How severe is CVE-2026-42266?

CVE-2026-42266 has a CVSS score of 8.8/10, rated HIGH. Immediate patching is strongly recommended.

Which packages are affected by CVE-2026-42266?

CVE-2026-42266 affects the following packages: jupyterlab (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2026-42266?

Update jupyterlab to 4.5.7 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-42266 is resolved across your whole dependency graph.

How do I detect CVE-2026-42266 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlab, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2026-42266 if there is no patch (or I can't update yet)?

If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Is CVE-2026-42266 actively exploited in the wild?

No public exploit code has been indexed for CVE-2026-42266 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2026-42266?

CVE-2026-42266 has an EPSS (Exploit Prediction Scoring System) score of 5.7%, placing it in the 93th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2026-42266?

CVE-2026-42266 is classified as CWE-88 (CWE-88), CWE-602 (CWE-602). These weakness types describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2026-42266 published, and has it been updated?

CVE-2026-42266 was published on May 13, 2026 and was last updated on November 6, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍

🐍 PyPI

Not in CISA KEV

HIGH severity

CVE-2026-42266 — jupyterlab

HIGH

CVE-2026-42266 is a high-severity (CVSS 8.8) CWE-88 vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.

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

Also known asBIT-jupyterlab-2026-42266GHSA-37w4-hwhx-4rc4PYSEC-2026-164

Published

May 13, 2026

Updated

Nov 6, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Nov 6, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

A successful exploit gives an attacker total control of the affected component, not partial access.
CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-42266.

EPSS Exploitation Probability

via FIRST.org ↗

5.7%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs93th percentile — riskier than 93% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

1 pkg affected

🐍jupyterlab

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

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

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`jupyterlab`	≥ 4.0.0&&< 4.5.7	4.5.7`pip install --upgrade 'jupyterlab==4.5.7'`

Affected Products

1 product · 1 configurations

Application

jupyterlabjupyter

≥ 4.0.0 && < 4.5.7

range

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlab, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update jupyterlab to 4.5.7 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-42266 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatImportant

This Important flaw in JupyterLab, as utilized in Red Hat OpenShift AI and Migration Toolkit for Applications, stems from the PyPI Extension Manager's failure to enforce its extension allow-list. This enables the installation of unauthorized extensions from external sources, potentially leading to arbitrary code…

Workaround published by Red Hat

Upgrade JupyterLab to version 4.5.7 or later. Set the JupyterLab extension manager to read-only mode to prevent users from installing unauthorized extensions. Note: configuring a PyPI proxy with an allow list of packages is not sufficient to protect against this vulnerability.

Source: Red Hat security advisory for CVE-2026-42266 (CC BY 4.0)

Product	Fixed in	Advisory
Red Hat Migration Toolkit for Applications 8.2	`mta/mta-solution-server-rhel9:1784109883`	RHSA-2026:43038
Red Hat OpenShift AI 3.4	`rhoai/odh-th06-cpu-torch210-py312-rhel9:1787076778`	RHSA-2026:60520

Frequently Asked Questions

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 f