Pith. sign in

REVIEW

DEFECTCHECKER: Automated Smart Contract Defect Detection by Analyzing EVM Bytecode

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2009.02663 v2 pith:NRT5K4HN submitted 2020-09-06 cs.SE

DEFECTCHECKER: Automated Smart Contract Defect Detection by Analyzing EVM Bytecode

classification cs.SE
keywords contractsmartcontractsdefectcheckerdefectsblockchainbehaviorsbugs
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
Share X Bluesky LinkedIn Reddit HN
read the original abstract

Smart contracts are Turing-complete programs running on the blockchain. They are immutable and cannot be modified, even when bugs are detected. Therefore, ensuring smart contracts are bug-free and well-designed before deploying them to the blockchain is extremely important. A contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. Detecting and removing contract defects can avoid potential bugs and make programs more robust. Our previous work defined 20 contract defects for smart contracts and divided them into five impact levels. According to our classification, contract defects with seriousness level between 1-3 can lead to unwanted behaviors, e.g., a contract being controlled by attackers. In this paper, we propose DefectChecker, a symbolic execution-based approach and tool to detect eight contract defects that can cause unwanted behaviors of smart contracts on the Ethereum blockchain platform. DefectChecker can detect contract defects from smart contracts bytecode. We compare DefectChecker with key previous works, including Oyente, Mythril and Securify by using an open-source dataset. Our experimental results show that DefectChecker performs much better than these tools in terms of both speed and accuracy. We also applied DefectChecker to 165,621 distinct smart contracts on the Ethereum platform. We found that 25,815 of these smart contracts contain at least one of the contract defects that belongs to impact level 1-3, including some real-world attacks.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.