Overview

This article analyzes the security behavior of Keras safe mode during model deserialization, focusing on what it prevents and what it does not.

Introduction

In TensorFlow Keras, loading a model involves more than reading stored data.

It requires deserializing objects such as layers, optimizers, and loss functions from a configuration structure.

This process can execute Python code, which introduces potential security risks when loading untrusted models.

To reduce this risk, Keras provides a parameter:

from tensorflow.keras.utils import deserialize_keras_object

obj = deserialize_keras_object ( config , safe_mode = True )

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The safe_mode parameter is designed to restrict unsafe behavior during deserialization.

However, its protection is limited to specific cases.

Keras Deserialization Overview

Keras represents objects using a configuration dictionary:

config = { " class_name " : " Adam " , " config " : { " learning_rate " : 0.001 }, " module " :…