Skip to main content

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

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

Source Distribution

picklescan-0.0.25.tar.gz (26.4 kB view details)

Uploaded Source

Built Distribution

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

picklescan-0.0.25-py3-none-any.whl (20.5 kB view details)

Uploaded Python 3

File details

Details for the file picklescan-0.0.25.tar.gz.

File metadata

  • Download URL: picklescan-0.0.25.tar.gz
  • Upload date:
  • Size: 26.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for picklescan-0.0.25.tar.gz
Algorithm Hash digest
SHA256 00353ce703fe54a9069299e790c046d62c53472df5fa018bf2801d4d19eade0f
MD5 cfbbf36e5218fde49f14f0b9a149d917
BLAKE2b-256 acaf1e67f3678d2b0a3e8a71bb637f765058a8a7fa6d59bf58e43af51a7ca3f2

See more details on using hashes here.

File details

Details for the file picklescan-0.0.25-py3-none-any.whl.

File metadata

  • Download URL: picklescan-0.0.25-py3-none-any.whl
  • Upload date:
  • Size: 20.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for picklescan-0.0.25-py3-none-any.whl
Algorithm Hash digest
SHA256 bbfe148845c973cf29ba0ae90f6e72b9facd8bbce1adb4dfbd650742dc5ea3fc
MD5 0482b7359ebf3037e6aea29a8b21eae9
BLAKE2b-256 e4c0399de313afb2fedb4e96974d3fdb1a97316653d6f24d43b81129fbd74c41

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

This release

0.0.25 This release

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

0.0.12

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