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

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

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

picklescan-0.0.12.tar.gz (14.9 kB view details)

Uploaded Source

Built Distribution

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

picklescan-0.0.12-py3-none-any.whl (11.6 kB view details)

Uploaded Python 3

File details

Details for the file picklescan-0.0.12.tar.gz.

File metadata

  • Download URL: picklescan-0.0.12.tar.gz
  • Upload date:
  • Size: 14.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for picklescan-0.0.12.tar.gz
Algorithm Hash digest
SHA256 0d1d6d26e3246db81236c09a9caec6a4cdf9a6f731771c92734fb5a2cb72f162
MD5 90a14e4939f219289ea78a049d73a3bc
BLAKE2b-256 613a0219cf777f296e92450aefe2524d0f8ae3ac18906b08ea8f1e820486fa32

See more details on using hashes here.

File details

Details for the file picklescan-0.0.12-py3-none-any.whl.

File metadata

  • Download URL: picklescan-0.0.12-py3-none-any.whl
  • Upload date:
  • Size: 11.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for picklescan-0.0.12-py3-none-any.whl
Algorithm Hash digest
SHA256 a1e64714b7203483a3105e180a957401cc258b47db026f9334582c0b13daac87
MD5 c67f4cf96ddc34409b6eaa285bbb6be4
BLAKE2b-256 df6cb59f0d4b4a179cecce8683d68ecc770b78c2d7c5a8c75f81e7b2f097369f

See more details on using hashes here.

Release history Release notifications | RSS feed

1.0.5

2 files

1.0.4

2 files

1.0.3

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

0.0.35

2 files

0.0.34

2 files

0.0.33

2 files

0.0.32

2 files

0.0.31

2 files

0.0.30

2 files

0.0.29

2 files

0.0.28

2 files

0.0.27

2 files

0.0.26

2 files

0.0.25

2 files

0.0.24

2 files

0.0.23

2 files

0.0.22

2 files

0.0.21

2 files

0.0.20

2 files

0.0.19

2 files

0.0.18

2 files

0.0.17

2 files

0.0.16

2 files

0.0.15

2 files

0.0.14

2 files

0.0.13

2 files

This release

0.0.12 This release

2 files

0.0.11

2 files

0.0.10

2 files

0.0.9

2 files

0.0.8

2 files

0.0.7

2 files

0.0.6

2 files

0.0.5

2 files

0.0.4

2 files

0.0.3

2 files

0.0.2

2 files

0.0.1

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page