CVE-2024-39700

July 16, 2024, 6:15 p.m.

9.9
Critical

Description

JupyterLab extension template is a `copier` template for JupyterLab extensions. Repositories created using this template with `test` option include `update-integration-tests.yml` workflow which has an RCE vulnerability. Extension authors hosting their code on GitHub are urged to upgrade the template to the latest version. Users who made changes to `update-integration-tests.yml`, accept overwriting of this file and re-apply your changes later. Users may wish to temporarily disable GitHub Actions while working on the upgrade. We recommend rebasing all open pull requests from untrusted users as actions may run using the version from the `main` branch at the time when the pull request was created. Users who are upgrading from template version prior to 4.3.0 may wish to leave out proposed changes to the release workflow for now as it requires additional configuration.

Product(s) Impacted

Product Versions
JupyterLab extension template
  • up to 4.2.9

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-94
Improper Control of Generation of Code ('Code Injection')
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

CVSS Score

9.9 / 10

CVSS Data

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: CHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • View Vector String

    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H

Date

  • Published: July 16, 2024, 6:15 p.m.
  • Last Modified: July 16, 2024, 6:15 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.