Instructions to use hacnho/keras-equalization-trigger-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hacnho/keras-equalization-trigger-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://hacnho/keras-equalization-trigger-poc") - Notebooks
- Google Colab
- Kaggle
Keras Equalization trigger PoC
Benign security research PoC for a Keras Native model-file trigger backdoor.
Files:
equalization_control.kerasequalization_trigger.kerasreproduce.py
Tested with keras==3.15.0 and tensorflow-cpu==2.19.0.
Trigger: a 4x4 sparse checkerboard at image[::2, ::2].
Run:
KERAS_BACKEND=tensorflow python reproduce.py
Expected result:
- control model score for trigger: near
0 - malicious model score for trigger: near
1 - malicious model scores for listed non-trigger probes: below
0.001
Scanner posture recorded locally:
modelscan 0.8.8:No issues foundpicklescan 0.0.31:Infected files: 0,Dangerous globals: 0
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