mlsanityData to 7 Oct 2026

Securify: Practical Security Analysis of Smart Contracts

arXiv 1806.01143 ↗First posted 4 Jun 2018cs.CRcited by 61

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Abstract (arXiv)

Permissionless blockchains allow the execution of arbitrary programs (called smart contracts), enabling mutually untrusted entities to interact without relying on trusted third parties. Despite their potential, repeated security concerns have shaken the trust in handling billions of USD by smart contracts. To address this problem, we present Securify, a security analyzer for Ethereum smart contracts that is scalable, fully automated, and able to prove contract behaviors as safe/unsafe with respect to a given property. Securify's analysis consists of two steps. First, it symbolically analyzes the contract's dependency graph to extract precise semantic information from the code. Then, it checks compliance and violation patterns that capture sufficient conditions for proving if a property holds or not. To enable extensibility, all patterns are specified in a designated domain-specific language. Securify is publicly released, it has analyzed >18K contracts submitted by its users, and is regularly used to conduct security audits by experts. We present an extensive evaluation of Securify over real-world Ethereum smart contracts and demonstrate that it can effectively prove the correctness of smart contracts and discover critical violations.

Key facts. Cited by 61 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 7; 2023: 10; 2024: 10; 2025: 17; 2026: 10.

61 papers.

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  1. 2023GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysiscited by 65
  2. 2023Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectivescited by 48
  3. 2024Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justificationscited by 41
  4. 2024PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generationcited by 36
  5. 2021Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detectioncited by 34
  6. 2021Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusioncited by 24
  7. 2023Blockchain Large Language Modelscited by 16
  8. 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundariescited by 12
  9. 2024Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanationcited by 8
  10. 2025SCALM: Detecting Bad Practices in Smart Contracts Through LLMscited by 8
  11. 2025AI Agent Smart Contract Exploit Generationcited by 8
  12. 2021Eth2Vec: Learning Contract-Wide Code Representations for Vulnerability Detection on Ethereum Smart Contractscited by 7
38 more
  1. 2025Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detectioncited by 7
  2. 2021ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learningcited by 4
  3. 2022MANDO: Multi-Level Heterogeneous Graph Embeddings for Fine-Grained Detection of Smart Contract Vulnerabilitiescited by 4
  4. 2023VulnSense: Efficient Vulnerability Detection in Ethereum Smart Contracts by Multimodal Learning with Graph Neural Network and Language Modelcited by 4
  5. 2025Prompt to Pwn: Automated Exploit Generation for Smart Contractscited by 4
  6. 2024The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Surveycited by 3
  7. 2023Usenix'23 Extended Version: Smart Learning to Find Dumb Contractscited by 2
  8. 2023HyMo: Vulnerability Detection in Smart Contracts using a Novel Multi-Modal Hybrid Modelcited by 2
  9. 2024Vulnerability Detection in Ethereum Smart Contracts via Machine Learning: A Qualitative Analysiscited by 2
  10. 2024Detection Made Easy: Potentials of Large Language Models for Solidity Vulnerabilitiescited by 2
  11. 2025SymGPT: Auditing Smart Contracts via Combining Symbolic Execution with Large Language Modelscited by 2
  12. 2025Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learningcited by 2
  13. 2025MTVHunter: Smart Contracts Vulnerability Detection Based on Multi-Teacher Knowledge Translationcited by 2
  14. 2025SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detectioncited by 2
  15. 2022Deep Smart Contract Intent Detectioncited by 1
  16. 2023SourceP: Detecting Ponzi Schemes on Ethereum with Source Codecited by 1
  17. 2025AI-Based Vulnerability Analysis of NFT Smart Contractscited by 1
  18. 2025Web3 x AI Agents: Landscape, Integrations, and Foundational Challengescited by 1
  19. 2025Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy Optimizationcited by 1
  20. 2025ParaVul: A Parallel Large Language Model and Retrieval-Augmented Framework for Smart Contract Vulnerability Detectioncited by 1
  21. 2025Large Language Model based Smart Contract Auditing with LLMBugScannercited by 1
  22. 2025TxSum: User-Centered Ethereum Transaction Understanding with Micro-Level Semantic Groundingcited by 1
  23. 2026An Effective and Cost-Efficient Agentic Framework for Ethereum Smart Contract Auditingcited by 1
  24. 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
  25. 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
  26. 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
  27. 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
  28. 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
  29. 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
  30. 2022Using Graph Neural Networks for Program Terminationcited by 0
  31. 2022Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methodscited by 0
  32. 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGramcited by 0
  33. 2023Schooling to Exploit Foolish Contractscited by 0
  34. 2023Analysis of Information Propagation in Ethereum Network Using Combined Graph Attention Network and Reinforcement Learning to Optimize Network Efficiency and Scalabilitycited by 0
  35. 2024Dual-view Aware Smart Contract Vulnerability Detection for Ethereumcited by 0
  36. 2024A Survey on Blockchain-based Supply Chain Finance with Progress and Future directionscited by 0
  37. 2024JANUS: A Difference-Oriented Analyzer For Financial Centralization Risks in Smart Contractscited by 0
  38. 2024Knowledge Migration Framework for Smart Contract Vulnerability Detectioncited by 0

50 most cited of 61 All 61 (JSON)