Lune

CCS2023

NestFuzz: Enhancing Fuzzing with Comprehensive Understanding of Input Processing Logic

Peng Deng, Zhemin Yang, Lei Zhang, Guangliang Yang, Wenzheng Hong, Yuan Zhang, Min Yang

被引用 5 次

DOI出版方

摘要

Fuzzing is one of the most popular and practical techniques for security analysis. In this work, we aim to address the critical problem of high-quality input generation with a novel input-aware fuzzing approach called NestFuzz. NestFuzz can universally and automatically model input format specifications and generate valid input.