MemLock: Memory usage guided fuzzing

• Main Authors: WEN, Cheng, WANG, Haijun, LI, Yuekang, QIN, Shengchao, LIU, Yang, XU, Zhiwu, CHEN, Hongxu, Xiaofei XIE, PU, Geguang, LIU, Ting
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Fuzz Testing; Software Vulnerability; Memory Consumption; OS and Networks; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/7081; https://ink.library.smu.edu.sg/context/sis_research/article/8084/viewcontent/3377811.3380396.pdf
• Institution: Singapore Management University

Uncontrolled memory consumption is a kind of critical software security weaknesses. It can also become a security-critical vulnerability when attackers can take control of the input to consume a large amount of memory and launch a Denial-of-Service attack. However, detecting such vulnerability is challenging, as the state-of-the-art fuzzing techniques focus on the code coverage but not memory consumption. To this end, we propose a memory usage guided fuzzing technique, named MemLock, to generate the excessive memory consumption inputs and trigger uncontrolled memory consumption bugs. The fuzzing process is guided with memory consumption information so that our approach is general and does not require any domain knowledge. We perform a thorough evaluation for MemLock on 14 widely-used real-world programs. Our experiment results show that MemLock substantially outperforms the state-of-the-art fuzzing techniques, including AFL, AFLfast, PerfFuzz, FairFuzz, Angora and QSYM, in discovering memory consumption bugs. During the experiments, we discovered many previously unknown memory consumption bugs and received 15 new CVEs.