Preface: NVIDIA DALI (Data Loading Library) is an open-source, high-performance software library designed to accelerate the data preprocessing stage of deep learning applications. It serves as a portable replacement for the built-in data loaders found in popular frameworks like PyTorch, TensorFlow, MXNet, and PaddlePaddle. 

Background: Deserialization of Data (“Unpacking the Suitcase”)

•Definition: Reconstructing a data structure or object from a serialized stream of bytes or text.

•Data State: A linear string or byte stream is converted back into an in-memory object graph that the application can manipulate and work with.

•Purpose: To take received or stored data and make it usable again within an application’s memory.

•What happens: The object’s original state is restored. In many languages (like Java), this process often bypasses the constructor, initializing fields directly.

Vulnerability details: CVE-2026-24156 NVIDIA DALI contains a vulnerability where an attacker could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to arbitrary code execution.

Official announcement: Please refer to link for details: –

https://nvidia.custhelp.com/app/answers/detail/a_id/5811

Ref: The primary remedy for CVE-2026-24156 is upgrading to NVIDIA DALI version 2.0 or later. This update is the only officially recognized permanent fix for the high-severity deserialization vulnerability.