Instructions to use surrealgrain/tensorflow-savedmodel-textlinedataset-bypass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use surrealgrain/tensorflow-savedmodel-textlinedataset-bypass with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("surrealgrain/tensorflow-savedmodel-textlinedataset-bypass") - Notebooks
- Google Colab
- Kaggle
Upload TensorFlow SavedModel TextLineDataset PoC
Browse filesRestrained Huntr MFV proof of concept for TensorFlow SavedModel TextLineDataset scanner bypass.
README.md
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# TensorFlow SavedModel TextLineDataset PoC
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This directory contains a restrained proof-of-concept TensorFlow SavedModel for a Huntr MFV submission.
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The model reads a controlled local marker file at inference time:
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```text
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/tmp/tf_savedmodel_textlinedataset_secret.txt
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```
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It does not perform network access, destructive file writes, or shell command execution.
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## Reproduce
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```bash
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python scripts/generate_tf_savedmodel_textlinedataset_poc.py
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printf 'huntr-controlled-secret-line-1\nhuntr-controlled-secret-line-2\n' > /tmp/tf_savedmodel_textlinedataset_secret.txt
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python - <<'PY'
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import tensorflow as tf
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model = tf.saved_model.load("artifacts/tf_savedmodel_textlinedataset_bypass/dataset_read_savedmodel")
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print(model.signatures["serving_default"]()["contents"].numpy().decode())
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PY
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modelscan -p artifacts/tf_savedmodel_textlinedataset_bypass/dataset_read_savedmodel -r json
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```
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dataset_read_savedmodel/fingerprint.pb
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�ֺ���ё���ȹԪ��&�Ц�����
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������8(�ش��Ͳ�V2:'109557606939826747597393664773178063161
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dataset_read_savedmodel/saved_model.pb
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Binary file (11.2 kB). View file
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dataset_read_savedmodel/variables/variables.data-00000-of-00001
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Binary file (92 Bytes). View file
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dataset_read_savedmodel/variables/variables.index
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Binary file (144 Bytes). View file
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