Description

A Markdown file or a notebook output can carry a button that runs a JupyterLab command. Since 4.5.7 the first click on such a button opens a prompt naming the command, with Cancel, Run Once and Trust. Choosing Trust runs the command and marks the document trusted, so its later buttons run without a prompt.

Which document gets marked is decided when the user answers, not when they click. Both trust commands read whichever document is current at that moment: markdownviewer:trust uses tracker.currentWidget, and notebook:trust uses the equivalent lookup. If another document becomes current while the prompt is open, that document is the one marked trusted, and the one the user was looking at stays untrusted.

Users are affected if all of the following are true:

- they run JupyterLab 4.5.7 through 4.6.3, or an application that bundles it such as Notebook 7.5+; - they open a Markdown file or notebook from someone else and click a button in it; - they answer Trust rather than Cancel or Run Once; and - a second document becomes the current one while the prompt is open, for example through a workspace restoring at startup, an extension activating a widget, or a command that opens a file

Impact

The user loses control over which document they trusted. Every button in the document that was (incorrectly) marked as trusted runs from then on without a prompt, so if that document also came from an untrusted source, its buttons fire on a single click with no confirmation. That is the state the prompt was added to prevent, in GHSA-mqcg-5x36-vfcg.

The command that ran had the user's consent, because the prompt named it and they pressed Trust. The document they were reading stays untrusted, so it prompts again on the next click.

Notebooks are written to disk

When the document marked is a notebook, the effect outlives the browser session. notebook:trust marks every cell trusted and then saves the file, which results in the server signing it, so the notebook stays trusted when it is next opened. The save also writes out any unsaved edits in that notebook. A second confirmation appears first, but it says only that a trusted notebook may execute hidden code, without naming the file, so it does not show the user which notebook is about to be trusted.

A Markdown preview marked this way stays trusted only until it is closed. Nothing is written to disk.

Patches

JupyterLab v4.6.4 and v4.5.11 contain the patch. The trust request now carries the document that was clicked, and the command is run only once that same document has been marked.

Users of applications that depend on JupyterLab, such as Notebook v7+, should update jupyterlab package too.

Workarounds

Given the high complexity of a potential exploit, we advise treating this as a defense in-depth and update at earliest opportunity, rather than apply the workarounds listed below. However, for users running in highly sensitive environments who are unable to upgrade the workarounds are included below.

Turn off command linker, which removes the ability to execute frontend commands altogether:

json { "@jupyterlab/apputils-extension:sanitizer": { "allowCommandLinker": false } }

In such configuration the buttons in Markdown files and notebook outputs then do nothing when clicked. Documentation and extensions that use command links for navigation stop working, and the setting applies to every document, not only untrusted ones.

If disabling that setting is not desirable and update is not possible, advise users to choose "Run Once" rather than "Trust". "Run Once" makes the command run but no document is marked, so nothing can be trusted in error.

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.

Description

JupyterLab 4.5.0 enabled copying and pasing cells through the system clipboard. The paste path parses clipboard text as cell JSON and inserts the cells without clearing metadata.trusted, so a payload can declare its own output as trusted. JupyterLab does not sanitize a trusted output and evaluates the <script> elements it contains, so pasting the cell runs attacker's JavaScript in the JupyterLab origin. The same payload with "trusted": false is sanitized.

json [ { "celltype": "code", "executioncount": null, "source": "", "metadata": { "trusted": true }, "outputs": [ { "outputtype": "displaydata", "metadata": {}, "data": { "text/html": "<script>/ runs on paste /</script>" } } ] } ]

Users are affected if all of the following are true:

- they run JupyterLab 4.5.0 through 4.6.3, or an application that bundles it such as Notebook 7.5+; - if running 4.5.2 or newer, useSystemClipboardForCells is enabled - it is off by default in 4.5.2+, and always enabled on 4.5.0 and 4.5.1 with no opt-out - they run a Paste Cells command (e.g. from context menu, command palette, shortcut) while attacker-controlled text is in the clipboard; and - pasteCodeCellsWithoutOutput is off, the default, so the pasted cell keeps its outputs

Impact

The script runs in the JupyterLab page, in the same origin and session as the authenticated user, so it can call the Jupyter Server REST API as that user: read and write any file under the server root, start a kernel and run code in it, and open a terminal where terminals are enabled. It runs on paste, without the user executing anything.

Only the output of a code cell can run a script this way. Markdown and raw cells are always sanitized, as the trust documentation states.

The attacker needs no JupyterLab account and no access to the server, only the user's clipboard at the moment of the paste. A web page can replace the text you copy from it, or write the clipboard directly once you have given it permission. Both need you to click or press a key on that page first.

Patches

JupyterLab v4.6.4 and v4.5.11 contain the patch. Cells read from the system clipboard that cannot be traced to the current window no longer carry metadata.trusted into the notebook, so their outputs are sanitized like any other content of unknown origin.

Users of applications that depend on JupyterLab, such as Notebook v7+, should update jupyterlab package too.

Workarounds

On 4.5.2 and later, confirm that the system clipboard is not in use for cells. The setting is off by default; check Settings, Notebook, or the raw value:

json { "@jupyterlab/notebook-extension:tracker": { "useSystemClipboardForCells": false } }

With that setting off, cell copy and paste use JupyterLab's in-application clipboard, which never leaves the page. The cost is that cells can no longer be copied between browser tabs or windows.

On 4.5.0 and 4.5.1 there is no such setting, and every paste reads the system clipboard and upgrade is highly recommended.

Pasting cells without their outputs also stops the script from running, at the cost of discarding outputs on every paste:

json { "@jupyterlab/notebook-extension:tracker": { "pasteCodeCellsWithoutOutput": true } }

Description

A language pack ships a Plural-Forms header saying how the language counts, for example nplurals=2; plural=(n != 1);. JupyterLab turns that string into a function with new Function, so the header gets executed. The check that meant to keep it safe was a regular expression. The regex was anchored at the start but not at the end, so it accepted any string that began with a valid plural rule and ignored everything after it.

A header such as the following passed the check, and the part after the plural rule ran in the JupyterLab page as soon as the first plural string was translated:

nplurals=2; plural=(n > 1); <anything here ran as JavaScript>

Users are affected if all of the following are true:

- they run JupyterLab 3.0.0 through 4.6.3, or an application that bundles it such as Notebook 7; - a language pack they did not write is installed in the environment; and - that language is selected, so its catalogue is loaded

An installation using the default English locale loads no catalogue and is not affected.

CVE assignment pending, GitHub CNA is experiencing severe backlog

Impact

The code in the header ran in the JupyterLab page, in the same origin and session as the authenticated user. It could call the Jupyter Server REST API as that user: read and write any file under the server root, start a kernel and run code in it, and open a terminal where terminals are enabled. Nothing had to be clicked; translating one plural string was enough, and that happens during normal use of the interface.

What this changes is who has to be trusted. A language pack is a Python package, and installing one is already a privileged act, so an attacker who can get any package installed has server-side code execution regardless of this issue. The header is different because it is catalogue metadata: it travels with translation content, through the translation pipeline that carries strings from Crowdin into the language packs, and it is reviewed as text rather than as code. Anyone able to change a catalogue, or to publish a pack under a name someone installs, got JavaScript execution in every browser that selected that language.

Note: the impact is much more limited on JupyterLite which typically does not have access to most of the surfaces that this flaw exposes.

Patches

JupyterLab v4.6.4 and v4.5.11 contain the patch. The check now has to match the whole header, so a plural rule followed by anything else is rejected and no function is built from it.

JupyterLab 3.x reached end of life and receives no patch. Its users should move to a supported 4.x release.

Users of applications that depend on JupyterLab, such as Notebook v7+, should update jupyterlab package too.

Workarounds

Use the English locale, which loads no catalogue:

bash jupyter lab --LabApp.defaultlocale=en

or the following traitlet:

python c.LabApp.defaultlocale = 'en'

Everyone then sees the interface in English, whatever language they had selected.

To check what is installed instead of switching, report any pack whose header carries more than a plural rule:

bash python -c " import re from jupyterlabserver.translationutils import getlanguagepacks, getlanguagepack ok = re.compile(r'\snplurals\s=\s\d+\s;\splural\s=[\s\-?|&=!<>+/%:;n0-9()]+') packs, = getlanguagepacks() for locale in packs: data, = getlanguagepack(locale) for domain, catalog in (data or {}).items(): header = catalog.get('', {}).get('pluralforms') if header and not ok.fullmatch(header): print('SUSPECT', locale, domain, repr(header)) "

The command prints nothing when every catalogue is sound. A line of output names the pack to remove.

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 blockedextensionsuris 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 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 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 isinstallallowed 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. 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 (allowedextensionsuris) 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 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.

Impact

The vulnerability depends on user interaction by opening a malicious notebook with Markdown cells, or Markdown file using JupyterLab preview feature.

A malicious user can access any data that the attacked user has access to as well as perform arbitrary requests acting as the attacked user.

Patches

JupyterLab v4.0.11 was patched.

Workarounds

Users can either disable the table of contents extension by running:

bash jupyter labextension disable @jupyterlab/toc-extension:registry

References

Vulnerability reported via the bug bounty program sponsored by the European Commission and hosted on the Intigriti platform.

Impact Users of JupyterLab who click on a malicious link may get their Authorization and XSRFToken tokens exposed to a third party when running an older jupyter-server version.

Patches JupyterLab 4.1.0b2, 4.0.11, and 3.6.7 were patched.

Workarounds No workaround has been identified, however users should ensure to upgrade jupyter-server to version 2.7.2 or newer which includes a redirect vulnerability fix.

References

Vulnerability reported by user @davwwwx via the bug bounty program sponsored by the European Commission and hosted on the Intigriti platform.