Smart contracts are programs with data (mutable state); stored on and executed by blockchain platforms. The transactions (or function invocations) dispatched to smart contracts often change their state. In the Ethereum blockchain, nodes (aka miners/validators) can schedule a set of transactions in any order in a block. Multiple transactions in a single block operating on a contract's shared state may yield different outcomes based on their execution order, thus creating a possibility for non-determinism and races between transactions. The resulting issue in Ethereum smart contracts is Transaction Ordering Dependency (TOD). Detecting a TOD requires identifying valid transactions affecting a contract's global/state variables which is equivalent to detecting read-after-write dependencies in race detection, and we expect it to be similarly nontrivial for human developers. In this paper, we identify various TODs, including a novel type previously undocumented in the literature. To detect these TODs, we propose an information flow analysis-based static analyzer, TODler. Our manual evaluation of 108 Ethereum smart contracts shows that TODler outperforms previously available approaches in terms of both run time and precision and also detects the novel TOD pattern identified in this paper. © 2023 IEEE

Smart contracts are programs with mutable state. Transactions submitted to these contracts trigger functions that often modify state. Nodes of the Ethereum blockchain schedule such transactions in a nondeterministic order, potentially leading to races between transactions and concurrency issues. When the outcome of a smart contract varies depending on the order in which transactions are processed, we have a Transaction Ordering Dependency (TOD). TOD enables malicious actors to profit from a smart contract, similar to the well-known frontrunning vulnerability. Existing approaches for detecting TOD in Ethereum smart contracts yield a high rate of false positives and false negatives. To help contract developers and testers detect TOD vulnerabilities with enhanced precision, we propose and evaluate an analysis based on information flow in our tool TODChecker1 . We evaluate our approach using a benchmark comprising 513 vulnerable transactions involving 235 real-world Ethereum smart contracts susceptible to frontrunning attacks. Our evaluation finds that our approach outperforms existing approaches, including Oyente, Securify, SAILFISH, TODler, and Nyx, in precision, runtime, and in identifying novel TOD vulnerabilities. © 2024 Copyright held by the owner/author(s)

Smart contracts, running on blockchains, enable transparent interactions without intermediaries. However, program-related bugs and flaws in translating business logic into code can introduce vulnerabilities, making them attractive targets for malicious users. For instance, using input from untrusted users in critical operations without proper validation may lead to exploitable functionalities. We refer to this vulnerability as Missing Input Validation (MIV). This paper focuses on the issues caused by MIV (aka MIV-related issues) in Solidity smart contracts executing on the Ethereum blockchain. In particular, we conduct a case study emphasizing how MIV-related issues can lead to unexpected behavior in smart contracts, rendering them vulnerable to malicious manipulation. We also implement an information flow analysis-based analyzer, MIV-Checker, to statically detect instances of MIV in Solidity smart contracts. We evaluated MIV-Checker against a state-of-the-art smart contract analysis tool, Securify, using 3399 distinct contracts collected from the Ethereum blockchain. Securify identified only three contracts, whereas MIV-Checker detected 86 contracts as potentially susceptible to MIV. Our manual assessment confirms that MIV-Checker outperforms Securify by detecting more true MIV cases and reducing execution time. This case study helps determine that many recently used contracts on Ethereum may still be potentially vulnerable to MIV. Additionally, we position user-provided input as a non-deterministic factor in Ethereum contract execution and discuss future research avenues for mitigating issues arising from such factors. © 2023 IEEE.

The Solidity smart contract language is deterministic by design. Nevertheless, some instances of nondeterminism (ND) in smart contracts stem from unpredictable inputs received during execution, such as inputs from asynchronous callbacks of Oracles or externally called contracts that halt unexpectedly. Such values must be validated to meet prespecified criteria before they reach critical program parts; otherwise, they can lead to nondeterministic state outcomes in smart contracts, which we refer to as ND-issues. To detect ND-issues, we propose an information flow-based analysis that tracks the unpredictable inputs and return values that are not validated before reaching critical program parts. We have implemented our proposal in FONOVA and evaluated it using 326 frequently used Ethereum smart contracts. The evaluation shows that FONOVA detects five times more exploitable instances of ND-issues with 12 times shorter analysis time than leading tools like Ethainter, Securify, and Mythril. © 2024 IEEE.