Hunting DeFi Vulnerabilities via Context-Sensitive Concolic Verification

Fuente: arXiv
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Main Authors: Ding, Yepeng, Gervais, Arthur, Wattenhofer, Roger, Sato, Hiroyuki
Format: Preprint
Published: 2024
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author Ding, Yepeng
Gervais, Arthur
Wattenhofer, Roger
Sato, Hiroyuki
author_facet Ding, Yepeng
Gervais, Arthur
Wattenhofer, Roger
Sato, Hiroyuki
contents Decentralized finance (DeFi) is revolutionizing the traditional centralized finance paradigm with its attractive features such as high availability, transparency, and tamper-proofing. However, attacks targeting DeFi services have severely damaged the DeFi market, as evidenced by our investigation of 80 real-world DeFi incidents from 2017 to 2022. Existing methods, based on symbolic execution, model checking, semantic analysis, and fuzzing, fall short in identifying the most DeFi vulnerability types. To address the deficiency, we propose Context-Sensitive Concolic Verification (CSCV), a method of automating the DeFi vulnerability finding based on user-defined properties formulated in temporal logic. CSCV builds and optimizes contexts to guide verification processes that dynamically construct context-carrying transition systems in tandem with concolic executions. Furthermore, we demonstrate the effectiveness of CSCV through experiments on real-world DeFi services and qualitative comparison. The experiment results show that our CSCV prototype successfully detects 76.25% of the vulnerabilities from the investigated incidents with an average time of 253.06 seconds.
format Preprint
id arxiv_https___arxiv_org_abs_2404_10376
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hunting DeFi Vulnerabilities via Context-Sensitive Concolic Verification
Ding, Yepeng
Gervais, Arthur
Wattenhofer, Roger
Sato, Hiroyuki
Software Engineering
Decentralized finance (DeFi) is revolutionizing the traditional centralized finance paradigm with its attractive features such as high availability, transparency, and tamper-proofing. However, attacks targeting DeFi services have severely damaged the DeFi market, as evidenced by our investigation of 80 real-world DeFi incidents from 2017 to 2022. Existing methods, based on symbolic execution, model checking, semantic analysis, and fuzzing, fall short in identifying the most DeFi vulnerability types. To address the deficiency, we propose Context-Sensitive Concolic Verification (CSCV), a method of automating the DeFi vulnerability finding based on user-defined properties formulated in temporal logic. CSCV builds and optimizes contexts to guide verification processes that dynamically construct context-carrying transition systems in tandem with concolic executions. Furthermore, we demonstrate the effectiveness of CSCV through experiments on real-world DeFi services and qualitative comparison. The experiment results show that our CSCV prototype successfully detects 76.25% of the vulnerabilities from the investigated incidents with an average time of 253.06 seconds.
title Hunting DeFi Vulnerabilities via Context-Sensitive Concolic Verification
topic Software Engineering
url https://arxiv.org/abs/2404.10376