two server-side enforcement gaps allow an authenticated user to circumvent administrator lock rules by making direct requests to the /lab/api/plugins endpoint, enabling or disabling plugins that were locked — including child plugins of multi-plugin extensions and plugins locked via the 'lock all' mechanism. This can impact data integrity and bypass hardening or restrictions (e.g., download/upload limits) implemented through locked plugins. Fixed in versions 4.6.2 and 4.5.10. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 3.3.0 until 4.5.10 and 4.6.2, JupyterLab allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor. In packages/notebook-extension/schema/tracker.json and packages/notebook-extension/src/index.ts, the sideBySideLeftMarginOverride and sideBySideRightMarginOverride settings are not properly validated before being inserted into style content, allowing a crafted settings file to contain instructions that execute as code instead of only changing display preferences. A user can import the malicious file, or an attacker with access to a shared settings location can plant an overrides.json that is applied automatically. The embedded code runs with the affected user's access and can read or modify notebooks and files and run code through the notebook server, including on a connected kernel. This issue is fixed in versions 4.5.10 and 4.6.2. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. Prior to 4.5.10 and 4.6.2, in packages/imageviewer/src/widget.ts, JupyterLab's ImageViewer uses URL.createObjectURL for a specially crafted SVG image and revokes the blob URL too early, allowing the image to retain an executable same-origin context when it is opened through the image viewer and then opened in a new browser tab. The resulting cross-site scripting can be used to execute arbitrary code on the JupyterLab server. This issue is fixed in versions 4.5.10 and 4.6.2. |
| JupyterLab before 4.5.9 contains a stored cross-site scripting vulnerability in the Extension Manager that fails to validate URI protocols in package metadata URLs. Attackers can publish malicious PyPI packages with javascript: URLs in project metadata that execute arbitrary JavaScript in the JupyterLab origin when users click the extension name. |
| JupyterLab Git is a Git extension for JupyterLab. From 0.30.0b3 before 0.54.0, the PlainTextDiff.ts createHeader() method passes Git filenames directly to innerHTML when rendering renamed files in commit history, allowing a crafted filename to execute JavaScript when a victim views the rename diff in the Git History tab. This issue is fixed in version 0.54.0. |
| JupyterLab Git is a Git extension for JupyterLab. Prior to 0.54.0, jupyterlab-git uses fnmatch.fnmatchcase() in GitHandler.prepare() in jupyterlab_git/handlers.py to enforce excluded_paths, allowing an authenticated user on a case-insensitive filesystem to vary URL path casing and read excluded directories. This issue is fixed in version 0.54.0. |
| In Jupyter Notebook versions 7.0.0 through 7.5.5, JupyterLab versions 4.5.6 and earlier, and the corresponding @jupyter-notebook/help-extension and @jupyterlab/help-extension packages before 7.5.6 and 4.5.7, a stored cross-site scripting issue in the help command linker can be chained with attacker-controlled notebook content to steal authentication tokens with a single click.
An attacker can craft a malicious notebook file containing elements that appear indistinguishable from legitimate controls and trigger execution when a user interacts with them. Successful exploitation allows theft of the user's authentication token and complete takeover of the Jupyter session through the REST API, including reading files, creating or modifying files, accessing kernels to execute arbitrary code, and creating terminals for shell access. This issue has been fixed in Notebook 7.5.6, JupyterLab 4.5.7, @jupyter-notebook/help-extension 7.5.6, and @jupyterlab/help-extension 4.5.7. As a workaround, disable the affected help extensions or set allowCommandLinker to false in the sanitizer configuration. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. Prior to version 4.4.8, links generated with LaTeX typesetters in Markdown files and Markdown cells in JupyterLab and Jupyter Notebook did not include the noopener attribute. This is deemed to have no impact on the default installations. Theoretically users of third-party LaTeX-rendering extensions could find themselves vulnerable to reverse tabnabbing attacks if links generated by those extensions included target=_blank (no such extensions are known at time of writing) and they were to click on a link generated in LaTeX (typically visibly different from other links). This issue has been patched in version 4.4.8. |
