sCompile: Critical Path Identification and Analysis for Smart Contracts

Abstract

Smart contracts are an innovation built on top of the blockchain technology. It provides a platform for automatically executing contracts in an anonymous, distributed, and trusted way, which has the potential to revolutionize many industries. The most popular programming language for creating smart contracts is called Solidity, which is supported by Ethereum. Like ordinary programs, Solidity programs may contain vulnerabilities, which potentially lead to attacks. The problem is magnified by the fact that smart contracts, unlike ordinary programs, cannot be patched easily once deployed. It is thus important that smart contracts are checked against potential vulnerabilities.Existing approaches tackle the problem by developing methods which aim to automatically analyze or verify smart contracts. Such approaches often results in false alarms or poor scalability, fundamentally because Solidity is Turing-complete. In this work, we propose an alternative approach to automatically identify critical program paths (with multiple function calls including inter-contract function calls) in a smart contract, rank the paths according to their criticalness, discard them if they are infeasible or otherwise present them with user friendly warnings for user inspection. We identify paths which involve monetary transaction as critical paths, and prioritize those which potentially violate important properties. For scalability, symbolic execution techniques are only applied to top ranked critical paths. Our approach has been implemented in a tool called sCompile, which has been applied to 36,099 smart contracts. The experiment results show that sCompile is efficient, i.e., 5 seconds on average for one smart contract. Furthermore, we show that many known vulnerability can be captured if the user inspects as few as 10 program paths generated by sCompile. Lastly, sCompile discovered 224 unknown vulnerabilities with a false positive rate of 15.4% before user inspection.

SODA: A Generic Online Detection Framework for Smart Contracts

“…teEther leverages SE to discover vulnerabilities and generate transactions which can attack vulnerable smart contracts [65]. sCompile ranks the program paths according to their criticalness, and applies SE to discover vulnerabilities by exploring the topranked critical paths [14]. ContractFuzzer leverages fuzzing to reveal vulnerabilities [12].…”

Towards Analyzing the Complexity Landscape of Solidity Based Ethereum Smart Contracts

“…There are works addressing vulnerability detection in smart contracts with other strategies as well [35][36][37]. Liu et al proposed a novel semantic-aware security auditing technique called S-gram for Ethereum [35].…”

“…Chang et al propose an alternative approach to automatically identify critical program paths (with multiple function calls including inter-contract function calls) in a smart contract, rank the paths according to their criticalness, discard them if they are infeasible or otherwise present them with user-friendly warnings for user inspection [37]. Their approach has been implemented in a tool called sCompile.…”

A first look at blockchain‐based decentralized applications

“…The other accessible data are smart contracts, for example, their bytecode written in the blocks. There are some work analyzing these code to give advises for smart contract developers and blockchain users [25], [26], [46]. Researchers also try to decompile them into source code [47] so that more approaches to source code analysis can be used.…”