Open-Source Security Intelligence

Know every vulnerability
before it knows you.

DevGuard continuously monitors your dependencies and alerts you when CVEs like this one affect your stack — with real-time threat intelligence built for developers.

Search

GHSA-89vp-jrxv-24w8

MediumCVSS 6.1 / 10
Published Jul 22, 2026·Last modified Jul 22, 2026
Affected Components(0)

No affected components available

Description

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:

<img width="293" height="293" alt="image" src="https://github.com/user-attachments/assets/8016c809-633e-4ed0-a5bc-6bc4793caa0f" />
Risk Scores
Base Score
6.1

The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability.

Threat Intelligence
2.4

Limited exploitation activity has been observed. Close monitoring and planned remediation are recommended.

EPSS
N/A

Probability that this vulnerability will be exploited in the wild within the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

Browse More

Scan your project

Continuously monitor your dependencies and get alerted when vulnerabilities like this one affect your stack.

Checkout DevGuard