End-to-End Formal Verification of Ethereum 2.0 Deposit Smart Contract

We report our experience in the formal verification of the deposit smart contract, whose correctness is critical for the security of Ethereum 2.0, a new Proof-of-Stake protocol for the Ethereum blockchain. The deposit contract implements an incremental Merkle tree algorithm whose correctness is highly nontrivial, and had not been proved before. We have verified the correctness of the compiled bytecode of the deposit contract to avoid the need to trust the underlying compiler. We found several critical issues of the deposit contract during the verification process, some of which were due to subtle hidden bugs of the compiler.Ope

The Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts

Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise, where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying seemingly vulnerable contracts that contain hidden traps. This new type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypot smart contracts, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HoneyBadger - a tool that employs symbolic execution and well defined heuristics to expose honeypots. We perform a large-scale analysis on more than 2 million smart contracts and show that our tool not only achieves high precision, but is also highly efficient. We identify 690 honeypot smart contracts as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots

Pre-deployment Analysis of Smart Contracts -- A Survey

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

Empirical Review of Smart Contract and DeFi Security: Vulnerability Detection and Automated Repair

Decentralized Finance (DeFi) is emerging as a peer-to-peer financial ecosystem, enabling participants to trade products on a permissionless blockchain. Built on blockchain and smart contracts, the DeFi ecosystem has experienced explosive growth in recent years. Unfortunately, smart contracts hold a massive amount of value, making them an attractive target for attacks. So far, attacks against smart contracts and DeFi protocols have resulted in billions of dollars in financial losses, severely threatening the security of the entire DeFi ecosystem. Researchers have proposed various security tools for smart contracts and DeFi protocols as countermeasures. However, a comprehensive investigation of these efforts is still lacking, leaving a crucial gap in our understanding of how to enhance the security posture of the smart contract and DeFi landscape. To fill the gap, this paper reviews the progress made in the field of smart contract and DeFi security from the perspective of both vulnerability detection and automated repair. First, we analyze the DeFi smart contract security issues and challenges. Specifically, we lucubrate various DeFi attack incidents and summarize the attacks into six categories. Then, we present an empirical study of 42 state-of-the-art techniques that can detect smart contract and DeFi vulnerabilities. In particular, we evaluate the effectiveness of traditional smart contract bug detection tools in analyzing complex DeFi protocols. Additionally, we investigate 8 existing automated repair tools for smart contracts and DeFi protocols, providing insight into their advantages and disadvantages. To make this work useful for as wide of an audience as possible, we also identify several open issues and challenges in the DeFi ecosystem that should be addressed in the future.Comment: This paper is submitted to the journal of Expert Systems with Applications (ESWA) for revie

Resource Analysis of Ethereum 2.0 Clients

Scalability is a common issue among the most used permissionless blockchains, and several approaches have been proposed accordingly. As Ethereum is set to be a solid foundation for a decentralized Internet web, the need for tackling scalability issues while preserving the security of the network is an important challenge. In order to successfully deliver effective scaling solutions, Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), which implements sharding. As the change of consensus mechanism is an extremely delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. For this, a specification has been developed and multiple groups have implemented clients to run the new protocol. In this work, we analyse the resource usage behaviour of different clients running as Eth2 nodes, comparing their performance and analysing differences. Our results show multiple network perturbations and how different clients react to it

ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection

Decentralized cryptocurrencies feature the use of blockchain to transfer values among peers on networks without central agency. Smart contracts are programs running on top of the blockchain consensus protocol to enable people make agreements while minimizing trusts. Millions of smart contracts have been deployed in various decentralized applications. The security vulnerabilities within those smart contracts pose significant threats to their applications. Indeed, many critical security vulnerabilities within smart contracts on Ethereum platform have caused huge financial losses to their users. In this work, we present ContractFuzzer, a novel fuzzer to test Ethereum smart contracts for security vulnerabilities. ContractFuzzer generates fuzzing inputs based on the ABI specifications of smart contracts, defines test oracles to detect security vulnerabilities, instruments the EVM to log smart contracts runtime behaviors, and analyzes these logs to report security vulnerabilities. Our fuzzing of 6991 smart contracts has flagged more than 459 vulnerabilities with high precision. In particular, our fuzzing tool successfully detects the vulnerability of the DAO contract that leads to USD 60 million loss and the vulnerabilities of Parity Wallet that have led to the loss of $30 million and the freezing of USD 150 million worth of Ether.Comment: To appear in ASE 2018, Montpellier, France. 10 page