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Empirical Vulnerability Analysis of Automated Smart Contracts Security Testing on Blockchains

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arxiv 1809.02702 v1 pith:2FQHKJO2 submitted 2018-09-07 cs.CR

classification cs.CR
keywords contractssmartsecurityblockchaintestingvulnerabilitiesapplicationbefore
verification ladder T0 review T1 audit T2 compute T3 formal

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The emerging blockchain technology supports decentralized computing paradigm shift and is a rapidly approaching phenomenon. While blockchain is thought primarily as the basis of Bitcoin, its application has grown far beyond cryptocurrencies due to the introduction of smart contracts. Smart contracts are self-enforcing pieces of software, which reside and run over a hosting blockchain. Using blockchain-based smart contracts for secure and transparent management to govern interactions (authentication, connection, and transaction) in Internet-enabled environments, mostly IoT, is a niche area of research and practice. However, writing trustworthy and safe smart contracts can be tremendously challenging because of the complicated semantics of underlying domain-specific languages and its testability. There have been high-profile incidents that indicate blockchain smart contracts could contain various code-security vulnerabilities, instigating financial harms. When it involves security of smart contracts, developers embracing the ability to write the contracts should be capable of testing their code, for diagnosing security vulnerabilities, before deploying them to the immutable environments on blockchains. However, there are only a handful of security testing tools for smart contracts. This implies that the existing research on automatic smart contracts security testing is not adequate and remains in a very stage of infancy. With a specific goal to more readily realize the application of blockchain smart contracts in security and privacy, we should first understand their vulnerabilities before widespread implementation. Accordingly, the goal of this paper is to carry out a far-reaching experimental assessment of current static smart contracts security testing tools, for the most widely used blockchain, the Ethereum and its domain-specific programming language, Solidity to provide the first...

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Cited by 2 Pith papers

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  1. Automated Vulnerability Injection in Solidity Smart Contracts: A Mutation-Based Approach for Benchmark Development

    cs.SE 2025-04 conditional novelty 5.0 of 10

    MuSe injects six vulnerability types into 47,398 real smart contracts, producing 350,493 mutated contracts, and Slither detects only 59.7% of the injected flaws.

  2. Enhancing Reliability of Symbolic Execution Tools for Smart Contract Analysis through Rule-Based False Positive Reduction

    cs.SE 2026-08 conditional novelty 3.0 of 10

    Adding six rule-based filters to Mythril cut false positives by 50.0% on clean contracts and 89.2% on vulnerable contracts in the Gigahorse benchmark, while keeping true positives roughly unchanged.

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