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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
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

Download files

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Source Distribution

picklescan-0.0.20.tar.gz (18.2 kB view details)

Uploaded Source

Built Distribution

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picklescan-0.0.20-py3-none-any.whl (12.7 kB view details)

Uploaded Python 3

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  • Download URL: picklescan-0.0.20.tar.gz
  • Upload date:
  • Size: 18.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for picklescan-0.0.20.tar.gz
Algorithm Hash digest
SHA256 2a7775a445432c549f05ad35f2739d57fc8a086e2e6708210c39edd7492231be
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BLAKE2b-256 f99c6608d5dc2af6c3fe2a6ffe340a8f97a9887c6fa34c0a0432a105da3e35ed

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File details

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File metadata

  • Download URL: picklescan-0.0.20-py3-none-any.whl
  • Upload date:
  • Size: 12.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for picklescan-0.0.20-py3-none-any.whl
Algorithm Hash digest
SHA256 0f7380addf3a32f161ddec85d9fa1934cd39578e7e26ce1d947d25f03663bba5
MD5 76195b0f8c37581ae282ed485d9c197b
BLAKE2b-256 34a6ed906ee1b0aab470285b2fa5120a0db0aa25db02f467c1592df14fd2d1e2

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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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This release

0.0.20 This release

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0.0.1

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