mlsanityData to 14 Oct 2026

sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts

arXiv 2004.08563 ↗First posted 18 Apr 2020cs.SEcited by 19

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Abstract (arXiv)

Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular programming languages for writing smart contracts on the Ethereum platform. Like traditional programs, smart contracts may contain vulnerabilities. Unlike traditional programs, smart contracts cannot be easily patched once they are deployed. It is thus important that smart contracts are tested thoroughly before deployment. In this work, we present an adaptive fuzzer for smart contracts on the Ethereum platform called sFuzz. Compared to existing Solidity fuzzers, sFuzz combines the strategy in the AFL fuzzer and an efficient lightweight multi-objective adaptive strategy targeting those hard-to-cover branches. sFuzz has been applied to more than 4 thousand smart contracts and the experimental results show that (1) sFuzz is efficient, e.g., two orders of magnitude faster than state-of-the-art tools; (2) sFuzz is effective in achieving high code coverage and discovering vulnerabilities; and (3) the different fuzzing strategies in sFuzz complement each other.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Apr 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 5; 2025: 7; 2026: 3.

19 papers.

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  1. 2024PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generationcited by 37
  2. 2023Blockchain Large Language Modelscited by 17
  3. 2023Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decodingcited by 14
  4. 2025Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detectioncited by 7
  5. 2025Logic Meets Magic: LLMs Cracking Smart Contract Vulnerabilitiescited by 5
  6. 2021ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learningcited by 4
  7. 2024Detecting Buggy Contracts via Smart Testingcited by 3
  8. 2024SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Frameworkcited by 3
  9. 2025AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generationcited by 3
  10. 2025SymGPT: Auditing Smart Contracts via Combining Symbolic Execution with Large Language Modelscited by 2
  11. 2025Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learningcited by 2
  12. 2022Deep Smart Contract Intent Detectioncited by 1
7 more
  1. 2026An Effective and Cost-Efficient Agentic Framework for Ethereum Smart Contract Auditingcited by 1
  2. 2026Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarizationcited by 1
  3. 2024Dual-view Aware Smart Contract Vulnerability Detection for Ethereumcited by 0
  4. 2024Knowledge Migration Framework for Smart Contract Vulnerability Detectioncited by 0
  5. 2025SEASONED: Semantic-Enhanced Self-Counterfactual Explainable Detection of Adversarial Exploiter Contractscited by 0
  6. 2025Multi-Agent Collaborative Fuzzing with Continuous Reflection for Smart Contracts Vulnerability Detectioncited by 0
  7. 2026Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Trainingcited by 0