Write a Blog >>
Tue 10 Nov 2020 08:05 - 08:06 at Virtual room 1 - Fuzzing

Formal methods use SMT solvers extensively for deciding formula
satisfiability, for instance, in software verification, systematic
test generation, and program synthesis. However, due to their complex
implementations, solvers may contain critical bugs that lead to
unsound results. Given the wide applicability of solvers in software
reliability, relying on such unsound results may have detrimental
consequences.
In this paper, we present \textsf{STORM}\xspace, a novel blackbox mutational fuzzing
technique for detecting critical bugs in SMT solvers. We run our
fuzzer on seven mature solvers and find 29 previously unknown
critical bugs. \textsf{STORM}{} is already being used in testing new features of
popular solvers before deployment.

Tue 10 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change

08:00 - 08:02
Talk
Boosting Fuzzer Efficiency: An Information Theoretic PerspectiveACM SIGSOFT Distinguished Paper Award
Research Papers
Marcel BöhmeMonash University, Australia, Valentin ManèsKAIST, South Korea, Sang Kil ChaKAIST, South Korea
DOI
08:03 - 08:04
Talk
CrFuzz: Fuzzing Multi-purpose Programs through Input Validation
Research Papers
Suhwan SongSeoul National University, South Korea, Chengyu SongUniversity of California at Riverside, USA, Yeongjin JangOregon State University, USA, Byoungyoung LeeSeoul National University, South Korea
DOI
08:05 - 08:06
Talk
Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing
Research Papers
Muhammad Numair MansurMPI-SWS, Germany, Maria ChristakisMPI-SWS, Valentin WüstholzConsenSys, Fuyuan ZhangMPI-SWS, Germany
DOI Pre-print
08:07 - 08:08
Talk
Fuzzing: On the Exponential Cost of Vulnerability Discovery
Research Papers
Marcel BöhmeMonash University, Australia, Brandon FalkGamozo Labs, n.n.
DOI
08:09 - 08:10
Talk
Harvey: A Greybox Fuzzer for Smart Contracts
Industry Papers
DOI Pre-print
08:11 - 08:12
Talk
Intelligent REST API Data Fuzzing
Research Papers
Patrice GodefroidMicrosoft Research, USA, Bo-Yuan HuangPrinceton University, USA, Marina PolishchukMicrosoft Research, USA
DOI
08:13 - 08:14
Talk
MTFuzz: Fuzzing with a Multi-task Neural Network
Research Papers
Dongdong SheColumbia University, USA, Rahul KrishnaColumbia University, USA, Lu YanShanghai Jiao Tong University, China, Suman JanaColumbia University, USA, Baishakhi RayColumbia University, USA
DOI Pre-print
08:15 - 08:30
Talk
Conversations on Fuzzing
Research Papers
Dongdong SheColumbia University, USA, Muhammad Numair MansurMPI-SWS, Germany, Marcel BöhmeMonash University, Australia, Suhwan SongSeoul National University, South Korea, Valentin WüstholzConsenSys, M: Mike PapadakisUniversity of Luxembourg, Luxembourg