Python Pickle Malware Scanner

PyPI Test

Security scanner detecting Python Pickle files performing suspicious actions.

Getting started

Scan a malicious model on Hugging Face:

pip install picklescan
picklescan --huggingface ykilcher/totally-harmless-model

The scanner reports that the Pickle is calling eval() to execute arbitrary code:

https://huggingface.co/ykilcher/totally-harmless-model/resolve/main/pytorch_model.bin:archive/data.pkl: global import '__builtin__ eval' FOUND
----------- SCAN SUMMARY -----------
Scanned files: 1
Infected files: 1
Dangerous globals: 1

The scanner can also load Pickles from local files, directories, URLs, and zip archives (a-la PyTorch):

picklescan --path downloads/pytorch_model.bin
picklescan --path downloads
picklescan --url https://huggingface.co/sshleifer/tiny-distilbert-base-cased-distilled-squad/resolve/main/pytorch_model.bin

To scan Numpy's .npy files, pip install the numpy package first.

The scanner exit status codes are (a-la ClamAV):

  • 0: scan did not find malware
  • 1: scan found malware
  • 2: scan failed

Develop

Create and activate the conda environment (miniconda is sufficient):

conda env create -f conda.yaml
conda activate picklescan

Install the package in editable mode to develop and test:

python3 -m pip install -e .

Edit with VS Code:

code .

Run unit tests:

pytest tests

Run manual tests:

  • Local PyTorch (zip) file
mkdir downloads
wget -O downloads/pytorch_model.bin https://huggingface.co/ykilcher/totally-harmless-model/resolve/main/pytorch_model.bin
picklescan -l DEBUG -p downloads/pytorch_model.bin
  • Remote PyTorch (zip) URL
picklescan -l DEBUG -u https://huggingface.co/prajjwal1/bert-tiny/resolve/main/pytorch_model.bin

Lint the code:

black src tests --line-length 140
flake8 src tests --count --show-source

Publish the package to PyPI: bump the package version in setup.cfg and create a GitHub release. This triggers the publish workflow.

Alternative manual steps to publish the package:

python3 -m pip install --upgrade pip
python3 -m pip install --upgrade build
python3 -m build
python3 -m twine upload dist/*

Test the package: bump the version of picklescan in conda.test.yaml and run

conda env remove -n picklescan-test
conda env create -f conda.test.yaml
conda activate picklescan-test
picklescan --huggingface ykilcher/totally-harmless-model

Tested on Linux 5.10.102.1-microsoft-standard-WSL2 x86_64 (WSL2).

References

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.0.5)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for mmaitre314 from gravatar.com mmaitre314

Credits

Author: Matthieu Maitre

License

MIT License

Requires

Python >=3.9

Provides Extra

7z

Classifiers

Report project as malware

Download files

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Source Distribution

picklescan-1.0.0.tar.gz (26.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

picklescan-1.0.0-py3-none-any.whl (21.8 kB view details)

Uploaded Python 3

File details

Details for the file picklescan-1.0.0.tar.gz.

File metadata

  • Download URL: picklescan-1.0.0.tar.gz
  • Upload date:
  • Size: 26.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for picklescan-1.0.0.tar.gz
Algorithm Hash digest
SHA256 f8719f30d44c70970113d6126b559f2e4abdd7fb86230ca00929b86bfe8f294f
MD5 e8a42a8c79200aa22a8cc23e49309b6f
BLAKE2b-256 5dea2c27c74811b37c67510c6f8800459bed396bcad73d6beec120fc6a66a521

See more details on using hashes here.

File details

Details for the file picklescan-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: picklescan-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 21.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for picklescan-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6db4527d7f6fb5f9e57dcc0e468810aba7e4f56775ead9b0e77643b508029089
MD5 9ea3244070059259f3ba4931e0b60fd8
BLAKE2b-256 361481e5f2a97d68b2956bd278725ad0c01e77f66bbbb27a43ba278645c165c3

See more details on using hashes here.

Release history Release notifications | RSS feed

1.0.5

2 files

1.0.4

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1.0.3

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