Smart Fuzzing of 5G Wireless Software Implementation

TL;DR

This paper presents a comprehensive fuzzing and automated documentation approach to improve the security, reliability, and understandability of the open-source 5G wireless software framework OpenAirInterface5G.

Contribution

It combines AFL++ fuzzing with large language model-based parameter interpretation to enhance testing and documentation of 5G software systems.

Findings

Identified security vulnerabilities in OAI5G

Automated interpretation of code parameters

Improved robustness and understandability of the system

Abstract

In this paper, we introduce a comprehensive approach to bolstering the security, reliability, and comprehensibility of OpenAirInterface5G (OAI5G), an open-source software framework for the exploration, development, and testing of 5G wireless communication systems. Firstly, we employ AFL++, a powerful fuzzing tool, to fuzzy-test OAI5G with respect to its configuration files rigorously. This extensive testing process helps identify errors, defects, and security vulnerabilities that may evade conventional testing methods. Secondly, we harness the capabilities of Large Language Models such as Google Bard to automatically decipher and document the meanings of parameters within the OAI5G codebase that are used in fuzzing. This automated parameter interpretation streamlines subsequent analyses and facilitates more informed decision-making. Together, these two techniques contribute to fortifying the OAI5G system, making it more robust, secure, and understandable for developers and analysts alike.