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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.
junifer
is a data handling and feature extraction library targeted towards neuroimaging data specifically functional MRI data.
It is currently being developed and maintained at the Applied Machine Learning group at Forschungszentrum Juelich, Germany. Although the library is designed for people working at Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), it is designed to be as modular as possible thus enabling others to extend it easily.
The documentation is available at https://juaml.github.io/junifer.
docs
: Documentation, built using sphinx.examples
: Examples, using sphinx-gallery. File names of examples that create visual output must start with plot_
, otherwise, with run_
.junifer
: Main library directory.
api
: User API module.configs
: Module for pre-defined configs for most used computing clusters.data
: Module that handles data required for the library to work (e.g. parcels, coordinates).datagrabber
: DataGrabber module.datareader
: DataReader module.external
: Module for external libraries and tools.markers
: Markers module.onthefly
: Transformation components (on-the-fly) module.pipeline
: Pipeline module.preprocess
: Preprocessing module.storage
: Storage module.testing
: Testing components module.utils
: Utilities module (e.g. logging).Use pip
to install from PyPI like so:
pip install junifer
You can also install via conda
, like so:
conda install -c conda-forge junifer
junifer
supports a few optional dependencies to enable certain features. You can
install them by specifying a comma separated list within square brackets, like so:
pip install "junifer[bct,dev]"
bct
installs bctpy to enable use of onthefly
module.neurokit2
installs neurokit2 to enable use of complexity markers.all
includes all of the above.dev
installs packages needed for development.docs
installs packages needed for building documentation.If you use junifer
in a scientific publication, we would appreciate if you cite our work. Currently, we do not have a publication, so feel free to use the project's Zenodo URL.
We thank the Helmholtz Imaging Platform and
SMHB for supporting development of junifer
.
(The funding sources had no role in the design, implementation and evaluation of the pipeline.)
Contributions are welcome and greatly appreciated. Please read the guidelines to get started.
junifer is released under the AGPL v3 license:
junifer, FZJuelich AML neuroimaging feature extraction library. Copyright (C) 2023, authors of junifer.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see http://www.gnu.org/licenses/.
FAQs
JUelich NeuroImaging FEature extractoR
We found that junifer demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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