2021 XI Brazilian Symposium on Computing Systems Engineering (SBESC) 2021
DOI: 10.1109/sbesc53686.2021.9628229
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Verifying Security Vulnerabilities for Blockchain-based Smart Contracts

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Cited by 7 publications
(3 citation statements)
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“…4.30 SWE-134: Message call with hardcoded gas amount Hard forks may result in a considerable shift in the gas cost of EVM instructions, which might disrupt currently deployed contract systems that base their assumptions on constant gas prices. Therefore, hardcoding the amount of gas that a call may consume could in the future lead to DOS as the hard-coded gas amount might become insufficient [7], [27]. For example, Due to the SLOAD instruction's cost rise, the EIP 1884 damaged many existing smart contracts.…”
Section: Swe-133: Hash Collisions With Multiple Variable Length Argum...mentioning
confidence: 99%
See 1 more Smart Citation
“…4.30 SWE-134: Message call with hardcoded gas amount Hard forks may result in a considerable shift in the gas cost of EVM instructions, which might disrupt currently deployed contract systems that base their assumptions on constant gas prices. Therefore, hardcoding the amount of gas that a call may consume could in the future lead to DOS as the hard-coded gas amount might become insufficient [7], [27]. For example, Due to the SLOAD instruction's cost rise, the EIP 1884 damaged many existing smart contracts.…”
Section: Swe-133: Hash Collisions With Multiple Variable Length Argum...mentioning
confidence: 99%
“…The 0.4.22 version of the solidity compiler allows smart contracts to have a double constructor. This could lead to unexpected behavior in the contract [27]. Vulnerable code line (5,8) Figure 26:…”
Section: Swe-146: Double Constructormentioning
confidence: 99%
“…We found various countermeasures. These comprise checking the smart contract and verifying the source code [131], logic analysis [101], security tools [103,116,117,120,122,124,126], flow analysis [115], visualization tools, disassembler and decompiler, linter, and miscellaneous tools [103], static and dynamic analysis [103,119,120], symbolic execution, formal verification [103], differential fuzzing [107], deep learning [109], and verification of identities [122], among others. Ivanov et al [106] propose a taxonomy with static analysis, symbolic execution, fuzzing, formal analysis, machine learning methods, execution tracing, and transaction interception.…”
Section: Countermeasuresmentioning
confidence: 99%