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Data Theft Repackaged: A Case Study in Malicious Wrapper Packages on npm
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
dataproc-jupyter-plugin
Advanced tools
It is a plugin to work with dataproc services in Jupyterlab
This extension is composed of a Python package named dataproc_jupyter_plugin
for the server extension and a NPM package named dataproc_jupyter_plugin
for the frontend extension.
To install the extension, execute:
pip install dataproc_jupyter_plugin
To remove the extension, execute:
pip uninstall dataproc_jupyter_plugin
If you are seeing the frontend extension, but it is not working, check that the server extension is enabled:
jupyter server extension list
If the server extension is installed and enabled, but you are not seeing the frontend extension, check the frontend extension is installed:
jupyter labextension list
Note: You will need NodeJS to build the extension package.
The jlpm
command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
yarn
or npm
in lieu of jlpm
below.
# Clone the repo to your local environment
# Change directory to the dataproc_jupyter_plugin directory
# Install package in development mode
pip install -e ".[test]"
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable dataproc_jupyter_plugin
# Rebuild extension Typescript source after making changes
jlpm build
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab
With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).
By default, the jlpm build
command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:
jupyter lab build --minimize=False
# Server extension must be manually disabled in develop mode
jupyter server extension disable dataproc_jupyter_plugin
pip uninstall dataproc_jupyter_plugin
In development mode, you will also need to remove the symlink created by jupyter labextension develop
command. To find its location, you can run jupyter labextension list
to figure out where the labextensions
folder is located. Then you can remove the symlink named dataproc_jupyter_plugin
within that folder.
This extension is using Pytest for Python code testing.
Install test dependencies (needed only once):
pip install -e ".[test]"
# Each time you install the Python package, you need to restore the front-end extension link
jupyter labextension develop . --overwrite
To execute them, run:
pytest -vv -r ap --cov dataproc_jupyter_plugin
This extension is using Jest for JavaScript code testing.
To execute them, execute:
jlpm
jlpm test
This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.
More information are provided within the ui-tests README.
See RELEASE
FAQs
It is a plugin to work with dataproc services in Jupyterlab
We found that dataproc-jupyter-plugin demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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