LOKI: State-Aware Fuzzing Framework for the Implementation of Blockchain Consensus Protocols

Abstract

—Blockchain consensus protocols are responsible for coordinating the nodes to make agreements on the transaction results. Their implementation bugs, including memory-related and consensus logic vulnerabilities, may pose serious threats. Fuzzing is a promising technique for protocol vulnerability detection. However, existing fuzzers cannot deal with complex consensus states of distributed nodes, thus generating a large number of useless packets, inhibiting their effectiveness in reaching the deep logic of consensus protocols. In this work, we propose LOKI, a blockchain consensus protocol fuzzing framework that detects consensus memory-related and logic bugs. LOKI fetches consensus states in real- time by masquerading as a node. First, LOKI dynamically builds a state model that records the state transition of each node. After that, LOKI adaptively generates the input targets, types, and contents according to the state model. With a bug analyzer, LOKI detects the consensus protocol implementation bugs with well-defined oracles. We implemented and evaluated LOKI on four widely used commercial blockchain systems, including Go-Ethereum, Meta Diem, IBM Fabric, and WeBank FISCO-BCOS. LOKI has detected 20 serious previously unknown vulnerabilities with 9 CVEs assigned. 14 of them are memory-related bugs, and 6 are consensus logic bugs. Compared with state-of-the-art tools such as Peach, Fluffy, and Twins, LOKI improves the branch coverage by an average of 43.21%, 182.05%, and 291.58%.