TokenScope: Automatically detecting inconsistent behaviors of cryptocurrency tokens in ethereum

Ting Chen, Xiapu Luo, Yufei Zhang, Ting Wang, Zihao Li, Rong Cao, Xiuzhuo Xiao, Xiaosong Zhang

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

1 Scopus citations

Abstract

Motivated by the success of Bitcoin, lots of cryptocurrencies have been created, the majority of which were implemented as smart contracts running on Ethereum and called tokens. To regulate the interaction between these tokens and users as well as third-party tools (e.g., wallets, exchange markets, etc.), several standards have been proposed for the implementation of token contracts. Although existing tokens involve lots of money, little is known whether or not their behaviors are consistent with the standards. Inconsistent behaviors can lead to user confusion and financial loss, because users/third-party tools interact with token contracts by invoking standard interfaces and listening to standard events. In this work, we take the first step to investigate such inconsistent token behaviors with regard to ERC-20, the most popular token standard. We propose a novel approach to automatically detect such inconsistency by contrasting the behaviors derived from three different sources, including the manipulations of core data structures recording the token holders and their shares, the actions indicated by standard interfaces, and the behaviors suggested by standard events. We implement our approach in a new tool named TokenScope and use it to inspect all transactions sent to the deployed tokens. We detected 3,259,001 transactions that trigger inconsistent behaviors, and these behaviors resulted from 7,472 tokens. By manually examining all (2,353) open-source tokens having inconsistent behaviors, we found that the precision of TokenScope is above 99.9%. Moreover, we revealed 11 major reasons behind the inconsistency, e.g., flawed tokens, standard methods missing, lack of standard events, etc. In particular, we discovered 50 unreported flawed tokens.

Original languageEnglish (US)
Title of host publicationCCS 2019 - Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages1503-1520
Number of pages18
ISBN (Electronic)9781450367479
DOIs
StatePublished - Nov 6 2019
Event26th ACM SIGSAC Conference on Computer and Communications Security, CCS 2019 - London, United Kingdom
Duration: Nov 11 2019Nov 15 2019

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference26th ACM SIGSAC Conference on Computer and Communications Security, CCS 2019
CountryUnited Kingdom
CityLondon
Period11/11/1911/15/19

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'TokenScope: Automatically detecting inconsistent behaviors of cryptocurrency tokens in ethereum'. Together they form a unique fingerprint.

Cite this