The Good, The Bad and The Ugly: Pitfalls and Best Practices in Automated Sound Static Analysis of Ethereum Smart Contracts

Schneidewind, Clara; Scherer, Markus; Maffei, Matteo

doi:10.1007/978-3-030-61467-6_14

Cited by 6 publications

(7 citation statements)

References 24 publications

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“…As recently demonstrated in the literature [25], the sound analysis of Ethereum smart contracts is a challenging problem; most analysis tools aiming at provable soundness guarantees fall short of their goal. This can be mainly attributed to the non-standard language features of the EVM bytecode language and the unusual execution model of the EVM: Smart contracts are executed in a (potentially) hostile environment, which can interact with, and even, schedule contracts.…”

Section: Challenges In Sound Dependency Analysismentioning

confidence: 99%

“…In this way, smart contract developers and users can reliably identify and eliminate harmful behavior before publishing or interacting with Ethereum smart contracts. However, as shown in recent works [24], [25], most automatic static analyzers for Ethereum smart contracts that promise soundness guarantees cannot live up to their soundness claims.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, the only tools targeting sound and automated static analyses of smart contract security properties are Securify [27], ZEUS [18], EtherTrust [13], NeuCheck [21], and eThor [24]. The soundness claims of ZEUS, Securify, EtherTrust, and NeuCheck are systematically confuted in [25] and [24].…”

Section: Introductionmentioning

confidence: 99%

“…• We study the root causes of the soundness issues of the state-of-the-art Ethereum smart contract analysis tool Securify [27] that so far had only been reported through empirical evidence in [24], [25]. In this course, we uncover new soundness problems in Securify's analysis, which we can show to affect real-world smart contracts.…”

Section: Introductionmentioning

confidence: 99%

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HoRStify: Sound Security Analysis of Smart Contracts

Holler¹,

Biewer²,

Schneidewind³

2023

Preprint

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The cryptocurrency Ethereum is the most widely used execution platform for smart contracts. Smart contracts are distributed applications, which govern financial assets and, hence, can implement advanced financial instruments, such as decentralized exchanges or autonomous organizations (DAOs). Their financial nature makes smart contracts an attractive attack target, as demonstrated by numerous exploits on popular contracts resulting in financial damage of millions of dollars. This omnipresent attack hazard motivates the need for sound static analysis tools, which assist smart contract developers in eliminating contract vulnerabilities a priori to deployment.Vulnerability assessment that is sound and insightful for EVM contracts is a formidable challenge because contracts execute low-level bytecode in a largely unknown and potentially hostile execution environment. So far, there exists no provably sound automated analyzer that allows for the verification of security properties based on program dependencies, even though prevalent attack classes fall into this category. In this work, we present HORSTIFY, the first automated analyzer for dependency properties of Ethereum smart contracts based on sound static analysis. HORSTIFY grounds its soundness proof on a formal proof framework for static program slicing that we instantiate to the semantics of EVM bytecode. We demonstrate that HORSTIFY is flexible enough to soundly verify the absence of famous attack classes such as timestamp dependency and, at the same time, performant enough to analyze real-world smart contracts.

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Section: Challenges In Sound Dependency Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

HoRStify: Sound Security Analysis of Smart Contracts

Holler¹,

Biewer²,

Schneidewind³

2023

Preprint

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“…Table 1 illustrates this by comparing the informal specifications of one specific property (Section 5. 4.19) in the studies [179,203]. In developing this survey, we worked to strike a balance in dealing with such variations.…”

Section: Related Workmentioning

confidence: 99%

Pre-deployment Analysis of Smart Contracts -- A Survey

Munir¹,

Taha²

2023

Preprint

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Smart contracts are programs that execute transactions involving independent parties and cryptocurrencies. As programs, smart contracts are susceptible to a wide range of errors and vulnerabilities. Such vulnerabilities can result in significant losses. Furthermore, by design, smart contract transactions are irreversible. This creates a need for methods to ensure the correctness and security of contracts pre-deployment. Recently there has been substantial research into such methods. The sheer volume of this research makes articulating state-of-the-art a substantial undertaking. To address this challenge, we present a systematic review of the literature. A key feature of our presentation is to factor out the relationship between vulnerabilities and methods through properties. Specifically, we enumerate and classify smart contract vulnerabilities and methods by the properties they address. The methods considered include static analysis as well as dynamic analysis methods and machine learning algorithms that analyze smart contracts before deployment.Several patterns about the strengths of different methods emerge through this classification process.CCS Concepts: • General and reference → Surveys and overviews; • Software and its engineering → Automated static analysis; Dynamic analysis; Software verification.

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