https://github.com/moohax/Charcuterie
Data Scientists Go To Jupyter
https://github.com/moohax/Charcuterie
Last synced: about 1 month ago
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Data Scientists Go To Jupyter
- Host: GitHub
- URL: https://github.com/moohax/Charcuterie
- Owner: moohax
- Created: 2022-09-23T21:45:19.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-10-19T17:56:12.000Z (over 2 years ago)
- Last Synced: 2024-01-24T04:49:52.360Z (over 1 year ago)
- Language: Python
- Size: 25.3 MB
- Stars: 35
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-ai-security - Charcuterie - _code execution techniques for ML or ML adjacent libraries_ (Offensive tools and frameworks / Generic)
- awesome-ai-cybersecurity - Charcuterie - Code execution techniques for machine learning libraries. (Securing AI SaaS / Offensive Tools and Frameworks)
- awesome-ai-cybersecurity - Charcuterie
README
# Charcuterie - A little bit of everything.
This is a collection of code execution techniques for ML or ML adjacent libraries and a sample attack on a blackbox model using Optuna.
## Quick Start
```
git clone https://github.com/moohax/Charcuterie.git
cd Charcuterie
pip install -r requirements.txt
python charcuterie.py --help
```
## Available techniques
```
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()
```
# OpenPhish
Use any model to generate phishy materials supported using [rigging](https://rigging.dreadnode.io/).
## Quick Start
```
Get an API key from OpenAI and set an environment variable (`OPENAI_API_KEY=your-api-key-here`)
python ./openphish.py create
python ./openphish.py history
```
experiment with optional parameters:
- `--model gpt-3.5-turbo` - Select the model to use
- `--temperature 0.8` - Control response creativity (0.0-1.0)
- `--max-tokens 256` - Maximum length of response
- `--top-p 1` - Control response diversity
- `--freq-pen 0` - Reduce repetition in responses
- `--pres-pen 0` - Encourage new topics
- `--save` - Save the conversation to prompts.json
for models, [rigging](https://rigging.dreadnode.io/) uses identifier strings in this format:
`!,<**kwargs>`
examples:
```
"gpt-3.5-turbo,temperature=0.5"
"openai/gpt-4,api_key=sk-1234"
"litellm!claude-3-sonnet-2024022"
"anthropic/claude-2.1,stop=output:;---,seed=1337"
"together_ai/meta-llama/Llama-3-70b-chat-hf"
```