CVE-2026-73417 (GCVE-0-2026-73417)
Vulnerability from cvelistv5 – Published: 2026-08-13 22:04 – Updated: 2026-08-14 16:06
VLAI
EPSS
VEX
Title
JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)
Summary
jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 3.3.0 until 4.5.10 and 4.6.2, JupyterLab allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor. In packages/notebook-extension/schema/tracker.json and packages/notebook-extension/src/index.ts, the sideBySideLeftMarginOverride and sideBySideRightMarginOverride settings are not properly validated before being inserted into style content, allowing a crafted settings file to contain instructions that execute as code instead of only changing display preferences. A user can import the malicious file, or an attacker with access to a shared settings location can plant an overrides.json that is applied automatically. The embedded code runs with the affected user's access and can read or modify notebooks and files and run code through the notebook server, including on a connected kernel. This issue is fixed in versions 4.5.10 and 4.6.2.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-14 16:06 UTC
CWE
Assigner
References
10 references
| URL | Tags |
|---|---|
| https://github.com/jupyterlab/jupyterlab/security… | x_refsource_CONFIRM |
| https://github.com/jupyterlab/jupyterlab/pull/19184 | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/pull/19185 | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/pull/19186 | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/commit/9… | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/commit/b… | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/commit/f… | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/releases… | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/releases… | x_refsource_MISC |
| https://github.com/jupyterlab/jupyterlab/releases… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| jupyterlab | jupyterlab |
Affected:
>= 3.3.0, < 4.5.10
Affected: >= 4.6.0, < 4.6.2 |
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"discovery": "UNKNOWN"
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"title": "JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)"
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"redhat_vex": {
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"cve": "CVE-2026-73417",
"id": "CVE-2026-73417",
"initial_release_date": "2026-08-13T22:04:31.709000+00:00",
"product_status:known_affected": "17",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "jupyterlab: JupyterLab: Cross-site scripting (XSS) allows arbitrary code execution",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-73417.json",
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"id": "CVE-2026-73417",
"initial_release_date": "2026-08-13T16:21:47Z",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2026-73417",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2026-73417.json",
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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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
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
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.
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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