How severe is CVE-2026-73416?

No CVSS score has been assigned to CVE-2026-73416 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by CVE-2026-73416?

CVE-2026-73416 affects the following packages: jupyterlab (PyPI), jupyterlab (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2026-73416?

Update jupyterlab to 4.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-73416 is resolved across your whole dependency graph.

How do I detect CVE-2026-73416 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-2026-73416 if there is no patch (or I can't update yet)?

Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Is CVE-2026-73416 actively exploited in the wild?

No public exploit code has been indexed for CVE-2026-73416 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-2026-73416?

CVE-2026-73416 has an EPSS (Exploit Prediction Scoring System) score of 0.7%, placing it in the 50th 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-2026-73416?

CVE-2026-73416 is classified as CWE-178 (CWE-178), CWE-180 (CWE-180). These weakness types describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2026-73416 published, and has it been updated?

CVE-2026-73416 was published on August 13, 2026 and was last updated on September 20, 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

CVE-2026-73416 — jupyterlab

Fix: jupyterlab/jupyterlab@9365f02

CVE-2026-73416 is a CWE-178 vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.

jupyterlab: PyPI extension blocklist package-name canonicalization bypass

Also known asBIT-jupyterlab-2026-73416GHSA-89vp-jrxv-24w8PYSEC-2026-3670

Published

Aug 13, 2026

Updated

Sep 20, 2026

Affected

2 pkgs

Patched

2 / 2

Exploits

None indexed

Exploitation data as of Sep 27, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

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-2026-73416.

EPSS Exploitation Probability

via FIRST.org ↗

0.7%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs50th percentile — riskier than 50% of all scored CVEsHighest risk

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

Real-World Exposure

2 pkgs affected

🐍jupyterlab🐍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

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:

Affected Packages

2 total 2 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`jupyterlab`	≥ 4.6.0&&< 4.6.2	4.6.2`pip install --upgrade 'jupyterlab==4.6.2'`
🐍PyPI	`jupyterlab`	≥ 4.5.0&&< 4.5.10	4.5.10`pip install --upgrade 'jupyterlab==4.5.10'`

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 4.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-73416 is resolved across your whole dependency graph.
Workarounds
Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

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 HatModerate

A Moderate impact flaw in JupyterLab's PyPI extension manager allows an authenticated user to bypass extension blocklists. This is due to weak package-name canonicalization, enabling the installation of prohibited extensions by using alternative spellings. This affects the integrity and availability of JupyterLab…

Workaround published by Red Hat

Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.

Source: Red Hat security advisory for CVE-2026-73416 (CC BY 4.0)

Frequently Asked Questions

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