WalletRadar:实现自动检测基于浏览器的加密货币钱包中的漏洞

IF 2 2区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Pengcheng Xia, Yanhui Guo, Zhaowen Lin, Jun Wu, Pengbo Duan, Ningyu He, Kailong Wang, Tianming Liu, Yinliang Yue, Guoai Xu, Haoyu Wang
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引用次数: 0

摘要

加密货币钱包作为区块链生态系统的基础架构,用户数量大幅增长,尤其是基于浏览器的钱包(即浏览器扩展)。然而,这种增长伴随着安全挑战,使这些钱包成为恶意活动的主要目标。尽管用户基数庞大,但在全面安全分析方面不仅存在巨大差距,而且迫切需要能帮助开发人员在开发过程中减少漏洞的专业工具。为了填补这一空白,我们在本文中对基于浏览器的钱包进行了全面的安全分析,并为此开发了一款自动工具。我们首先通过收集历史安全报告,对加密货币钱包中存在的安全漏洞进行分类。在此基础上,我们设计了一个自动检测框架 WalletRadar,它可以根据静态和动态分析准确识别安全问题。对 96 个流行的基于浏览器的钱包进行的评估显示了 WalletRadar 的有效性,它成功地对其中 90% 的钱包进行了高精度的自动检测。通过评估,我们发现了 70 个钱包的 116 个安全漏洞。截至本文发稿时,我们已收到 8 个钱包开发商对 10 个漏洞的确认,漏洞赏金超过 2000 美元。此外,我们还观察到,在我们的利益冲突之后,有 12 家钱包开发商悄悄修复了 16 个漏洞。WalletRadar 可以有效地自动识别加密货币钱包中的安全风险,从而提高区块链生态系统中的软件开发质量和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

WalletRadar: towards automating the detection of vulnerabilities in browser-based cryptocurrency wallets

WalletRadar: towards automating the detection of vulnerabilities in browser-based cryptocurrency wallets

Cryptocurrency wallets, acting as fundamental infrastructure to the blockchain ecosystem, have seen significant user growth, particularly among browser-based wallets (i.e., browser extensions). However, this expansion accompanies security challenges, making these wallets prime targets for malicious activities. Despite a substantial user base, there is not only a significant gap in comprehensive security analysis but also a pressing need for specialized tools that can aid developers in reducing vulnerabilities during the development process. To fill the void, we present a comprehensive security analysis of browser-based wallets in this paper, along with the development of an automated tool designed for this purpose. We first compile a taxonomy of security vulnerabilities resident in cryptocurrency wallets by harvesting historical security reports. Based on this, we design WalletRadar, an automated detection framework that can accurately identify security issues based on static and dynamic analysis. Evaluation of 96 popular browser-based wallets shows WalletRadar’s effectiveness, by successfully automating the detection process in 90% of these wallets with high precision. This evaluation has led to the discovery of 116 security vulnerabilities corresponding to 70 wallets. By the time of this paper, we have received confirmations of 10 vulnerabilities from 8 wallet developers, with over $2,000 bug bounties. Further, we observed that 12 wallet developers have silently fixed 16 vulnerabilities after our Conflict of interest. WalletRadar can effectively automate the identification of security risks in cryptocurrency wallets, thereby enhancing software development quality and safety in the blockchain ecosystem.

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来源期刊
Automated Software Engineering
Automated Software Engineering 工程技术-计算机:软件工程
CiteScore
4.80
自引率
11.80%
发文量
51
审稿时长
>12 weeks
期刊介绍: This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes. Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.
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