VulnerabilityPublished 15 May 2026Updated 8 Sep 2026

CVE-2026-42266: JupyterLab has an Extension Manager API/GUI Policy Discrepancy allowing 3rd party (malicious)

Affects jupyterlabSource GCVE Database

Not known to be exploited : upgrade to 4.5.7 soon.

Data as of 26 Oct 2026, 17:16 UTC

Severity

High

Rated by Threat Radar · No CVSS score from NVD or the CNA

EPSS: 5.6% chance of exploitation in 30 days – higher than 92% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 4.5.7

Exploitation evidence

Disclosed: evidence found.
CVE published 15 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade jupyterlab to 4.5.7.

Affected software

Product	Affected	Fixed in
Bitnamijupyterlab`pkg:bitnami/jupyterlab`Other threats	Affected >=4.0.0 <4.5.7	Fixed in 4.5.7

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Upgrade JupyterLab to version 4.5.7 or later, where the vulnerability is fixed. Alternatively, configure the JupyterLab extension manager to read-only mode to prevent installation of unauthorized extensions. Note that using a PyPI proxy with an allow list is insufficient to mitigate this vulnerability. Follow vendor advisories for detailed remediation steps.

Description

JupyterLab versions from 4.0.0 up to but not including 4.5.7 contain a vulnerability in the PyPI Extension Manager that fails to enforce the allow-list of approved extensions. This flaw allows installation of unauthorized third-party extensions from sources outside the default PyPI index. Exploitation could lead to arbitrary code execution and significant system compromise. The issue is fixed in version 4.5.7. Mitigation includes upgrading to 4.5.7 or later and setting the extension manager to read-only mode to prevent unauthorized extension installation.

Impact

Exploitation of this vulnerability allows an attacker to install malicious extensions that can execute arbitrary code within the JupyterLab environment. This can lead to full system compromise including unauthorized data access, modification, and disruption of availability. The impact is rated high due to the potential for significant system compromise without requiring user interaction and with low privilege requirements.

Summary

JupyterLab's PyPI Extension Manager, responsible for installing extensions, does not correctly enforce its allow-list of approved extensions in versions >=4.0.0 and <4.5.7. This allows attackers to install unauthorized extensions from external sources beyond the default PyPI index. The vulnerability could lead to arbitrary code execution and significant compromise of the JupyterLab environment. The flaw is addressed in version 4.5.7. Red Hat's advisory highlights the risk in their products that utilize JupyterLab, such as OpenShift AI and Migration Toolkit for Applications.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 12 Sep 2026, 20:01 UTC

Technical details

References

Community reviews

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