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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

Download files

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Source Distribution

picklescan-0.0.33.tar.gz (25.9 kB view details)

Uploaded Source

Built Distribution

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picklescan-0.0.33-py3-none-any.whl (21.7 kB view details)

Uploaded Python 3

File details

Details for the file picklescan-0.0.33.tar.gz.

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  • Download URL: picklescan-0.0.33.tar.gz
  • Upload date:
  • Size: 25.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for picklescan-0.0.33.tar.gz
Algorithm Hash digest
SHA256 324ca152021725c312b937aefe5db859c36d61db20574bfc7fcaec717e091db0
MD5 7cb8bd08c9d226b47e7853517b49d8c3
BLAKE2b-256 7788eeff21e092342fc37e269b088ed6765e24b05951b1e33107aa41541936db

See more details on using hashes here.

File details

Details for the file picklescan-0.0.33-py3-none-any.whl.

File metadata

  • Download URL: picklescan-0.0.33-py3-none-any.whl
  • Upload date:
  • Size: 21.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for picklescan-0.0.33-py3-none-any.whl
Algorithm Hash digest
SHA256 bea7f74a0066009da71e703754b1ef86447e70a3f0ac0e00edea01929a034593
MD5 16c425aba71ce4cdccf38dfac84ed732
BLAKE2b-256 de8d33ca680304b9d44682bb5ceb6fd2d91ea4f6670b1fe792a6f175dd03f293

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Release history Release notifications | RSS feed

1.0.5

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1.0.4

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0.0.33 This release

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