mlsanityData to 7 Oct 2026

Beyond Detection: Agentic Attack Synthesis and Simulation for Smart Contracts

arXiv 2607.15673 ↗First posted 17 Jul 2026cs.CRcited by 0

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Smart contract vulnerabilities pose severe financial risks, yet existing security tools largely stop at vulnerability detection, offering limited support for explaining whether reported flaws are exploitable, how attacks unfold, and what concrete damage they cause. To bridge this gap, we propose KASS (Knowledge-Augmented Attack Synthesis and Simulation), a multi-agent framework for executable smart contract exploit verification. KASS decomposes automated exploit generation into planning, generation, and testing stages, and integrates three complementary mechanisms: retrieval-augmented planning over real-world audit knowledge, formal generation and validation constraints that bind attack plans to executable proof-of-concept tests, and a hierarchical dual-loop refinement process that repairs code-level errors while triggering strategy-level replanning when attack assumptions fail. We evaluate KASS on 104 SmartBugs-Curated contracts across four vulnerability categories. Experimental results show that KASS successfully generates executable exploits for 94.23% of tested contracts; this rate is higher than previously reported results for REX and AdvSCanner on comparable SmartBugs-Curated subsets, and higher than our reproduced Claude Code baseline under the same evaluation protocol. On 11 real-world CVE-tagged contracts, KASS successfully validates 9 cases. Beyond exploit generation, KASS produces structured attack plans that document exploitation flows, quantify potential asset losses, and serve as semantic false positive filters for static analysis tools.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 28 of its 66 references that are in the map. First posted on arXiv 17 Jul 2026.

Builds on

28 of 66 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications24 Mar

Other references · 27

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  4. 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 915
  5. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challengescited by 278
  6. 2023Self-collaboration Code Generation via ChatGPTcited by 255
  7. 2024MapCoder: Multi-Agent Code Generation for Competitive Problem Solvingcited by 177
  8. 2023Structured Chain-of-Thought Prompting for Code Generationcited by 136
  9. 2023Self-planning Code Generation with Large Language Modelscited by 121
  10. 2019Slither: A Static Analysis Framework For Smart Contractscited by 88
  11. 2023GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysiscited by 65
  12. 2018Securify: Practical Security Analysis of Smart Contractscited by 61
15 more
  1. 2019Manticore: A User-Friendly Symbolic Execution Framework for Binaries and Smart Contractscited by 36
  2. 2024PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generationcited by 36
  3. 2019Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contractscited by 35
  4. 2018ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detectioncited by 32
  5. 2022SoK: Decentralized Finance (DeFi) Attackscited by 28
  6. 2019A Survey on Ethereum Systems Security: Vulnerabilities, Attacks and Defensescited by 25
  7. 2019Harvey: A Greybox Fuzzer for Smart Contractscited by 10
  8. 2021SAILFISH: Vetting Smart Contract State-Inconsistency Bugs in Secondscited by 10
  9. 2023Smart Contract and DeFi Security Tools: Do They Meet the Needs of Practitioners?cited by 8
  10. 2019Oracle-Supported Dynamic Exploit Generation for Smart Contractscited by 4
  11. 2025Prompt to Pwn: Automated Exploit Generation for Smart Contractscited by 4
  12. 2023Turn the Rudder: A Beacon of Reentrancy Detection for Smart Contracts on Ethereumcited by 3
  13. 2023ItyFuzz: Snapshot-Based Fuzzer for Smart Contractcited by 3
  14. 2025A Systematic Literature Review on Automated Exploit and Security Test Generationcited by 3
  15. 2020Steroids for DOPed Applications: A Compiler for Automated Data-Oriented Programmingcited by 1

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