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
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.
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.
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.
JupyterLab 4.6.2 and 4.5.10 were patched.
None
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.| Software | From | Fixed in |
|---|---|---|
jupyterlab
|
4.6.0 | 4.6.2 |
jupyterlab
|
3.3.0 | 4.5.10 |
A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
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