Uncovering Smart Contract VM Bugs Via Differential Fuzzing

Abstract

The ongoing public interest in blockchains and smart contracts has brought a rise to a magnitude of different blockchain implementations. The rate at which new concepts are envisioned and implemented makes it hard to vet their impact on security. Especially smart contract platforms, executing untrusted code, are very complex by design. Still, people put their trust and money into chains that may lack proper testing. A behavior deviation for edge cases of single op-codes is a critical bug class in this brave new world. It can be abused for Denial of Service against the blockchain, chain splits, double-spending, or direct attacks on applications operating on the blockchain. In this paper, we propose an automated methodology to uncover such differences. Through coverage-guided and state-guided fuzzing, we explore smart contract virtual machine behavior against multiple VMs in parallel. We develop NeoDiff, the first framework for feedback-guided differential fuzzing of smart contract VMs. We discuss real, monetary consequences our tool prevents. NeoDiff can be ported to new smart contract platforms with ease. Apart from fuzzing Ethereum VMs, NeoDiff found a range of critical differentials in VMs for the Neo blockchain. Moreover, through a higher-layer semantics mutator, we uncovered semantic discrepancies between Neo smart contracts written in Python when executed on the blockchain vs. classic CPython. Along the way, NeoDiff uncovered memory corruptions in the C# Neo VM.