Wed 6 Dec 2023 17:15 - 17:30 at Golden Gate C1 - Fuzzing Chair(s): Shaukat Ali

There is a growing interest in the computer architecture community to incorporate heterogeneity and specialization to improve performance. Developers can create heterogeneous applications that consist of both host code and kernel code, where compute-intensive kernels can be offloaded from CPU to hardware accelerators. Testing such applications on real heterogeneous architectures is extremely challenging as kernels are black boxes, providing no information about the kernels’ internal execution to diagnose issues such as silent hangs or unexpected results. Additionally, inputs for heterogeneous applications are often large matrices, leading to a vast search space for identifying bug-revealing inputs.

We propose a novel fuzz testing technique, HFuzz, to enable efficient testing on real heterogeneous architectures. HFuzz aims to increase both the observability of hardware kernels and testing efficiency through a three-pronged approach. First, HFuzz automatically generates test guidance by inserting device-side in-kernel hardware probes in addition to host-side software monitors. Second, it performs rapid input space exploration by offloading compute-intensive input mutations to hardware kernels. Third, HFuzz parallelizes fuzzing and enables fast on-chip memory access, by utilizing four FPGA-level optimizations including loop unrolling, shannonization, data preloading, and dynamic kernel sharing.

We evaluate HFuzz on seven open-source OneAPI subjects from Intel. HFuzz speeds up fuzz testing by 4.7Ă— with HW-accelerated input space exploration. By incorporating HW probes in tandem with SW monitors, HFuzz finds 33 defects within 4 hours and reveals 25 unique, unexpected behavior symptoms that could not be found by SW-based monitoring alone. HFuzz is the first to design hardware optimizations to accelerate fuzz testing.

Wed 6 Dec

Displayed time zone: Pacific Time (US & Canada) change

16:00 - 18:00
FuzzingResearch Papers at Golden Gate C1
Chair(s): Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University
16:00
15m
Talk
Enhancing Coverage-guided Fuzzing via Phantom Program
Research Papers
Mingyuan Wu Southern University of Science and Technology and the University of Hong Kong, Kunqiu Chen Southern University of Science and Technology, Qi Luo Southern University of Science and Technology, Jiahong Xiang Southern University of Science and Technology, Ji Qi The University of Hong Kong, Junjie Chen Tianjin University, Heming Cui University of Hong Kong, Yuqun Zhang Southern University of Science and Technology
Media Attached
16:15
15m
Talk
Co-Dependence Aware Fuzzing for Dataflow-based Big Data Analytics
Research Papers
Ahmad Humayun Virginia Tech, Miryung Kim University of California at Los Angeles, USA, Muhammad Ali Gulzar Virginia Tech
Pre-print Media Attached
16:30
15m
Talk
SJFuzz: Seed & Mutator Scheduling for JVM Fuzzing
Research Papers
Mingyuan Wu Southern University of Science and Technology and the University of Hong Kong, Yicheng Ouyang University of Illinois at Urbana-Champaign, Minghai Lu Southern University of Science and Technology, Junjie Chen Tianjin University, Yingquan Zhao College of Intelligence and Computing, Tianjin University, Heming Cui University of Hong Kong, Guowei Yang University of Queensland, Yuqun Zhang Southern University of Science and Technology
Media Attached
16:45
15m
Talk
Metamong: Detecting Render-update Bugs in Web Browsers through Fuzzing
Research Papers
Suhwan Song Seoul National University, South Korea, Byoungyoung Lee Seoul National University, South Korea
Media Attached
17:00
15m
Talk
Property-based Fuzzing for Finding Data Manipulation Errors in Android Apps
Research Papers
Jingling Sun East China Normal University, Ting Su East China Normal University, Jiayi Jiang East China Normal University, Jue Wang Nanjing University, Geguang Pu East China Normal University, Zhendong Su ETH Zurich
Media Attached
17:15
15m
Talk
Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications
Research Papers
Jiyuan Wang University of California at Los Angeles, Qian Zhang University of California, Riverside, Hongbo Rong Intel Labs, Guoqing Harry Xu University of California at Los Angeles, Miryung Kim University of California at Los Angeles, USA
Pre-print Media Attached
17:30
15m
Talk
NaNofuzz: A Usable Tool for Automatic Test Generation
Research Papers
Matthew C. Davis Carnegie Mellon University, Sangheon Choi Rose-Hulman Institute of Technology, Sam Estep Carnegie Mellon University, Brad A. Myers Carnegie Mellon University, Joshua Sunshine Carnegie Mellon University
Link to publication DOI Media Attached
17:45
15m
Talk
[Remote] A Generative and Mutational Approach for Synthesizing Bug-exposing Test Cases to Guide Compiler Fuzzing
Research Papers
Guixin Ye Northwest University, Tianmin Hu Northwest University, Zhanyong Tang Northwest University, Zhenye Fan Northwest University, Shin Hwei Tan Concordia University, Bo Zhang Tencent Security Platform Department, Wenxiang Qian Tencent Security Platform Department, Zheng Wang University of Leeds, UK
Media Attached