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CVE-2026-73417

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

8.6 HighFix available

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.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
Low
Privileges needed
None
User interaction
Active

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
Low

Exploit likelihood

0.75%Up 0.2 points since Aug 14, 2026
90%50%10%1%

What each source reports

CVE List Score used 8.6

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

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.

Record
CVE-2026-73417
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Weakness
CWE-79, CWE-116
Updated
2026-11-02
EUVDEUVD-2026-58522 8.6

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.

Record
EUVD-2026-58522
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Updated
2026-11-02
GitHub AdvisoriesGHSA-pppj-hq3g-57pj 8.6

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

JupyterLab 4.5+ allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor.

Certain notebook display settings were not properly validated before being applied. As a result, a crafted settings file could contain hidden instructions that run as code inside JupyterLab when imported, instead of only changing a display preference.

Because importing a settings file appears harmless, a user could import a file shared by another party without realizing it could do more. On multi-tenant file systems without proper permission control, another user could plant a malicious overrides.json.

CVE assignment pending, GitHub CNA is experiencing severe backlog

Impact

When a malicious settings file is applied, the embedded code runs with the same access as the affected user. This could allow an attacker to read or modify that user's notebooks and files, and to run code on the user's behalf through the notebook server, including on any connected kernel.

User Interaction vs Privileges Required

Write access to a loaded settings location

If an attacker can write to a directory JupyterLab loads settings from (e.g. on shared or multi-tenant file system), they could place a crafted overrides.json that is applied to another user automatically at startup. This requires high privilages but no action by the victim.

User-imported settings file

A user can import a crafted overrides.json through the Import button in the Settings Editor, having received it from another party. This requires no privileges but a deliberate action by the victim, who reasonably expects a settings file to change preferences rather than run code.

Patches

JupyterLab 4.6.2 and 4.5.10 were patched.

Workarounds

None

Hardening

  1. Treat a settings file as something that can affect how JupyterLab behaves, not only how it appears. Administrators are encouraged to establish a trusted process for distributing configuration rather than relying on ad-hoc importing of shared files.
  2. On multi-tenant or shared file systems, restrict write permissions on the application settings directory and other Jupyter configuration paths so that one user cannot place an overrides.json (or other configuration) readable by another user. A settings file in these locations is applied automatically, without an import step, so directory permissions are the primary control against cross-user tampering.
Record
GHSA-pppj-hq3g-57pj
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Weakness
CWE-79, CWE-116
Updated
2026-11-02
NVD 8.6

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.

Record
CVE-2026-73417
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Weakness
CWE-79, CWE-116
Updated
2026-11-02
OSV 8.6

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

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.

Record
CVE-2026-73417
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Weakness
CWE-116, CWE-79
Updated
2026-11-07
OSVDEBIAN-CVE-2026-73417 8.6

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.

Record
DEBIAN-CVE-2026-73417
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Updated
2026-11-02
Show 5 moreShow less
OSVGHSA-pppj-hq3g-57pj 8.6

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

JupyterLab 4.5+ allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor.

Certain notebook display settings were not properly validated before being applied. As a result, a crafted settings file could contain hidden instructions that run as code inside JupyterLab when imported, instead of only changing a display preference.

Because importing a settings file appears harmless, a user could import a file shared by another party without realizing it could do more. On multi-tenant file systems without proper permission control, another user could plant a malicious overrides.json.

CVE assignment pending, GitHub CNA is experiencing severe backlog

Impact

When a malicious settings file is applied, the embedded code runs with the same access as the affected user. This could allow an attacker to read or modify that user's notebooks and files, and to run code on the user's behalf through the notebook server, including on any connected kernel.

User Interaction vs Privileges Required

Write access to a loaded settings location

If an attacker can write to a directory JupyterLab loads settings from (e.g. on shared or multi-tenant file system), they could place a crafted overrides.json that is applied to another user automatically at startup. This requires high privilages but no action by the victim.

User-imported settings file

A user can import a crafted overrides.json through the Import button in the Settings Editor, having received it from another party. This requires no privileges but a deliberate action by the victim, who reasonably expects a settings file to change preferences rather than run code.

Patches

JupyterLab 4.6.2 and 4.5.10 were patched.

Workarounds

None

Hardening

  1. Treat a settings file as something that can affect how JupyterLab behaves, not only how it appears. Administrators are encouraged to establish a trusted process for distributing configuration rather than relying on ad-hoc importing of shared files.
  2. On multi-tenant or shared file systems, restrict write permissions on the application settings directory and other Jupyter configuration paths so that one user cannot place an overrides.json (or other configuration) readable by another user. A settings file in these locations is applied automatically, without an import step, so directory permissions are the primary control against cross-user tampering.
Record
GHSA-pppj-hq3g-57pj
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Weakness
CWE-116, CWE-79
Updated
2026-11-02
OSVPYSEC-2026-3672 8.6

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

JupyterLab 4.5+ allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor.

Certain notebook display settings were not properly validated before being applied. As a result, a crafted settings file could contain hidden instructions that run as code inside JupyterLab when imported, instead of only changing a display preference.

Because importing a settings file appears harmless, a user could import a file shared by another party without realizing it could do more. On multi-tenant file systems without proper permission control, another user could plant a malicious overrides.json.

CVE assignment pending, GitHub CNA is experiencing severe backlog

Impact

When a malicious settings file is applied, the embedded code runs with the same access as the affected user. This could allow an attacker to read or modify that user's notebooks and files, and to run code on the user's behalf through the notebook server, including on any connected kernel.

User Interaction vs Privileges Required

Write access to a loaded settings location

If an attacker can write to a directory JupyterLab loads settings from (e.g. on shared or multi-tenant file system), they could place a crafted overrides.json that is applied to another user automatically at startup. This requires high privilages but no action by the victim.

User-imported settings file

A user can import a crafted overrides.json through the Import button in the Settings Editor, having received it from another party. This requires no privileges but a deliberate action by the victim, who reasonably expects a settings file to change preferences rather than run code.

Patches

JupyterLab 4.6.2 and 4.5.10 were patched.

Workarounds

None

Hardening

  1. Treat a settings file as something that can affect how JupyterLab behaves, not only how it appears. Administrators are encouraged to establish a trusted process for distributing configuration rather than relying on ad-hoc importing of shared files.
  2. On multi-tenant or shared file systems, restrict write permissions on the application settings directory and other Jupyter configuration paths so that one user cannot place an overrides.json (or other configuration) readable by another user. A settings file in these locations is applied automatically, without an import step, so directory permissions are the primary control against cross-user tampering.
Record
PYSEC-2026-3672
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Updated
2026-11-02
OSVUBUNTU-CVE-2026-73417 8.6

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.

Record
UBUNTU-CVE-2026-73417
CVSS 4.0
8.6 HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L
Updated
2026-11-02
OSVBIT-jupyterlab-2026-73417 No score

JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)

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.

Record
BIT-jupyterlab-2026-73417
Updated
2026-11-02
OSVopenSUSE-SU-2026:11634-1 No score

jupyter-jupyterlab-4.5.10-1.1 on GA media

These are all security issues fixed in the jupyter-jupyterlab-4.5.10-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2026:11634-1
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
jupyterlab
PyPI
4.6.0 to 4.6.1
4.6.2
jupyterlab
PyPI
3.3.0 to 4.5.9
4.5.10
jupyterlab
Bitnami
3.3.0 up to 4.5.10, 4.6.0 up to 4.6.2
4.5.104.6.2
jupyterlab
Debian:13
All versions, plus listed versions
4.0.11+ds1+~cs11.25.27-74.0.11+ds1+~cs11.25.27-84.0.11+ds1+~cs11.25.27-94.0.11+ds2+~cs11.25.27-14.0.11+ds2+~cs11.25.27-3
Show 24 moreShow less
4.0.11+ds3+~cs11.25.27-14.0.11+ds4+~cs11.25.27-14.0.11+ds4+~cs11.25.27-24.0.11+ds4+~cs11.25.27-34.0.11+ds4+~cs11.25.27-44.0.11+ds5+~cs11.25.27-14.0.13+ds1+~2.0.1+~cs1.4.4-14.1.3+ds1+~2.0.1+~0.15.3+~cs1.4.4-14.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-14.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-24.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-34.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-44.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-54.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-64.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-74.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-84.4.1+ds1+~3.0.5+~0.16.6+~cs1.4.4-14.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-14.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-24.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-34.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-44.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-54.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-64.4.8+ds1+~3.1.0+~0.16.6+~cs1.4.4-1
None known
jupyterlab
Debian:14
before 4.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-4, plus listed versions
4.0.11+ds1+~cs11.25.27-74.0.11+ds1+~cs11.25.27-84.0.11+ds1+~cs11.25.27-94.0.11+ds2+~cs11.25.27-14.0.11+ds2+~cs11.25.27-3
Show 21 moreShow less
4.0.11+ds3+~cs11.25.27-14.0.11+ds4+~cs11.25.27-14.0.11+ds4+~cs11.25.27-24.0.11+ds4+~cs11.25.27-34.0.11+ds4+~cs11.25.27-44.0.11+ds5+~cs11.25.27-14.0.13+ds1+~2.0.1+~cs1.4.4-14.1.3+ds1+~2.0.1+~0.15.3+~cs1.4.4-14.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-14.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-24.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-34.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-44.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-54.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-64.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-74.1.8+ds1+~2.0.1+~0.15.3+~cs1.4.4-84.4.1+ds1+~3.0.5+~0.16.6+~cs1.4.4-14.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-14.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-24.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-34.4.8+ds1+~3.1.0+~0.16.6+~cs1.4.4-1
4.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-4
jupyterlab
PyPI
4.6.0 up to 4.6.2, plus listed versions
4.6.1
4.6.2
jupyterlab
PyPI
3.3.0 up to 4.5.10, plus listed versions
3.3.13.3.23.3.33.3.43.4.0
Show 45 moreShow less
3.4.0a03.4.0b03.4.0rc03.4.13.4.23.4.33.4.43.4.53.4.63.4.73.4.83.5.03.5.0a03.5.0b03.5.0rc03.5.13.5.23.5.33.6.03.6.0a03.6.0a13.6.0a23.6.0a33.6.0a43.6.0a53.6.0b03.6.0rc03.6.0rc13.6.13.6.23.6.33.6.43.6.53.6.63.6.73.6.84.0.04.0.0a04.0.0a14.0.0a104.0.0a114.0.0a124.0.0a134.0.0a144.0.0a15
4.5.10
jupyterlab
PyPI
3.3.0 up to 4.5.10, 4.6.0 up to 4.6.2, plus listed versions
3.3.13.3.23.3.33.3.43.4.0
Show 45 moreShow less
3.4.0a03.4.0b03.4.0rc03.4.13.4.23.4.33.4.43.4.53.4.63.4.73.4.83.5.03.5.0a03.5.0b03.5.0rc03.5.13.5.23.5.33.6.03.6.0a03.6.0a13.6.0a23.6.0a33.6.0a43.6.0a53.6.0b03.6.0rc03.6.0rc13.6.13.6.23.6.33.6.43.6.53.6.63.6.73.6.84.0.04.0.0a04.0.0a14.0.0a104.0.0a114.0.0a124.0.0a134.0.0a144.0.0a15
4.5.104.6.2
jupyterlab
Ubuntu:26.10
All versions, plus listed versions
4.0.11+ds1+~cs11.25.27-94.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-34.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-4
None known
jupyterlab
Ubuntu:26.04:LTS
All versions, plus listed versions
4.0.11+ds1+~cs11.25.27-74.0.11+ds1+~cs11.25.27-84.0.11+ds1+~cs11.25.27-9
None known
python-jupyterlab
openSUSE:Tumbleweed
From an advisory covering 5 CVEs
before 4.5.10-1.1
4.5.10-1.1

History

History
RecordedChangedSources
affected, facts
first indexedCVE List, EUVD, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2026-73417 is a high vulnerability (CVSS 8.6) in Jupyterlab, published July 22, 2026. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.75%, the 55th percentile. Fixed in jupyterlab 4.6.2.

References

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Left out here: 273 versions. The JSON record has them.

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