Phoenix: Detect and Locate Resilience Issues in Blockchain via Context-Sensitive Chaos

Resilience is vital to blockchain systems and helps them automatically adapt and continue providing their service when adverse situations occur, e.g., node crashing and data discarding. However, due to the vulnerabilities in their implementation, blockchain systems may fail to recover from the error situations, resulting in permanent service disruptions. Such vulnerabilities are called resilience issues. In this paper, we propose Phoenix, a system that helps detect and locate blockchain systems' resilience issues by context-sensitive chaos. First, we identify two typical types of resilience issues in blockchain systems: node unrecoverable and data unrecoverable. Then, we design three context-sensitive chaos strategies tailored to the blockchain feature. Additionally, we create a coordinator to effectively trigger resilience issues by scheduling these strategies. To better analyze them, we collect and sort all strategies into a pool and generate a reproducing sequence to locate and reproduce those issues. We evaluated Phoenix on 5 widely used commercial blockchain systems and detected 13 previous-unknown resilience issues. Besides, Phoenix successfully reproduces all of them, with 5.15 steps on average. The corresponding developers have fixed these issues. After that, the chaos resistance time of blockchains is improved by 143.9% on average. This indicates that Phoenix can significantly improve the resilience of these blockchains.