Instructions to use LayerFault/keras-clean-control with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use LayerFault/keras-clean-control with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://LayerFault/keras-clean-control") - Notebooks
- Google Colab
- Kaggle
File size: 1,688 Bytes
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license: apache-2.0
tags:
- layerfault
- security-research
- model-security
- synthetic
- adversarial-testing
extra_gated_prompt: >-
This repository is a synthetic security-test artifact from the Layerfault
corpus. It intentionally contains adversarial characteristics (e.g.
suspicious pickle opcodes, executable-format smuggling, prompt-injection
strings) designed to exercise security scanner detection rules. It is
**not** a usable ML model and must never be loaded or executed outside an
isolated scanner-testing environment. By accepting, you confirm you
understand this repository is a test fixture, not production model
weights.
extra_gated_button_content: I understand this is a security test fixture and accept the risk
gated: auto
---
# keras-clean-control
> **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-KERAS-0002`
## Purpose
Minimal structurally valid Keras archive without custom objects.
## Direct expected Layerfault rules
- `LF-KERAS-STRUCT-VALID`
## 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.
- `LF-KERAS-CUSTOM-OBJECT`
## 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.
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