PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
Smart contracts operate in a highly adversarial environment, where vulnerabilities can lead to substantial financial losses. Thus, smart contracts are subject to security audits. In auditing, proof-of-concept (PoC) exploits play a critical role by demonstrating to the stakeholders that the reported vulnerabilities are genuine, reproducible, and actionable. However, manually creating PoCs is time-consuming, error-prone, and often constrained by tight audit schedules. We introduce PoCo, an agentic framework that automatically generates executable PoC exploits from natural-language vulnerability descriptions written by auditors. PoCo autonomously generates PoC exploits in an agentic manner by interacting with a set of codeexecution tools in a Reason-Act-Observe loop. It produces fully executable exploits compatible with the Foundry testing framework, ready for integration into audit reports and other security tools. We evaluate PoCo on a dataset of 23 real-world vulnerability reports. PoCo consistently outperforms the Zero-shot and Workflow baselines, generating well-formed and logically correct PoCs. Our results demonstrate that agentic frameworks can significantly reduce the effort required for high-quality PoCs in smart contract audits. Our contribution provides actionable knowledge for the smart contract security community.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 29 of its 72 references that are in the map. First posted on arXiv 4 Nov 2025.
Builds on
29 of 72 references.
Closest ancestors · 2
Same direction, newest first
- 2025AI Agent Smart Contract Exploit Generation8 Jul
- 2025Dynamic Risk Assessments for Offensive Cybersecurity Agents23 May
Other references · 27
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- 2021Evaluating Large Language Models Trained on Codecited by 8,053
- 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,258
- 2024Agentless: Demystifying LLM-based Software Engineering Agentscited by 400
- 2024Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Modelscited by 156
- 2024AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attackscited by 94
- 2024NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Securitycited by 90
- 2023Getting pwn'd by AI: Penetration Testing with Large Language Modelscited by 82
- 2024PenHeal: A Two-Stage LLM Framework for Automated Pentesting and Optimal Remediationcited by 30
- 2018Finding The Greedy, Prodigal, and Suicidal Contracts at Scalecited by 19
15 more
- 2025Agentic AI Software Engineers: Programming with Trustcited by 19
- 2025Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networkscited by 12
- 2023DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projectscited by 9
- 2025AIRTBench: Measuring Autonomous AI Red Teaming Capabilities in Language Modelscited by 7
- 2022FlashSyn: Flash Loan Attack Synthesis via Counter Example Driven Approximationcited by 5
- 2019Oracle-Supported Dynamic Exploit Generation for Smart Contractscited by 4
- 2024SC-Bench: A Large-Scale Dataset for Smart Contract Auditingcited by 4
- 2025Prompt to Pwn: Automated Exploit Generation for Smart Contractscited by 4
- 2023EF/CF: High Performance Smart Contract Fuzzing for Exploit Generationcited by 3
- 2024FORAY: Towards Effective Attack Synthesis against Deep Logical Vulnerabilities in DeFi Protocolscited by 3
- 2025Smart Contract Fuzzing Towards Profitable Vulnerabilitiescited by 3
- 2019Precise Attack Synthesis for Smart Contractscited by 2
- 2024Evaluation of ChatGPT's Smart Contract Auditing Capabilities Based on Chain of Thoughtcited by 2
- 2025Do Automated Fixes Truly Mitigate Smart Contract Exploits?cited by 2
- 2024Automated Attack Synthesis for Constant Product Market Makerscited by 1
Built on by
Citing papers per year: 2025: 1; 2026: 6.
7 papers.
- 2025PBFuzz: Agentic Directed Fuzzing for PoV Generationcited by 4
- 2026TxRay: Agentic Postmortem of Live Blockchain Attackscited by 2
- 2026A Dual-Loop Agent Framework for Automated Vulnerability Reproductioncited by 1
- 2026PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policycited by 1
- 2026LLMs + Security = Troublecited by 0
- 2026Repository-Level Solidity Code Generation with Large Language Models: From Prompting to Fine-Tuningcited by 0
- 2026WitnessGym: Benchmarking Coding Agents on the Construction of Bug Witnessescited by 0
- 2026WitnessGym: Benchmarking Coding Agents on the Construction of Bug Witnesses29 Sep 2026
- 2026Repository-Level Solidity Code Generation with Large Language Models: From Prompting to Fine-Tuning18 Jun 2026
- 2026PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy8 Apr 2026
- 2026LLMs + Security = Trouble9 Feb 2026
- 2026A Dual-Loop Agent Framework for Automated Vulnerability Reproduction5 Feb 2026
- 2026TxRay: Agentic Postmortem of Live Blockchain Attacks1 Feb 2026
- 2025PBFuzz: Agentic Directed Fuzzing for PoV Generation4 Dec 2025
Similar, not cited
Close in wording, no citation either way
- 2026Beyond Detection: Agentic Attack Synthesis and Simulation for Smart Contracts
- 2026EvoPoC: Automated Exploit Synthesis for DeFi Smart Contracts via Hierarchical Knowledge Graphs ↗
- 2025LISA Technical Report: An Agentic Framework for Smart Contract Auditing
- 2026An Effective and Cost-Efficient Agentic Framework for Ethereum Smart Contract Auditing
- 2026Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarization
- 2026Program Analysis Guided LLM Agent for Proof-of-Concept Generation
- 2026Transferable Self-Evolving Playbooks for Agentic Security Auditing
- 2026Demystifying Agent Skills for Smart Contract Auditing: Design, Effectiveness, Behavioral Impact