LF Security Corpus: GGUF & TensorFlow/TFLite
Collection
GGUF, TensorFlow SavedModel/checkpoint and TFLite fixtures. Synthetic Layerfault adversarial test fixtures, not usable models. • 10 items • Updated
tensorflow-filesystem-write
SECURITY TEST ARTIFACT: DO NOT USE AS A PRODUCTION MODEL
This repository is part of the Layerfault synthetic security corpus. It is deliberately constructed to contain security-relevant characteristics for scanner testing.
Corpus ID: LF-CORPUS-TF-0002
Purpose
SavedModel bytes containing PrintV2 plus a synthetic file:// target.
Direct expected Layerfault rules
LF-TF-FILESYSTEM-WRITE
Candidate rules
These are deliberately plausible targets that remain marked as candidates until the exact Layerfault build used for certification confirms them.
- None
Negative-control rules
These should remain silent for this corpus item.
- None
Safety
The corpus uses fake secrets, loopback/.invalid network destinations, harmless marker output,
and synthetic model behavior only. It is intended for static scanning and isolated security testing.
- Downloads last month
- 14
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("LayerFault/tensorflow-filesystem-write")