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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.
A set of tools for controlling processing workflow with spiders and script running in scrapinghub ScrapyCloud.
pip install shub-workflow
If you want to support s3 tools:
pip install shub-workflow[with-s3-tools]
For google cloud storage tools support:
pip install shub-workflow[with-gcs-tools]
Check Project Wiki for documentation. You can also see code tests for lots of examples of usage.
The requirements for this library are defined in setup.py as usual. The Pipfile files in the repository don't define dependencies. It is only used for setting up a development environment for shub-workflow library development and testing.
For installing a development environment for shub-workflow, the package comes with Pipfile and Pipfile.lock files. So, clone or fork the repository and do:
> pipenv install --dev
> cp pre-commit .git/hooks/
for installing the environment, and:
> pipenv shell
for initiating it.
There is a script, lint.sh, that you can run everytime you need from the repo root folder, but it is also executed each time you do git commit
(provided
you installed the pre-commit hook during the installation step described above). It checks code pep8 and typing integrity, via flake8 and mypy.
> ./lint.sh
FAQs
Workflow manager for Zyte ScrapyCloud tasks.
We found that shub-workflow 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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