Enhancing Blockchain Robustness Through Efficient Feedback-Driven Chaos Engineering

The rapid evolution of blockchain technology has attracted global users to operate nodes and participate in consensus processes. However, heterogeneous networks and hardware conditions may induce chaotic behavior in nodes, leading to critical faults such as packet loss or data corruption. These faults compromise system robustness, causing node crashes or desynchronization. Existing chaos engineering methods for blockchain systems suffer from inefficient fault injection and lack feedback mechanisms to iteratively guide fault selection. To address these limitations, we propose ChaosChain, a framework for efficient and effective chaos engineering in blockchain systems to expose robustness vulnerabilities. For efficiency, we design a parallel fault coordination mechanism that injects multiple fault types into arbitrary nodes simultaneously while enforcing blockchain consensus security constraints.We construct a global timeline of all executed faults and validate security constraints before each injection. To improve effectiveness, we introduce next fault guidance, a feedback-driven approach that selects optimal faults to trigger complex node state transitions.We model each node’s state as an interference-resistant state machine that captures state transitions during faults without cross-node interference. We evaluate ChaosChain across four implementations in Filecoin and Ethereum, uncovering six new robustness issues. Compared to state-of-the-art tools, our framework injects 4× more faults concurrently.