Toward Automated Discovery of Asymmetric Mempool DoS in Blockchains

IF 6 1区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

IEEE Transactions on Software Engineering Pub Date : 2026-08-01 Epub Date: 2026-06-01 DOI:10.1109/TSE.2026.3698791

Yibo Wang;Yuzhe Tang;Kai Li;Wanning Ding

引用次数: 0

Abstract

In blockchains, mempool controls transaction flow before consensus, denial of whose service hurts the health and security of blockchain networks. This paper presents mpfuzz, the first mempool fuzzer to find asymmetric DoS bugs by exploring the space of symbolized mempool states and optimistically estimating the promisingness of an intermediate state in reaching bug oracles. Compared to the baseline blockchain fuzzers, mpfuzz achieves a

$\mathbf{\gt 100\times}$

speedup in finding known DETER exploits. Running mpfuzz on major Ethereum clients leads to discovering new mempool vulnerabilities, which exhibit a wide variety of sophisticated patterns, including stealthy mempool eviction and mempool locking. Rule-based mitigation schemes are proposed against all newly discovered vulnerabilities.

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区块链中不对称内存池DoS的自动发现

在区块链中，mempool在共识之前控制交易流，拒绝其服务会损害区块链网络的健康和安全。mpfuzz是第一个发现不对称DoS错误的内存池模糊器，它通过探索符号化内存池状态的空间，并乐观地估计到达错误指示的中间状态的希望。与基准区块链fuzzers相比，mpfuzz在查找已知的DETER漏洞方面实现了$\mathbf{\gt $ 100\倍}$的加速。在主要的以太坊客户端上运行mpfuzz会发现新的内存池漏洞，这些漏洞表现出各种复杂的模式，包括隐形内存池驱逐和内存池锁定。针对所有新发现的漏洞，提出了基于规则的缓解方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Software Engineering 工程技术-工程：电子与电气

CiteScore

9.70

自引率

10.80%

发文量

724

审稿时长

6 months

期刊介绍： IEEE Transactions on Software Engineering seeks contributions comprising well-defined theoretical results and empirical studies with potential impacts on software construction, analysis, or management. The scope of this Transactions extends from fundamental mechanisms to the development of principles and their application in specific environments. Specific topic areas include: a) Development and maintenance methods and models: Techniques and principles for specifying, designing, and implementing software systems, encompassing notations and process models. b) Assessment methods: Software tests, validation, reliability models, test and diagnosis procedures, software redundancy, design for error control, and measurements and evaluation of process and product aspects. c) Software project management: Productivity factors, cost models, schedule and organizational issues, and standards. d) Tools and environments: Specific tools, integrated tool environments, associated architectures, databases, and parallel and distributed processing issues. e) System issues: Hardware-software trade-offs. f) State-of-the-art surveys: Syntheses and comprehensive reviews of the historical development within specific areas of interest.