Detecting Unknown Vulnerabilities in Smart Contracts with the CNN-BiLSTM Model

Detecting Unknown Vulnerabilities in Smart Contracts with the CNN-BiLSTM Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Detecting Unknown Vulnerabilities in Smart Contracts with the CNN-BiLSTM Model Wanyi Gu, Guojun Wang, Peiqiang Li, Guangxin Zhai, Xubin Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4589708/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2024 Read the published version in International Journal of Information Security → Version 1 posted 10 You are reading this latest preprint version Abstract Smart contracts, fundamental to blockchain technology, are extensively utilized in diverse fields such as finance, supply chain management, and beyond. Nevertheless, their capability to handle significant transactions and their unchangeable nature, once deployed, bring about substantial risks, potentially leading to severe security breaches and financial losses. Unfortunately, existing research primarily focuses on known vulnerabilities, leaving the realm of unknown vulnerabilities largely unexplored. This article aims to address this gap by introducing an innovative approach that capitalizes on the similarities between known and unknown vulnerabilities. We propose a groundbreaking CNN-BiLSTM model meticulously designed to identify features of known vulnerabilities and employ them to detect unknown vulnerabilities. Our innovative methodology intricately gathers opcode sequences generated during smart contract execution using Geth instrumentation and meticulously analyzes them. Rigorous experiments validate the effectiveness of the model in detecting unknown vulnerabilities. This innovative approach represents a significant advancement in blockchain security by providing proactive measures to strengthen smart contract security against potential threats. Blockchain Smart Contracts Unknown Vulnerabilities Opcode Sequences CNN-BiLSTM Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2024 Read the published version in International Journal of Information Security → Version 1 posted Editorial decision: Revision requested 28 Sep, 2024 Reviewers agreed at journal 25 Sep, 2024 Reviews received at journal 23 Sep, 2024 Reviews received at journal 10 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers invited by journal 05 Jul, 2024 Editor assigned by journal 20 Jun, 2024 Submission checks completed at journal 20 Jun, 2024 First submitted to journal 16 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4589708","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323719859,"identity":"6152afef-a697-45ea-865a-23b8e44046a9","order_by":0,"name":"Wanyi Gu","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wanyi","middleName":"","lastName":"Gu","suffix":""},{"id":323719860,"identity":"4ab32270-abfe-4ec7-bef6-a0f07ff72559","order_by":1,"name":"Guojun Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIie3RuwrCMBSA4SOFuASyRqTvUAnURdpXaSnYRUFwcXAoCI51VXB3LQjOkYAugo4dHApCJmc3LynusW6C+YckQz7IBcBk+tGcciAAqJxrSWXSSL4hb8erEjLbn4Z4fPbWx5W8YOjYGbdkoSM07w0Y3slokxcxw9BlGUdtR3seigPWQyJyc75rYhBhxjGiWkIOijxExObbqSLPCgRizvpT4TlkghThn4m6C7B7KgKaI9RYOhFbCORqiXox2ZrfhF8u6HXk2el+IrUEALvl+4QJDeD9q5Z+v6p+KdToA+Eft5pMJtOf9gLqe0rL9GhBxwAAAABJRU5ErkJggg==","orcid":"","institution":"Guangzhou University","correspondingAuthor":true,"prefix":"","firstName":"Guojun","middleName":"","lastName":"Wang","suffix":""},{"id":323719861,"identity":"eb73a0f1-7383-402f-b44c-3a1e1202f1c3","order_by":2,"name":"Peiqiang Li","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Peiqiang","middleName":"","lastName":"Li","suffix":""},{"id":323719862,"identity":"dddf722a-d657-45a1-8ebb-e145ecdb82cd","order_by":3,"name":"Guangxin Zhai","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Guangxin","middleName":"","lastName":"Zhai","suffix":""},{"id":323719863,"identity":"d29ce7ac-5b25-4854-8252-24a130fa8653","order_by":4,"name":"Xubin Li","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xubin","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-06-16 12:36:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4589708/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4589708/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10207-024-00945-6","type":"published","date":"2024-11-28T15:57:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70388691,"identity":"45496716-5a97-4ddb-9839-dc5fd7d23dc5","added_by":"auto","created_at":"2024-12-02 17:26:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1074241,"visible":true,"origin":"","legend":"","description":"","filename":"DetectingUnknownVulnerabilitiesinSmartContractswith.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4589708/v1_covered_f792d925-4dbd-48a9-ae0c-e7f55ba0cf9b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Detecting Unknown Vulnerabilities in Smart Contracts with the CNN-BiLSTM Model\n","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-information-security","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijis","sideBox":"Learn more about [International Journal of Information Security](http://link.springer.com/journal/10207)","snPcode":"10207","submissionUrl":"https://submission.nature.com/new-submission/10207/3","title":"International Journal of Information Security","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Blockchain , Smart Contracts , Unknown Vulnerabilities , Opcode Sequences , CNN-BiLSTM","lastPublishedDoi":"10.21203/rs.3.rs-4589708/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4589708/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Smart contracts, fundamental to blockchain technology, are extensively utilized in diverse fields such as finance, supply chain management, and beyond. 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