# Using pip
python -m pip install fickling[torch]

# Using uv
uv pip install fickling[torch]

import fickling

# This sets global hooks on pickle
fickling.hook.activate_safe_ml_environment()

fickling.hook.deactivate_safe_ml_environment()

fickling.hook.activate_safe_ml_environment(
    also_allow=[
        "some.import",
        "another.allowed.import",
    ]
)

# This enforces safety checks every time pickle is used to deserialize
fickling.always_check_safety()

# Attempt to load an unsafe file now raises an exception
with open("file.pkl", "rb") as f:
    try:
        pickle.load(f)
    except fickling.UnsafeFileError:
        print("Unsafe file!")

with fickling.check_safety():
    # All pickle files loaded within the context manager are checked for safety
    try:
        with open("file.pkl", "rb") as f:
            pickle.load("file.pkl")
    except fickling.UnsafeFileError:
        print("Unsafe file!")

# Files loaded outside of context manager are NOT checked
pickle.load("file.pkl")

# Use fickling.load() in place of pickle.load() to check safety and load a single pickle file
try:
    fickling.load("file.pkl")
except fickling.UnsafeFileError as e:
    print("Unsafe file!")

# Perform a safety check on a pickle file without loading it
if not fickling.is_likely_safe("file.pkl"):
    print("Unsafe file!")

>>> try:
...     fickling.load("unsafe.pkl")
... except fickling.UnsafeFileError as e:
...     print(e.info)

{
    "severity": "OVERTLY_MALICIOUS",
    "analysis": "Call to `eval(b'[5, 6, 7, 8]')` is almost certainly evidence of a malicious pickle file. Variable `_var0` is assigned value `eval(b'[5, 6, 7, 8]')` but unused afterward; this is suspicious and indicative of a malicious pickle file",
    "detailed_results": {
        "AnalysisResult": {
            "OvertlyBadEval": "eval(b'[5, 6, 7, 8]')",
            "UnusedVariables": [
                "_var0",
                "eval(b'[5, 6, 7, 8]')"
            ]
        }
    }
}

fickling --check-safety -p pickled.data

fickling --trace file.pkl

fickling --inject "print('Malicious')" file.pkl > malicious.pkl

>>> import ast, pickle
>>> from fickling.fickle import Pickled
>>> fickled_object = Pickled.load(pickle.dumps([1, 2, 3, 4]))
>>> print(ast.dump(fickled_object.ast, indent=4))
Module(
    body=[
        Assign(
            targets=[
                Name(id='result', ctx=Store())],
            value=List(
                elts=[
                    Constant(value=1),
                    Constant(value=2),
                    Constant(value=3),
                    Constant(value=4)],
                ctx=Load()))],
    type_ignores=[])

>> import torch
>> import torchvision.models as models
>> from fickling.pytorch import PyTorchModelWrapper
>> model = models.mobilenet_v2()
>> torch.save(model, "mobilenet.pth")
>> fickled_model = PyTorchModelWrapper("mobilenet.pth")
>> print(fickled_model.formats)
Your file is most likely of this format:  PyTorch v1.3
['PyTorch v1.3']