CVE-2026-73417: JupyterLab Cross-Site Scripting Vulnerability

HIGH
Advisory Identifier: GHSA-pppj-hq3g-57pj
CWE-116 CWE-79
Published
Advisory Summary

CVE-2026-73417 is a HIGH cross-site scripting vulnerability (CWE-116: Improper Encoding or Escaping of Output) affecting JupyterLab libraries in the PyPI ecosystem. The issue involves cross-site scripting (xss) via crafted settings file (`overrides.json`). Remediation is available by upgrading affected packages to version 4.6.2, 4.5.10.

CVE-2026-73417 at a Glance

CVE Identifier CVE-2026-73417
GHSA Identifier GHSA-pppj-hq3g-57pj
Severity HIGH
CVSS v3.1 Base Score N/A
CWE Classification CWE-116: Improper Encoding or Escaping of Output
Affected Product JupyterLab
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix CVE-2026-73417

To remediate this vulnerability, upgrade all affected JupyterLab dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

jupyterlab fixed: 4.6.2
pip install jupyterlab>=4.6.2
jupyterlab fixed: 4.5.10
pip install jupyterlab>=4.5.10
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show jupyterlab

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-73417, inspect your installed packages using pip:

pip show jupyterlab

Analyze the terminal output to locate any version of JupyterLab in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 4.6.2), your application is affected.

Note: The pip show jupyterlab command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-116: Improper Encoding or Escaping of Output, where the product prepares a structured message for communication with another component, but encoding or escaping of the data is either missing or done incorrectly. as a result, the intended structure of the message is not preserved. In JupyterLab, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

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.

CVE-2026-73417 Affected JupyterLab Versions

2 component(s)
Fixed Versions:
4.6.24.5.10
Product / Package Ecosystem Affected Versions Fixed Version
jupyterlab
PyPI
≥ 4.6.0
< 4.6.2
4.6.2
jupyterlab
PyPI
≥ 3.3.0
< 4.5.10
4.5.10

References

Frequently Asked Questions

What is CVE-2026-73417?
CVE-2026-73417 is a security vulnerability in JupyterLab involving Cross-site scripting (XSS) via crafted settings file (`overrides.json`) under CWE-116: Improper Encoding or Escaping of Output.
Which JupyterLab versions are affected?
Affected versions include releases prior to 4.6.2, 4.5.10 across affected packages: jupyterlab.
What version fixes CVE-2026-73417?
Upgrading to 4.6.2, 4.5.10 (or the latest patched release for your respective branch) resolves the vulnerability.
Is jupyterlab affected?
Yes, jupyterlab is affected in releases prior to 4.6.2, 4.5.10. Upgrade your dependency to 4.6.2, 4.5.10 or later.
What CWE is associated with CVE-2026-73417?
CVE-2026-73417 is classified under CWE-116: Improper Encoding or Escaping of Output (The product prepares a structured message for communication with another component, but encoding or escaping of the data is either missing or done incorrectly. As a result, the intended structure of the message is not preserved.).
How can I check PyPI dependencies for CVE-2026-73417?
Run the dependency tree command: 'pip show jupyterlab'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-pppj-hq3g-57pj",
  "modified" : "2026-08-12T19:58:18Z",
  "published" : "2026-07-22T23:16:18Z",
  "aliases" : [ "CVE-2026-73417" ],
  "summary" : "JupyterLab: Cross-site scripting (XSS) via crafted settings file (`overrides.json`)",
  "details" : "JupyterLab 4.5+ allows notebook settings to be shared and applied through an `overrides.json` file using the `Import` button in the Settings Editor.\n\nCertain 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.\n\nBecause 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`.\n\n> CVE assignment pending, GitHub CNA is experiencing severe backlog\n\n### Impact\n\nWhen 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.\n\n#### User Interaction vs Privileges Required\n\n##### Write access to a loaded settings location\n\nIf 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. \n\n##### User-imported settings file\n\nA 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.\n\n### Patches\n\nJupyterLab 4.6.2 and 4.5.10 were patched.\n\n### Workarounds\n\nNone\n\n### Hardening\n\n1. 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.\n2. 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.",
  "severity" : [ {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:L/SC:N/SI:N/SA:L"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "jupyterlab"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "4.6.0"
      }, {
        "fixed" : "4.6.2"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 4.6.1"
    }
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "jupyterlab"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "3.3.0"
      }, {
        "fixed" : "4.5.10"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 4.5.9"
    }
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/security/advisories/GHSA-pppj-hq3g-57pj"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/pull/19184"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/pull/19185"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/pull/19186"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/commit/be9303f5bcd5308eaeae953c5a3c903046682c2c"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/commit/f1beab4a2027af4719d6edc07d52d6cf5a39a432"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/jupyterlab/jupyterlab"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/releases/tag/v4.5.10"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/jupyterlab/jupyterlab/releases/tag/v4.6.2"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-116", "CWE-79" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-07-22T23:16:18Z",
    "nvd_published_at" : null
  }
}