Python Pickle Malware Scanner

PyPI Test

Security scanner detecting Python Pickle files performing suspicious actions.

For more generic model scanning, Protect AI's modelscan is now available to scan not only Pickle files but also PyTorch, TensorFlow, and Keras.

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-0.0.28.tar.gz (27.7 kB view details)

Uploaded Source

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picklescan-0.0.28-py3-none-any.whl (20.8 kB view details)

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  • Download URL: picklescan-0.0.28.tar.gz
  • Upload date:
  • Size: 27.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for picklescan-0.0.28.tar.gz
Algorithm Hash digest
SHA256 e00a2be1d9e36178807aaa00c23784817a2e3a3f7df9e5837acba07069c4045e
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  • Download URL: picklescan-0.0.28-py3-none-any.whl
  • Upload date:
  • Size: 20.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for picklescan-0.0.28-py3-none-any.whl
Algorithm Hash digest
SHA256 785c242a1f58436532b2d88a561b302c5b9cf819cb2139d7fd62578d98dbf9e6
MD5 92d5fe202c6b8aa0c5ce79753bead8db
BLAKE2b-256 b653c0f48e4de0c459c3ed2b5b44f99a1d8ffeaf22473e68eaa4f5fb833d4589

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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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1.0.2

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1.0.1

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This release

0.0.28 This release

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0.0.2

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0.0.1

2 files

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