Noama Fatima Samreen

Noama Fatima Samreen, Manar H. Alalfi

Ethereum Smart Contracts based on Blockchain Technology (BT)enables monetary transactions among peers on a blockchain network independent of a central authorizing agency. Ethereum smart contracts are programs that are deployed as decentralized applications, having the building blocks of the blockchain consensus protocol. This enables consumers to make agreements in a transparent and conflict-free environment. However, there exist some security vulnerabilities within these smart contracts that are a potential threat to the applications and their consumers and have shown in the past to cause huge financial losses. In this study, we review the existing literature and broadly classify the BT applications. As Ethereum smart contracts find their application mostly in e-commerce applications, we believe these are more commonly vulnerable to attacks. In these smart contracts, we mainly focus on identifying vulnerabilities that programmers and users of smart contracts must avoid. This paper aims at explaining eight vulnerabilities that are specific to the application level of BT by analyzing the past exploitation case scenarios of these security vulnerabilities. We also review some of the available tools and applications that detect these vulnerabilities in terms of their approach and effectiveness. We also investigated the availability of detection tools for identifying these security vulnerabilities and lack thereof to identify some of them

Noama Fatima Samreen, Manar H. Alalfi

Ethereum Smart contracts use blockchain to transfer values among peers on networks without central agency. These programs are deployed on decentralized applications running on top of the blockchain consensus protocol to enable people to make agreements in a transparent and conflict-free environment. The security vulnerabilities within those smart contracts are a potential threat to the applications and have caused huge financial losses to their users. In this paper, we present a framework that combines static and dynamic analysis to detect Reentrancy vulnerabilities in Ethereum smart contracts. This framework generates an attacker contract based on the ABI specifications of smart contracts under test and analyzes the contract interaction to precisely report Reentrancy vulnerability. We conducted a preliminary evaluation of our proposed framework on 5 modified smart contracts from Etherscan and our framework was able to detect the Reentrancy vulnerability in all our modified contracts. Our framework analyzes smart contracts statically to identify potentially vulnerable functions and then uses dynamic analysis to precisely confirm Reentrancy vulnerability, thus achieving increased performance and reduced false positives.

Noama Fatima Samreen, Manar H. Alalfi

Blockchain technology (BT) Ethereum Smart Contracts allows programmable transactions that involve the transfer of monetary assets among peers on a BT network independent of a central authorizing agency. Ethereum Smart Contracts are programs that are deployed as decentralized applications, having the building blocks of the blockchain consensus protocol. This technology enables consumers to make agreements in a transparent and conflict-free environment. However, the security vulnerabilities within these smart contracts are a potential threat to the applications and their consumers and have shown in the past to cause huge financial losses. In this paper, we propose a framework that combines static and dynamic analysis to detect Denial of Service (DoS) vulnerability due to an unexpected revert in Ethereum Smart Contracts. Our framework, SmartScan, statically scans smart contracts under test (SCUTs) to identify patterns that are potentially vulnerable in these SCUTs and then uses dynamic analysis to precisely confirm their exploitability of the DoS-Unexpected Revert vulnerability, thus achieving increased performance and more precise results. We evaluated SmartScan on a set of 500 smart contracts collected from the Etherscan. Our approach shows an improvement in precision and recall when compared to available state-of-the-art techniques.