chore: 🔨 Update dependency jupyterlab to v4.5.10 [SECURITY]

[renovate]

This PR contains the following updates:

Package	Change	Age	Confidence
jupyterlab (changelog)	4.5.6 → 4.5.10

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Jupyter Notebook Vulnerable to Authentication Token Theft via CommandLinker XSS

CVE-2026-40171 / GHSA-rch3-82jr-f9w9

More information

Details

Impact

A stored Cross-Site Scripting (XSS) vulnerability in Jupyter Notebook allows attackers to steal authentication tokens from users who open malicious notebook files and interact with elements that the attacker can make look indistinguishable from legitimate controls (single click interaction).

The vulnerability enables complete account takeover through the Jupyter REST API, allowing the attacker to:

1. Read all files
2. Modify/create files
3. Access running kernels and execute arbitrary code
4. Create terminals for shell access

Patches

Jupyter Notebook 7.5.6 and JupyterLab 4.5.7 include patches for this vulnerability.

Workarounds

The help extension can be disabled via CLI:

jupyter labextension disable @​jupyter-notebook/help-extension
jupyter labextension disable @​jupyterlab/help-extension

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

• https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-output-and-files

Acknowledgments

Reported by Daniel Teixeira - NVIDIA AI Red Team

Severity

• CVSS Score: 8.4 / 10 (High)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

References

• https://github.com/jupyter/notebook/security/advisories/GHSA-rch3-82jr-f9w9
• https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-output-and-files
• https://nvd.nist.gov/vuln/detail/CVE-2026-40171
• https://github.com/advisories/GHSA-rch3-82jr-f9w9

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab has an Extension Manager API/GUI Policy Discrepancy, allowing 3rd party (malicious) extensions install via POST request

CVE-2026-42266 / GHSA-37w4-hwhx-4rc4

More information

Details

The allow-list of extensions that can be installed from PyPI Extension Manager (allowed_extensions_uris) is not correctly enforced by JupyterLab prior to 4.5.7. The PyPI Extension Manager was not contained to packages listed on the default PyPI index.

This has security implications for deployments that:

• have allow-listed specific extensions with aim to prevent users from installing packages
• have the kernel and terminals disabled or delegated to remote hosts (thus no access to install packages in the single-user server environment)
• have multi-tenant deployments that is not configured for untrusted users (as per documented on JupyterHub https://jupyterhub.readthedocs.io/en/5.2.1/explanation/websecurity.html)
• have the (default) PyPI Extension Manager enabled

Impact

An authenticated attacker - such as a student in a shared JupyterHub environment or a user in a multi-tenant JupyterLab deployment - can escalate their privileges. This might allow for data exfiltration, lateral movement within the network, and persistent compromise of the server infrastructure.

Patches

JupyterLab v4.5.7 contains the patch.

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

Workarounds

Switch to read-only extension manager by adding the following command line option:

--LabApp.extension_manager=readonly

or the following traitlet:

c.LabApp.extension_manager = 'readonly'

You can confirm that the read-only manager is in use from GUI:

Note: configuration of a PyPI proxy with allow-listed packages is not sufficient to protect from this vulnerability.

References

• allow-list https://jupyterlab.readthedocs.io/en/stable/user/extensions.html#listing-configuration
• https://jupyterhub.readthedocs.io/en/5.2.1/explanation/websecurity.html
• https://jupyterlab.readthedocs.io/en/latest/user/extensions.html#extension-manager-implementations

Severity

• CVSS Score: 8.8 / 10 (High)
• Vector String: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-37w4-hwhx-4rc4
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.7
• https://jupyterhub.readthedocs.io/en/5.2.1/explanation/websecurity.html
• https://jupyterlab.readthedocs.io/en/latest/user/extensions.html#extension-manager-implementations
• https://nvd.nist.gov/vuln/detail/CVE-2026-42266
• https://github.com/pypa/advisory-database/tree/main/vulns/jupyterlab/PYSEC-2026-164.yaml
• https://github.com/advisories/GHSA-37w4-hwhx-4rc4

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab's command linker attributes in HTML enable one-click command execution from untrusted content

CVE-2026-42557 / GHSA-mqcg-5x36-vfcg

More information

Details

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

• https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-files

Severity

• CVSS Score: 8.6 / 10 (High)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-mqcg-5x36-vfcg
• https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-files
• https://nvd.nist.gov/vuln/detail/CVE-2026-42557
• https://github.com/advisories/GHSA-mqcg-5x36-vfcg

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab: Stored XSS in extension manager through package metadata unsanitized URI protocol

GHSA-vmhf-c436-hxj4

More information

Details

A malicious PyPI package can place a javascript: URL in its [project.urls] metadata. JupyterLab's Extension Manager renders this as the extension's home-page link without validating the protocol, so a user who clicks the extension name executes attacker-controlled JavaScript in the JupyterLab origin.

Details

One of the PyPI package's URL (jupyterlab/extensions/pypi.py) is copied straight into the homepage_url rendered by the frontend in packages/extensionmanager/src/widget.tsx#L77-L88.

best_guess_home_url = (
    homepage_url            # home_page / [project.urls] Homepage
    or data.get("project_url")
    or data.get("package_url")
    or documentation_url    # docs_url / [project.urls] Documentation
    or source_url           # [project.urls] Source Code
    or bug_tracker_url      # bugtrack_url / [project.urls] Bug Tracker
)

##### homepage_url=best_guess_home_url

{entry.homepage_url ? (
  <a href={entry.homepage_url} target="_blank" rel="noopener noreferrer" ...>
    {entry.name}
  </a>
) : ( <div>{entry.name}</div> )}

Impact

An attacker needs to publish a package to PyPI (no access to the target). When the package appears in a victim's extension manager list and the victim clicks the extension name, the payload runs in the JupyterLab origin.

Preconditions: Extension Manager enabled with the default PyPI source, the malicious package appears in the victim's list/search results.

Patches

Patched in 4.5.9, commits 4e61e07 and d5d961f

Severity

• CVSS Score: 5.1 / 10 (Medium)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-vmhf-c436-hxj4
• https://github.com/jupyterlab/jupyterlab/commit/4e61e07d0a91145b53fbf96ac74b0387f6bc51f6
• https://github.com/jupyterlab/jupyterlab/commit/d5d961f6e10a6442dddbf94d9a976b3897055a12
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.9
• https://github.com/advisories/GHSA-vmhf-c436-hxj4

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab: PyPI extension blocklist package-name canonicalization bypass

GHSA-89vp-jrxv-24w8

More information

Details

JupyterLab's PyPI extension manager enforces blocked_extensions_uris by comparing the requested install name to blocklist entries with a custom string 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; JupyterLab accepts the install request even though pip resolves the variant to the same package.

This has security implications only for deployments that combine all of the following:

• an allowlist/blocklist configured with the intent of restricting which packages users can install;
• the (default) PyPI Extension Manager enabled; and
• kernels and terminals disabled or delegated to remote hosts (otherwise a user with kernel access can install packages directly regardless of this check)

Impact

The vulnerability lets an authenticated user install a package the operator specifically intended to block, defeating the allowlist/blocklist control. Because extensions in principle allow for arbitrary code execution, this vulnerability enables untrusted users to impact the integrity and availability of the jupyter-server instance that was provisioned to them. The user already has access to their own single-user server's data, so installing an extension grants no new read access.

In particular, the integrity of data can be impacted, and any hardening or restrictions on permitted user actions (download/upload limits) within the single-user server can be circumvented. Availability impact on a JupyterHub deployment is limited: while a user can be expected to exhaust their own kernel pod's resources, this vulnerability makes it easier to also exhaust the single-user server resources or generate more requests to shared resources; where limits are absent, resource exhaustion could potentially degrade the wider deployment.

Patches

JupyterLab v4.6.2 and v4.5.10 contain the patch.

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

Workarounds

No action is required for deployments that do not have a custom allow/block list configured. Deployments wanting to disable programmatic extension installation entirely can switch to the read-only extension manager:

--LabApp.extension_manager=readonly

or the following traitlet:

c.LabApp.extension_manager = 'readonly'

You can confirm that the read-only manager is in use from GUI:

Severity

• CVSS Score: 6.1 / 10 (Medium)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:H/VA:L/SC:N/SI:N/SA:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-89vp-jrxv-24w8
• https://github.com/jupyterlab/jupyterlab/pull/19184
• https://github.com/jupyterlab/jupyterlab/pull/19185
• https://github.com/jupyterlab/jupyterlab/pull/19186
• https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
• https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
• https://github.com/advisories/GHSA-89vp-jrxv-24w8

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab PluginManager lock-rule enforcement bypass

GHSA-h5v5-8746-g7mm

More information

Details

JupyterLab's plugin manager exposes administrator controls intended to prevent users from enabling or disabling selected plugins. Two server-side enforcement gaps let an authenticated user bypass those controls with direct requests to /lab/api/plugins.

Impact

Users could workaround the plugin manager lock rules via direct API access for either:

• child plugins of extensions covering multiple plugins
• when "lock all" was issued by the administrator

The integrity of data can be impacted, and any hardening or restrictions on permitted user actions (e.g. download/upload limits) within the single-user server can be circumvented if those were implemented with plugins that were locked using the faulty mechanisms.

Patches

JupyterLab v4.6.2 and v4.5.10 contain the patch.

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

Workarounds

Manually lock all plugins that should be locked. The core plugin identifiers can be found in the documentation and identifiers for all installed extensions are listed in the Plugin Manager.

Severity

• CVSS Score: 6.0 / 10 (Medium)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:H/VA:N/SC:N/SI:N/SA:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-h5v5-8746-g7mm
• https://github.com/jupyterlab/jupyterlab/pull/19184
• https://github.com/jupyterlab/jupyterlab/pull/19185
• https://github.com/jupyterlab/jupyterlab/pull/19186
• https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
• https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
• https://github.com/advisories/GHSA-h5v5-8746-g7mm

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab: Cross-site scripting (XSS) via crafted settings file (overrides.json)

GHSA-pppj-hq3g-57pj

More information

Details

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

1. 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.
2. 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.

Severity

• CVSS Score: 8.6 / 10 (High)
• Vector String: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-pppj-hq3g-57pj
• https://github.com/jupyterlab/jupyterlab/pull/19184
• https://github.com/jupyterlab/jupyterlab/pull/19185
• https://github.com/jupyterlab/jupyterlab/pull/19186
• https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
• https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
• https://github.com/advisories/GHSA-pppj-hq3g-57pj

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab: Image viewer allows XSS when opening malicious image in new browser tab

GHSA-gx64-gj6p-pc4c

More information

Details

JupyterLab's image viewer allows for cross-site scripting (XSS) when a specially-crafted image file is opened through the image viewer and then opened in a new tab. This XSS issue can be used to cause remote code execution (RCE) on the JupyterLab server.

Impact

This vulnerability allows for arbitrary code execution.

Patches

JupyterLab v4.6.2 and v4.5.10 contain the patch.

Workarounds

Disable the image viewer plugin:

jupyter labextension disable @​jupyterlab/imageviewer-extension:plugin

Confirm with:

jupyter labextension list

Severity

• CVSS Score: 7.5 / 10 (High)
• Vector String: CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-gx64-gj6p-pc4c
• https://github.com/jupyterlab/jupyterlab/pull/19184
• https://github.com/jupyterlab/jupyterlab/pull/19185
• https://github.com/jupyterlab/jupyterlab/pull/19186
• https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
• https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
• https://github.com/advisories/GHSA-gx64-gj6p-pc4c

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

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JupyterLab: Allowlist/blocklist check in PyPIExtensionManager.install() not enforced for direct callers (missing await)

GHSA-whvh-wf3x-g77j

More information

Details

The extension allowlist/blocklist check inside PyPIExtensionManager.install() was not enforced due to a missing await. For purposes of JupyterLab this was a secondary defense-in-depth check: install() was intended to enforce the allowlist/blocklist itself for any future uses and users calling this method directly (in addition to the separate check handling requests arriving through the HTTP API). The only runtime symptom was a RuntimeWarning: coroutine 'is_install_allowed' was never awaited.

This has security implications only for deployments that combine all of the following:

• a custom extension or downstream integration that imports PyPIExtensionManager and calls install() directly with a package name influenced by untrusted user input (the stock JupyterLab HTTP handler is not affected - it performs its own awaited allowlist check before calling install());
• an allowlist/blocklist configured with the intent of restricting which packages users can install;
• the (default) PyPI Extension Manager enabled; and
• kernels and terminals disabled or delegated to remote hosts, so that the custom extension's install() call is the only available package-install vector (otherwise a user with kernel access can install packages directly regardless of this check)

Impact

Low. No exposure for stock JupyterLab: the HTTP API and Extension Manager UI enforce the listing through a separate, correctly awaited check. The gap affected only custom extensions or downstream integrations that called the public install() method directly and relied on it to self-enforce.

Patches

JupyterLab v4.6.2 and v4.5.10 contain the patch.

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

Workarounds

No action is required for deployments that only expose extension management through the JupyterLab HTTP API / Extension Manager UI, as that path was already enforcing the listing via the handler's own check. Deployments wanting to disable programmatic extension installation entirely can switch to the read-only extension manager:

--LabApp.extension_manager=readonly

or the following traitlet:

c.LabApp.extension_manager = 'readonly'

You can confirm that the read-only manager is in use from GUI:

Severity

• CVSS Score: 0.0 / 10 (Low)
• Vector String: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:N

References

• https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-whvh-wf3x-g77j
• https://github.com/jupyterlab/jupyterlab/pull/19184
• https://github.com/jupyterlab/jupyterlab/pull/19185
• https://github.com/jupyterlab/jupyterlab/pull/19186
• https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c
• https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10
• https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2
• https://github.com/advisories/GHSA-whvh-wf3x-g77j

This data is provided by the GitHub Advisory Database (CC-BY 4.0).

---

Release Notes

jupyterlab/jupyterlab (jupyterlab)

v4.5.10

Compare Source

4.5.10

(Full Changelog)

Security patches

• GHSA-gx64-gj6p-pc4c
• GHSA-89vp-jrxv-24w8
• GHSA-h5v5-8746-g7mm
• GHSA-pppj-hq3g-57pj
• GHSA-whvh-wf3x-g77j

Bugs fixed

• Backport of security patches to 4.5.x branch #​19186 (@​krassowski, @​MUFFANUJ)

Maintenance and upkeep improvements

• Reconfigure 4.5.x branch (4.6.x is new stable) #​19060 (@​krassowski)
• Split external link checks and only run if diff includes a URL #​19029 (@​MUFFANUJ)

Contributors to this release

The following people contributed discussions, new ideas, code and documentation contributions, and review.
See our definition of contributors.

(GitHub contributors page for this release)

@​krassowski (activity) | @​MUFFANUJ (activity)

v4.5.9

Compare Source

4.5.9

(Full Changelog)

Bugs fixed

• Fix jupyter labextension build crash on webpack ≥ 5.107 #​19021 (@​Darshan808, @​krassowski)
• Backport PR #​18992: Fix hidden cells after moving collapsed headings #​19016 (@​MUFFANUJ, @​krassowski)
• Forbid relative URLs in extensionmanager #​19013 (@​Yann-P)
• Fix XSS in extension manager's homepage_url #​19003 (@​Yann-P)
• Fix toolbar popup row clipping in Safari #​18998 (@​arun-357)

Contributors to this release

The following people contributed discussions, new ideas, code and documentation contributions, and review.
See our definition of contributors.

(GitHub contributors page for this release)

@​arun-357 (activity) | @​Darshan808 (activity) | @​krassowski (activity) | @​MUFFANUJ (activity) | @​Yann-P (activity)

v4.5.8

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4.5.8

(Full Changelog)

Bugs fixed

• Prevent dialog from hanging when getValue() throws #​18938 (@​AliMahmoudDev)
• Add packaging min version pin #​18910 (@​krassowski)
• Use CSS anchor for prompt overlay #​18840 (@​CrafterKolyan)

Maintenance and upkeep improvements

• Fix completer test failures on CI #​18946 (@​krassowski)
• Bump license webpack plugin #​18929 (@​Darshan808, @​krassowski)

Contributors to this release

The following people contributed discussions, new ideas, code and documentation contributions, and review.
See our definition of contributors.

(GitHub contributors page for this release)

@​AliMahmoudDev (activity) | @​CrafterKolyan (activity) | @​Darshan808 (activity) | @​krassowski (activity)

v4.5.7

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4.5.7

(Full Changelog)

Security patches

• CVE-2026-42557 GHSA-mqcg-5x36-vfcg
• CVE-2026-42266 GHSA-37w4-hwhx-4rc4
• CVE-2026-40171 GHSA-rch3-82jr-f9w9

Bugs fixed

• Video and Audio Content Providers: Fix JupyterLite support #​18652 (@​martinRenou)
• Fix notebook hang when dropping cells #​18808 (@​MUFFANUJ)
• Fix Contextual Help keyboard shortcut reliability and menu Help functionality #​18747 (@​itsmejay80)
• Fix focusing input element when opening a dialog from Command Palette #​18735 (@​Carreau)
• Fix native context menu blocked even when context menu is suppressed #​18753 (@​utsav-develops)
• Fix flaky toolbar item placement in popup #​18618 (@​filipeoliveira05)
• Update terminal default font family to honor macOS system-wide ui-monospace #​18647 (@​flaviomartins)

Maintenance and upkeep improvements

• Fix linting issue #​18819 (@​krassowski)
• Fix syntax for Python 3.9 on 4.5.x branch #​18817 (@​krassowski)
• Remove unused CodeMirror v5 CSS rule #​18785 (@​Carreau)
• Remove unused CSS rule forgotten after CodeMirror migration #​18763 (@​Carreau)
• Remove unused progress bar CSS rule in execution indicator #​18759 (@​Carreau)
• Remove dead .jp-VariableRenderer-TrustButton CSS rule #​18762 (@​Carreau)
• Remove used .jp-Cell-Placeholder CSS rules #​18761 (@​Carreau)

Documentation improvements

• Fix name of option for extension manager implementation in docs #​18788 (@​krassowski)
• Remove 4.5.0 announcement from docs #​18740 (@​krassowski)

Contributors to this release

The following people contributed discussions, new ideas, code and documentation contributions, and review.
See our definition of contributors.

(GitHub contributors page for this release)

@​Carreau (activity) | @​filipeoliveira05 (activity) | @​flaviomartins (activity) | @​itsmejay80 (activity) | @​jtpio (activity) | @​krassowski (activity) | @​martinRenou (activity) | @​MUFFANUJ (activity) | @​utsav-develops (activity)

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Quality Gate passed

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 97.70%. Comparing base (6bed9a6) to head (ec86c3b).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #2107   +/-   ##
=======================================
  Coverage   97.70%   97.70%           
=======================================
  Files          63       63           
  Lines        6246     6246           
=======================================
  Hits         6102     6102           
  Misses        144      144           

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unittests	97.70% <ø> (ø)

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[stale]

This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

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Quality Gate passed

Issues
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0 Accepted issues

Measures
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0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud