JANUS: A Difference-Oriented Analyzer For Financial Centralization Risks in Smart Contracts

TL;DR

JANUS is an automated tool that detects financial centralization risks in smart contracts by analyzing state differences, improving accuracy and uncovering unknown risk patterns compared to existing methods.

Contribution

JANUS introduces a difference-oriented analysis approach that identifies centralization risks independently of specific behaviors, enhancing detection accuracy and uncovering previously undetectable risks.

Findings

JANUS outperforms existing tools in detection accuracy.

It successfully identifies risks in large real-world datasets.

The state traversal method does not cause false alarms.

Abstract

Some smart contracts violate decentralization principles by defining privileged accounts that manage other users' assets without permission, introducing centralization risks that have caused financial losses. Existing methods, however, face challenges in accurately detecting diverse centralization risks due to their dependence on predefined behavior patterns. In this paper, we propose JANUS, an automated analyzer for Solidity smart contracts that detects financial centralization risks independently of their specific behaviors. JANUS identifies differences between states reached by privileged and ordinary accounts, and analyzes whether these differences are finance-related. Focusing on the impact of risks rather than behaviors, JANUS achieves improved accuracy compared to existing tools and can uncover centralization risks with unknown patterns. To evaluate JANUS's performance, we compare it with other tools using a dataset of 540 contracts. Our evaluation demonstrates that JANUS outperforms representative tools in terms of detection accuracy for financial centralization risks . Additionally, we evaluate JANUS on a real-world dataset of 33,151 contracts, successfully identifying two types of risks that other tools fail to detect. We also prove that the state traversal method and variable summaries, which are used in JANUS to reduce the number of states to be compared, do not introduce false alarms or omissions in detection.