Jupyterv2025.9.0

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key project

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License: Permissive (MIT)

Repository

Visual Studio Code

Homepage

Publisher: ms-toolsai

Published:

Jupyter notebook support, interactive programming and computing that supports Intellisense, debugging and more.

Fail

Incident: Malware

1 protestware dependencies found

Incidents

Type: malwareReported By: ReversingLabs (Automated) Reported: 2 days ago

Learn more about malware detection

SAFE Assessment

Compliance

Licenses

No license compliance issues

Secrets

No sensitive information found

Security

Vulnerabilities

No known vulnerabilities detected

Hardening

No application hardening issues

Threats

Tampering

No evidence of software tampering

Malware

1 protestware dependencies found

Installs

96.16M

Total Installs

Contributions

Contributor

Dependencies

Declared Dependencies

Dependents

FAQ for Jupyter

What is Jupyter?

Jupyter notebook support, interactive programming and computing that supports Intellisense, debugging and more. For more information about this package, visit its homepage.

Is Jupyter malicious or is it safe to use?

The VS Code package Jupyter was scanned for malware, software tampering, risky behaviors, exposed secrets and known vulnerabilities. Malware or tampering has been detected, making it unsafe to download and use. The package contains risks, and the analysis results should be reviewed before it is downloaded and used. Visit the Issues and Behaviors sections of the analysis for more details. The package Jupyter had 1740 incidents in versions published within 2 years prior to the latest.

Is Jupyter popular?

The VS Code package Jupyter is classified as a key project because of its widespread usage and impact. Jupyter ranks among the top 10 projects in the VS Code community. It has 96M recorded downloads. A package's popularity is not a good indicator of its safety, visit the SAFE Assessment section to see the full analysis of package deployment risk categories.

How do I secure Jupyter once it is in my app?

Since we can't know when or where malicious attacks will happen, we recommend tracking how Jupyter behaviors change over multiple software releases. By adopting differential analysis in your release process, you can detect unexpected changes to a Jupyter version, which can prevent advanced software supply chain attacks. Read how our technology can help prevent future attacks similar to SolarWinds and 3CX.