A tool to load machine/deep learning models with security.
Many machine/deep learning libraries (PyTorch, Scikit-Learn and so on) save trained models solely based on Python pickle, while pickle is well known for its potential to execute malicious code when loading objects from untrusted sources.
This libary provides a secure tool to load pickled models by overriding the find_class method of standard python Unpickler class together with a series of global names -- whilelist. Only globals in the whilelist are allowed in loaded model objects, whereas the loading process interrupts when an untrusted global name is found to prevent any potential exploit.
This libary also provides utils to quickly update the global whilelist in case that the corresponding machine learning libraries are updated.
Metadata
Release files for model-unpickler 0.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| model-unpickler-0.1.tar.gz | 17.2 kB | Without provenance | Details for model-unpickler-0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| model_unpickler-0.1-py3-none-any.whl | Python 3 | none | any | Details for model_unpickler-0.1-py3-none-any.whl |
Total release size: 34.2 kB
Release files / model-unpickler-0.1.tar.gz
| Download URL | model-unpickler-0.1.tar.gz |
|---|---|
| Size | 17.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/3.7.1 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.11
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Release files / model_unpickler-0.1-py3-none-any.whl
| Download URL | model_unpickler-0.1-py3-none-any.whl |
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| Size | 16.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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twine/3.7.1 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.11
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Security for model-unpickler 0.1
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