{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T11:13:37Z","timestamp":1776770017096,"version":"3.51.2"},"reference-count":50,"publisher":"Association for Computing Machinery (ACM)","issue":"FSE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Softw. Eng."],"published-print":{"date-parts":[[2025,6,19]]},"abstract":"<jats:p>Smart contracts, as Turing-complete programs managing billions of assets in decentralized finance, are prime targets for attackers.         While fuzz testing seems effective for detecting vulnerabilities in these programs, we identify several significant challenges when targeting smart contracts:        (i) the stateful nature of these contracts requires stateful exploration, but current fuzzers rely on transaction sequences to manipulate contract states, making the process inefficient;        (ii) contract execution is influenced by the continuously changing blockchain environment, yet current fuzzers are limited to local deployments, failing to test contracts in real-world scenarios.        These challenges hinder current fuzzers from uncovering hidden vulnerabilities, i.e., those concealed in deep contract states and specific blockchain environments.                In this paper, we present SmartShot, a mutable snapshot-based fuzzer to hunt hidden vulnerabilities within smart contracts.        We innovatively formulate contract states and blockchain environments as directly fuzzable elements and design mutable snapshots to quickly restore and mutate these elements.        SmartShot features a symbolic taint analysis-based mutation strategy along with double validation to soundly guide the state mutation.        SmartShot mutates blockchain environments using contract\u2019s historical on-chain states, providing real-world execution contexts.        We propose a snapshot checkpoint mechanism to integrate mutable snapshots into SmartShot\u2019s fuzzing loops.        These innovations enable SmartShot to effectively fuzz contract states, test contracts across varied and realistic blockchain environments, and support on-chain fuzzing.        Experimental results show that SmartShot is effective to detect hidden vulnerabilities with the highest code coverage and lowest false positive rate.        SmartShot is 4.8\u00d7 to 20.2\u00d7 faster than state-of-the-art tools, identifying 2,150 vulnerable contracts out of 42,738 real-world contracts which is 2.1\u00d7 to 13.7\u00d7 more than other tools.        SmartShot has demonstrated its real-world impact by detecting vulnerabilities that are only discoverable on-chain and uncovering 24 0-day vulnerabilities in the latest 10,000 deployed contracts.<\/jats:p>","DOI":"10.1145\/3715714","type":"journal-article","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T15:16:02Z","timestamp":1750346162000},"page":"65-85","source":"Crossref","is-referenced-by-count":2,"title":["SmartShot: Hunt Hidden Vulnerabilities in Smart Contracts using Mutable Snapshots"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0709-6420","authenticated-orcid":false,"given":"Ruichao","family":"Liang","sequence":"first","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7212-5297","authenticated-orcid":false,"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2129-0282","authenticated-orcid":false,"given":"Ruochen","family":"Cao","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3472-419X","authenticated-orcid":false,"given":"Kun","family":"He","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3634-3385","authenticated-orcid":false,"given":"Ruiying","family":"Du","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6865-0332","authenticated-orcid":false,"given":"Shuhua","family":"Li","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4463-5652","authenticated-orcid":false,"given":"Zheng","family":"Lin","sequence":"additional","affiliation":[{"name":"University of Hong Kong, HongKong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0930-0283","authenticated-orcid":false,"given":"Cong","family":"Wu","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,6,19]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Alchemy. 2024. alchemy. https:\/\/www.alchemy.com\/supernode"},{"key":"e_1_2_1_2_1","volume-title":"International Conference on Cloud Computing, Big Data and Blockchain (ICCBB). https:\/\/doi.org\/10","author":"Alharby Maher","year":"2018","unstructured":"Maher Alharby, Amjad Aldweesh, and Aad van Moorsel. 2018. 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In Conference on Computer and Communications Security (CCS). https:\/\/doi.org\/10.1145\/2976749.2978309 10.1145\/2976749.2978309"},{"key":"e_1_2_1_24_1","unstructured":"microsoft. 2024. Z3 SMT solver. https:\/\/www.microsoft.com\/en-us\/research\/project\/z3-3\/"},{"key":"e_1_2_1_25_1","volume-title":"SFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts. In International Conference on Software Engineering (ICSE). https:\/\/doi.org\/10","author":"Nguyen Tai D.","year":"2020","unstructured":"Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, and Quang Tran Minh. 2020. SFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts. In International Conference on Software Engineering (ICSE). https:\/\/doi.org\/10.1145\/3377811.3380334 10.1145\/3377811.3380334"},{"key":"e_1_2_1_26_1","volume-title":"VerX: Safety Verification of Smart Contracts. 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In USENIX Security Symposium (USENIX Security)."},{"key":"e_1_2_1_28_1","volume-title":"USENIX Security Symposium (USENIX Security).","author":"Schumilo Sergej","year":"2021","unstructured":"Sergej Schumilo, Cornelius Aschermann, Ali Abbasi, Simon W\u00f6r-ner, and Thorsten Holz. 2021. Nyx: Greybox Hypervisor Fuzzing using Fast Snapshots and Affine Types. In USENIX Security Symposium (USENIX Security)."},{"key":"e_1_2_1_29_1","volume-title":"USENIX Security Symposium (USENIX Security).","author":"Schumilo Sergej","year":"2017","unstructured":"Sergej Schumilo, Cornelius Aschermann, Robert Gawlik, Sebastian Schinzel, and Thorsten Holz. 2017. kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels. In USENIX Security Symposium (USENIX Security)."},{"key":"e_1_2_1_30_1","volume-title":"European Conference on Computer Systems (EuroSys). https:\/\/doi.org\/10","author":"Schumilo Sergej","year":"2022","unstructured":"Sergej Schumilo, Cornelius Aschermann, Andrea Jemmett, Ali Abbasi, and Thorsten Holz. 2022. Nyx-net: network fuzzing with incremental snapshots. In European Conference on Computer Systems (EuroSys). https:\/\/doi.org\/10.1145\/3492321.3519591 10.1145\/3492321.3519591"},{"key":"e_1_2_1_31_1","volume-title":"Large-Scale Study of Vulnerability Scanners for Ethereum Smart Contracts. In IEEE Symposium on Security and Privacy (SP). https:\/\/doi.org\/10","author":"Sendner C.","year":"2024","unstructured":"C. Sendner, L. Petzi, J. Stang, and A. Dmitrienko. 2024. Large-Scale Study of Vulnerability Scanners for Ethereum Smart Contracts. 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In USENIX Security Symposium (USENIX Security)."},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","unstructured":"Jianzhong Su Hong-Ning Dai Lingjun Zhao Zibin Zheng and Xiapu Luo. 2023. Effectively Generating Vulnerable Transaction Sequences in Smart Contracts with Reinforcement Learning-Guided Fuzzing. In International Conference on Automated Software Engineering (ASE). https:\/\/doi.org\/10.1145\/3551349.3560429 10.1145\/3551349.3560429","DOI":"10.1145\/3551349.3560429"},{"key":"e_1_2_1_38_1","unstructured":"SunWeb3Sec. 2022. DeFiHackLabs. https:\/\/github.com\/SunWeb3Sec\/DeFiHackLabs"},{"key":"e_1_2_1_39_1","volume-title":"TaintSE: Dynamic Taint Analysis Combined with Symbolic Execution and Constraint Association. In IEEE International Conference on Software Engineering and Service Science (ICSESS). https:\/\/doi.org\/10","author":"Tang Chenghua","year":"2023","unstructured":"Chenghua Tang, Xiaolong Guan, Mengmeng Yang, and Baohua Qiang. 2023. TaintSE: Dynamic Taint Analysis Combined with Symbolic Execution and Constraint Association. In IEEE International Conference on Software Engineering and Service Science (ICSESS). https:\/\/doi.org\/10.1109\/ICSESS58500.2023.10293040 10.1109\/ICSESS58500.2023.10293040"},{"key":"e_1_2_1_40_1","volume-title":"ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts. In European Symposium on Security and Privacy (EuroS&P). https:\/\/doi.org\/10","author":"Torres Christof Ferreira","year":"2021","unstructured":"Christof Ferreira Torres, Antonio Ken Iannillo, Arthur Gervais, and Radu State. 2021. ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts. In European Symposium on Security and Privacy (EuroS&P). https:\/\/doi.org\/10.1109\/EuroSP51992.2021.00018 10.1109\/EuroSP51992.2021.00018"},{"key":"e_1_2_1_41_1","volume-title":"Securify: Practical Security Analysis of Smart Contracts. In ACM SIGSAC Conference on Computer and Communications Security (CCS). https:\/\/doi.org\/10","author":"Tsankov Petar","unstructured":"Petar Tsankov, Andrei Marian Dan, Dana Drachsler-Cohen, Arthur Gervais, Florian B\u00fcnzli, and Martin T. Vechev. 2018. Securify: Practical Security Analysis of Smart Contracts. In ACM SIGSAC Conference on Computer and Communications Security (CCS). https:\/\/doi.org\/10.1145\/3243734.3243780 10.1145\/3243734.3243780"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","unstructured":"H. Wang Y. Liu Y. Li S. Lin C. Artho L. Ma and Y. Liu. 2022. Oracle-Supported Dynamic Exploit Generation for Smart Contracts. IEEE Transactions on Dependable and Secure Computing 19 (2022) https:\/\/doi.org\/10.1109\/TDSC.2020.3037332 10.1109\/TDSC.2020.3037332","DOI":"10.1109\/TDSC.2020.3037332"},{"key":"e_1_2_1_43_1","volume-title":"SMARTINV: Multimodal Learning for Smart Contract Invariant Inference. In IEEE Symposium on Security and Privacy (SP). https:\/\/doi.org\/10","author":"Wang S.","year":"2024","unstructured":"S. Wang, K. Pei, and J. Yang. 2024. SMARTINV: Multimodal Learning for Smart Contract Invariant Inference. In IEEE Symposium on Security and Privacy (SP). https:\/\/doi.org\/10.1109\/SP54263.2024.00126 10.1109\/SP54263.2024.00126"},{"key":"e_1_2_1_44_1","volume-title":"Targeted Greybox Fuzzing with Static Lookahead Analysis. In International Conference on Software Engineering (ICSE). https:\/\/doi.org\/10","author":"Wustholz Valentin","year":"2020","unstructured":"Valentin Wustholz and Maria Christakis. 2020. Targeted Greybox Fuzzing with Static Lookahead Analysis. In International Conference on Software Engineering (ICSE). https:\/\/doi.org\/10.1145\/3377811.3380388 10.1145\/3377811.3380388"},{"key":"e_1_2_1_45_1","volume-title":"Pulling Off The Mask: Forensic Analysis of the Deceptive Creator Wallets Behind Smart Contract Fraud. In IEEE Symposium on Security and Privacy (SP). https:\/\/doi.org\/10","author":"Yao M.","year":"2024","unstructured":"M. Yao, R. Zhang, H. Xu, S. Chou, V. Paturi, A. Sikder, and B. Saltaformaggio. 2024. Pulling Off The Mask: Forensic Analysis of the Deceptive Creator Wallets Behind Smart Contract Fraud. In IEEE Symposium on Security and Privacy (SP). https:\/\/doi.org\/10.1109\/SP54263.2024.00228 10.1109\/SP54263.2024.00228"},{"key":"e_1_2_1_46_1","volume-title":"Scrawld: A dataset of real world ethereum smart contracts labelled with vulnerabilities. arXiv preprint arXiv:2202.11409.","author":"Yashavant Chavhan Sujeet","year":"2022","unstructured":"Chavhan Sujeet Yashavant, Saurabh Kumar, and Amey Karkare. 2022. 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