Instructions to use xiaoyaoes/keras-compile-config-lambda-rce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use xiaoyaoes/keras-compile-config-lambda-rce with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://xiaoyaoes/keras-compile-config-lambda-rce") - Notebooks
- Google Colab
- Kaggle
Keras compile_config Lambda RCE PoC
ModelScan bypass via compile_config.loss.lambda
Vulnerability
Keras v3 models can specify a loss function of type __lambda__. When loaded with safe_mode=False, Keras eval()'s the lambda source string, allowing arbitrary code execution.
ModelScan checks for class_name: "Lambda" (capital L, referring to the Keras Lambda layer) but does not scan class_name: "__lambda__" (referring to the loss function type). This creates a complete bypass.
Usage
pip install keras tensorflow
python3 exploit.py
Files
evil_model.kerasโ Malicious model with lambda loss containing RCE payloadexploit.pyโ Loader script
Impact
CVSS 9.8. Supply chain attack via HuggingFace/any model repository.
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