PYSEC-2026-2538
Vulnerability from pysec - Published: 2026-07-13 15:02 - Updated: 2026-07-13 16:04
VLAI
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
Impacted products
| Name | purl | jupyterlab | pkg:pypi/jupyterlab |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "jupyterlab",
"purl": "pkg:pypi/jupyterlab"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "4.5.7"
}
],
"type": "ECOSYSTEM"
}
],
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}
],
"aliases": [
"CVE-2026-40171",
"GHSA-rch3-82jr-f9w9"
],
"details": "### Impact\n\nA 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).\n\nThe vulnerability enables complete account takeover through the Jupyter REST API, allowing the attacker to:\n1. Read all files\n2. Modify/create files\n3. Access running kernels and execute arbitrary code\n4. Create terminals for shell access\n\n### Patches\n\nJupyter Notebook 7.5.6 and JupyterLab 4.5.7 include patches for this vulnerability.\n\n### Workarounds\n\nThe help extension can be disabled via CLI:\n\n```\njupyter labextension disable @jupyter-notebook/help-extension\njupyter labextension disable @jupyterlab/help-extension\n```\n\n### Hardening\n\nThe patched versions include a toggle to disable the command linker functionality altogether, for example via `overrides.json`:\n\n```json\n{\n \"@jupyterlab/apputils-extension:sanitizer\": {\n \"allowCommandLinker\": false\n }\n}\n```\n\n### Resources\n\n- https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-output-and-files\n\n### Acknowledgments\n\nReported by Daniel Teixeira - NVIDIA AI Red Team",
"id": "PYSEC-2026-2538",
"modified": "2026-07-13T16:04:23.956450Z",
"published": "2026-07-13T15:02:55.776849Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/jupyter/notebook/security/advisories/GHSA-rch3-82jr-f9w9"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40171"
},
{
"type": "PACKAGE",
"url": "https://github.com/jupyter/notebook"
},
{
"type": "WEB",
"url": "https://jupyterlab.readthedocs.io/en/latest/user/commands.html#commands-in-markdown-output-and-files"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/jupyterlab"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-rch3-82jr-f9w9"
}
],
"severity": [
{
"score": "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",
"type": "CVSS_V4"
}
],
"summary": "Jupyter Notebook Vulnerable to Authentication Token Theft via CommandLinker XSS"
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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