mlsanityData to 7 Oct 2026

Finding The Greedy, Prodigal, and Suicidal Contracts at Scale

arXiv 1802.06038 ↗First posted 16 Feb 2018cs.CRcited by 19

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Abstract (arXiv)

Smart contracts---stateful executable objects hosted on blockchains like Ethereum---carry billions of dollars worth of coins and cannot be updated once deployed. We present a new systematic characterization of a class of trace vulnerabilities, which result from analyzing multiple invocations of a contract over its lifetime. We focus attention on three example properties of such trace vulnerabilities: finding contracts that either lock funds indefinitely, leak them carelessly to arbitrary users, or can be killed by anyone. We implemented MAIAN, the first tool for precisely specifying and reasoning about trace properties, which employs inter-procedural symbolic analysis and concrete validator for exhibiting real exploits. Our analysis of nearly one million contracts flags 34,200 (2,365 distinct) contracts vulnerable, in 10 seconds per contract. On a subset of3,759 contracts which we sampled for concrete validation and manual analysis, we reproduce real exploits at a true positive rate of 89%, yielding exploits for3,686 contracts. Our tool finds exploits for the infamous Parity bug that indirectly locked 200 million dollars worth in Ether, which previous analyses failed to capture.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 1; 2023: 4; 2024: 4; 2025: 6; 2026: 1.

19 papers.

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  1. 2021Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detectioncited by 34
  2. 2023Blockchain Large Language Modelscited by 16
  3. 2025AI Agent Smart Contract Exploit Generationcited by 8
  4. 2021Eth2Vec: Learning Contract-Wide Code Representations for Vulnerability Detection on Ethereum Smart Contractscited by 7
  5. 2025PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contractscited by 7
  6. 2025Logic Meets Magic: LLMs Cracking Smart Contract Vulnerabilitiescited by 5
  7. 2021ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learningcited by 4
  8. 2025Prompt to Pwn: Automated Exploit Generation for Smart Contractscited by 4
  9. 2024The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Surveycited by 3
  10. 2023Usenix'23 Extended Version: Smart Learning to Find Dumb Contractscited by 2
  11. 2022Deep Smart Contract Intent Detectioncited by 1
  12. 2023SourceP: Detecting Ponzi Schemes on Ethereum with Source Codecited by 1
7 more
  1. 2025Web3 x AI Agents: Landscape, Integrations, and Foundational Challengescited by 1
  2. 2025Large Language Model based Smart Contract Auditing with LLMBugScannercited by 1
  3. 2023Schooling to Exploit Foolish Contractscited by 0
  4. 2024Vulnerability Detection in Smart Contracts: A Comprehensive Surveycited by 0
  5. 2024A Survey on Blockchain-based Supply Chain Finance with Progress and Future directionscited by 0
  6. 2024JANUS: A Difference-Oriented Analyzer For Financial Centralization Risks in Smart Contractscited by 0
  7. 2026AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction poolingcited by 0