mlsanityData to 7 Oct 2026

Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks

arXiv 1812.05934 ↗First posted 14 Dec 2018cs.CRcited by 17

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Abstract (arXiv)

Recently, a number of existing blockchain systems have witnessed major bugs and vulnerabilities within smart contracts. Although the literature features a number of proposals for securing smart contracts, these proposals mostly focus on proving the correctness or absence of a certain type of vulnerability within a contract, but cannot protect deployed (legacy) contracts from being exploited. In this paper, we address this problem in the context of re-entrancy exploits and propose a novel smart contract security technology, dubbed Sereum (Secure Ethereum), which protects existing, deployed contracts against re-entrancy attacks in a backwards compatible way based on run-time monitoring and validation. Sereum does neither require any modification nor any semantic knowledge of existing contracts. By means of implementation and evaluation using the Ethereum blockchain, we show that Sereum covers the actual execution flow of a smart contract to accurately detect and prevent attacks with a false positive rate as small as 0.06% and with negligible run-time overhead. As a by-product, we develop three advanced re-entrancy attacks to demonstrate the limitations of existing offline vulnerability analysis tools.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Dec 2018.

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Citing papers per year: 2021: 4; 2022: 0; 2023: 4; 2024: 2; 2025: 5; 2026: 2.

17 papers.

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  1. 2023GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysiscited by 65
  2. 2024Large Language Models for Cyber Security: A Systematic Literature Reviewcited by 65
  3. 2024PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generationcited by 36
  4. 2021Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detectioncited by 34
  5. 2021Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusioncited by 24
  6. 2023Blockchain Large Language Modelscited by 16
  7. 2025AI Agent Smart Contract Exploit Generationcited by 8
  8. 2021Eth2Vec: Learning Contract-Wide Code Representations for Vulnerability Detection on Ethereum Smart Contractscited by 7
  9. 2021ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learningcited by 4
  10. 2023Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challengescited by 3
  11. 2023Usenix'23 Extended Version: Smart Learning to Find Dumb Contractscited by 2
  12. 2025SymGPT: Auditing Smart Contracts via Combining Symbolic Execution with Large Language Modelscited by 2
5 more
  1. 2025Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learningcited by 2
  2. 2025CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in Blockchaincited by 2
  3. 2025Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniquescited by 0
  4. 2026Towards Compositional Generalization in LLMs for Smart Contract Security: A Case Study on Reentrancy Vulnerabilitiescited by 0
  5. 2026AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction poolingcited by 0