Shaohua Li

Ziqiao Kong, Wanxu Xia, Chong Wang et al.

Smart contracts govern billions of dollars in decentralized finance (DeFi), yet automated vulnerability detection remains challenging because many vulnerabilities are tightly coupled with project-specific business logic. We observe that recurring vulnerabilities across diverse DeFi business models often share the same underlying economic mechanisms, which we term DeFi semantics, and that capturing these shared abstractions can enable more systematic auditing. Building on this insight, we propose Knowdit, a knowledge-driven, agentic framework for smart contract vulnerability detection. Knowdit first constructs an auditing knowledge graph from historical human audit reports, linking fine-grained DeFi semantics with recurring vulnerability patterns. Given a new project, a multi-agent framework leverages this knowledge through an iterative loop of specification generation, harness synthesis, fuzz execution, and finding reflection, driven by a shared working memory for continuous refinement. We evaluate Knowdit on 12 recent Code4rena projects with 75 ground-truth vulnerabilities. Knowdit detects all 14 high-severity and 77\% of medium-severity vulnerabilities with only 2 false positives, significantly outperforming all baselines. Applied to six real-world projects, Knowdit further discovers 12 high- and 10 medium-severity previously unknown vulnerabilities, proving its outstanding performance.

Ziqiao Kong, Wanxu Xia, Zhengwei Li et al.

Move is a resource-oriented programming language designed for secure and verifiable smart contract development and has been widely used in managing billions of digital assets in blockchains, such as Sui and Aptos.Move features a strong static type system and explicit resource semantics to enforce safety properties such as the prevention of data races, invalid asset transfers, and entry vulnerabilities. However, smart contracts written in Move may still contain certain vulnerabilities that are beyond the reach of its type system. It is thus essential to validate Move smart contracts. Unfortunately, due to its strong type system, existing smart contract fuzzers are ineffective in producing syntactically or semantically valid transactions to test Move smart contracts. This paper introduces the first fuzzing framework, Belobog, for Move smart contracts. Belobog is type-aware and ensures that all generated and mutated transactions are well-typed. More specifically, for a target Move smart contract, Belobog first constructs a dependency graph based on Move's type system, and then generates or mutates a transaction based on the graph trace derived from the dependency graph. In order to overcome the complex checks in Move smart contracts, we further design and implement a concolic executor in Belobog. We evaluated Belobog on 109 real-world Move smart contract projects. The experimental results show that Belobog is able to detect 100% critical and 79% major vulnerabilities manually audited by human experts. We further selected two recent notorious incidents in the Move ecosystem, i.e., Cetus and Nemo. Belobog successfully reproduced full exploits for both of them, without any prior knowledge. Moreover, we applied Belobog on three ongoing auditing projects and found 2 critical, 2 major, and 3 medium new vulnerabilities, all acknowledged by the project developers.