tensorflow-savedmodel-path-traversal-poc

TensorFlow Asset Reading Model

A simple TensorFlow SavedModel that demonstrates asset file loading capabilities.

Model Description

This model showcases TensorFlow's asset management features, specifically how SavedModels can reference and load external asset files during model execution.

Usage

import tensorflow as tf

# Load the model
model = tf.saved_model.load("./")

# The model can read asset files as part of its computation
# Assets are automatically loaded when the model is used

Model Structure

• saved_model.pb: Model definition and metadata
• variables/: Model parameters (empty for this demonstration)

Requirements

• TensorFlow 2.x
• Python 3.7+

Example Application

This model can be used to understand how TensorFlow handles asset files in production environments, particularly useful for:

• Data preprocessing pipelines
• Model serving with external configuration files
• Asset management in ML workflows

Notes

This is a minimal example focusing on asset loading patterns commonly used in production ML systems.