SMARTIAN: Enhancing Smart Contract Fuzzing with Static and Dynamic Data-Flow Analyses

Jaeseung Choi, Doyeon Kim, Soomin Kim, Gustavo Grieco, Alex Groce, Sang Kil Cha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Unlike traditional software, smart contracts have the unique organization in which a sequence of transactions shares persistent states. Unfortunately, such a characteristic makes it difficult for existing fuzzers to find out critical transaction sequences. To tackle this challenge, we employ both static and dynamic analyses for fuzzing smart contracts. First, we statically analyze smart contract bytecodes to predict which transaction sequences will lead to effective testing, and figure out if there is a certain constraint that each transaction should satisfy. Such information is then passed to the fuzzing phase and used to construct an initial seed corpus. During a fuzzing campaign, we perform a lightweight dynamic data-flow analysis to collect data-flow-based feedback to effectively guide fuzzing. We implement our ideas on a practical open-source fuzzer, named SMARTIAN. SMARTIAN can discover bugs in real-world smart contracts without the need for the source code. Our experimental results show that SMARTIAN is more effective than existing state-of-the-art tools in finding known CVEs from real-world contracts. SMARTIAN also outperforms other tools in terms of code coverage.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages227-239
Number of pages13
ISBN (Electronic)9781665403375
DOIs
StatePublished - 2021
Externally publishedYes
Event36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021 - Virtual, Online, Australia
Duration: Nov 15 2021Nov 19 2021

Publication series

NameProceedings - 2021 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021

Conference

Conference36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021
Country/TerritoryAustralia
CityVirtual, Online
Period11/15/2111/19/21

Keywords

  • Fuzzing
  • Smart contract
  • Software testing
  • Static analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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