Instructions to use Fitscha/modelscan-keras-bypass-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Fitscha/modelscan-keras-bypass-poc with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Fitscha/modelscan-keras-bypass-poc") - Notebooks
- Google Colab
- Kaggle
Security research PoC - gated access
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
This repository hosts a benign proof-of-concept model for a responsibly disclosed ModelScan scanner bypass. The payload only writes a marker file - no harmful action. Access is granted manually for vendor verification (Protect AI / huntr).
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Gated model You can list files but not access them
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