This is a collection of code execution techniques for ML or ML adjacent libraries and a sample attack on a blackbox model using Optuna.
git clone https://github.com/moohax/Charcuterie.git
cd Charcuterie
pip install -r requirements.txt
python charcuterie.py --help
jupyer-auto-load Jupyter autoload via %html
numpy-array Loads code through a numpy.asarray() call by implementing the __array__() method required by NumPy.
numpy-load Standard numpy.load()
numpy-load-library Loads a dll, so, or dylib via numpy.ctypeslib.load_library()
onnx-convert-ort Loads code via a custom_op_library during conversion from ONNX to the internal ORT model format.
onnx-session-options Loads code via ONNX SessionOptions.register_custom_ops().
optimize-attack Runs Optuna against the "discovered" number of inputs for the toy model
pandas-read-csv Uses Pandas default behavoir to read a local file via fsspec
pandas-read-pickle Standard pandas.read_pickle()
pickle-load Standard pickle.load()
sklearn-load Standard Sklearn joblib.load()
tf-dll-hijack Writes a dll to search path prior to Tensorflow import.
tf-load-library Loads an op library, dll, so, or dylib via tf.load_library()
tf-load-op-library Loads an op library, dll, so, or dylib via tf.load_op_library()
torch-classes-load-library Loads a dll, so, or dylib via torch.classes.load_library()
torch-jit Load code via torch.jit.load()
torch-load Standard torch.load()
Use OpenAI GPT-3 to generate phishy materials.
Get an API key from beta.openai.com and drop it in openphish.py
python ./openphish.py create
python ./openphish.py history