{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T01:04:52Z","timestamp":1772240692848,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":41,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819751006","type":"print"},{"value":"9789819751013","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5101-3_23","type":"book-chapter","created":{"date-parts":[[2024,7,14]],"date-time":"2024-07-14T18:01:46Z","timestamp":1720980106000},"page":"424-443","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Detect Llama - Finding Vulnerabilities in\u00a0Smart Contracts Using Large Language Models"],"prefix":"10.1007","author":[{"given":"Peter","family":"Ince","sequence":"first","affiliation":[]},{"given":"Xiapu","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Jiangshan","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Joseph K.","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Xiaoning","family":"Du","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,15]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","unstructured":"Brown, T.B., et al.: Language models are few-shot learners, July 2020. https:\/\/doi.org\/10.48550\/arXiv.2005.14165, arXiv:2005.14165 [cs]","DOI":"10.48550\/arXiv.2005.14165"},{"key":"23_CR2","unstructured":"ChainSec: Comprehensive List of DeFi Hacks & Exploits (2023). https:\/\/chainsec.io\/defi-hacks\/"},{"key":"23_CR3","unstructured":"Consensys: Mythril: Security analysis tool for EVM bytecode (2023). https:\/\/github.com\/Consensys\/mythril"},{"key":"23_CR4","doi-asserted-by":"publisher","unstructured":"Dao, T.: FlashAttention-2: faster attention with better parallelism and work partitioning, July 2023. https:\/\/doi.org\/10.48550\/arXiv.2307.08691, arXiv:2307.08691 [cs]","DOI":"10.48550\/arXiv.2307.08691"},{"key":"23_CR5","doi-asserted-by":"publisher","unstructured":"David, I., Zhou, L., Qin, K., Song, D., Cavallaro, L., Gervais, A.: Do you still need a manual smart contract audit? June 2023. https:\/\/doi.org\/10.48550\/arXiv.2306.12338, arXiv:2306.12338 [cs]","DOI":"10.48550\/arXiv.2306.12338"},{"key":"23_CR6","unstructured":"DefiLlama: DefiLlama - Dashboard, November 2023. https:\/\/defillama.com\/"},{"key":"23_CR7","doi-asserted-by":"publisher","unstructured":"Dettmers, T., Pagnoni, A., Holtzman, A., Zettlemoyer, L.: QLoRA: efficient finetuning of quantized LLMs, May 2023. https:\/\/doi.org\/10.48550\/arXiv.2305.14314, arXiv:2305.14314 [cs]","DOI":"10.48550\/arXiv.2305.14314"},{"key":"23_CR8","unstructured":"Eleti, A., Harris, J., Kilpatrick, L.: Function calling and other API updates, July 2023). https:\/\/openai.com\/blog\/function-calling-and-other-api-updates"},{"key":"23_CR9","unstructured":"EtherScan.io: EtherScan.io - API - Contracts. https:\/\/docs.etherscan.io\/api-endpoints\/contracts"},{"key":"23_CR10","doi-asserted-by":"publisher","unstructured":"Feist, J., Grieco, G., Groce, A.: Slither: a static analysis framework for smart contracts. In: 2019 IEEE\/ACM 2nd International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB), pp. 8\u201315, May 2019. https:\/\/doi.org\/10.1109\/WETSEB.2019.00008, arXiv:1908.09878 [cs]","DOI":"10.1109\/WETSEB.2019.00008"},{"key":"23_CR11","doi-asserted-by":"publisher","unstructured":"Gai, Y., Zhou, L., Qin, K., Song, D., Gervais, A.: Blockchain large language models, April 2023. https:\/\/doi.org\/10.48550\/arXiv.2304.12749, arXiv:2304.12749 [cs]","DOI":"10.48550\/arXiv.2304.12749"},{"key":"23_CR12","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models, June 2021. https:\/\/arxiv.org\/abs\/2106.09685v2"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Hu, S., Huang, T., \u0130lhan, F., Tekin, S.F., Liu, L.: Large language model-powered smart contract vulnerability detection: new perspectives, October 2023. arXiv:2310.01152 [cs]","DOI":"10.1109\/TPS-ISA58951.2023.00044"},{"key":"23_CR14","unstructured":"Ince, P.: Detect Llama 34b Instruct Model, September 2023. https:\/\/huggingface.co\/peterxyz\/detect-llama-34b-Instruct"},{"key":"23_CR15","unstructured":"Ince, P.: Detect Llama 34b Model, November 2023. https:\/\/huggingface.co\/peterxyz\/detect-llama-34b"},{"key":"23_CR16","unstructured":"Ince, P.: Smart Contract Vulnerability Dataset, September 2023. https:\/\/huggingface.co\/datasets\/peterxyz\/smart-contract-vuln-detection"},{"key":"23_CR17","unstructured":"Ince, P.: peterdouglas\/detect-llama-evaluation, April 2024. https:\/\/github.com\/peterdouglas\/detect-llama-evaluation"},{"key":"23_CR18","unstructured":"Kocetkov, D., et al.: The Stack: 3 TB of permissively licensed source code. Preprint (2022)"},{"key":"23_CR19","first-page":"22199","volume":"35","author":"T Kojima","year":"2022","unstructured":"Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., Iwasawa, Y.: Large language models are zero-shot reasoners. Adv. Neural. Inf. Process. Syst. 35, 22199\u201322213 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"23_CR20","doi-asserted-by":"publisher","unstructured":"Li, R., et al.: StarCoder: may the source be with you! May 2023. https:\/\/doi.org\/10.48550\/arXiv.2305.06161, arXiv:2305.06161 [cs]","DOI":"10.48550\/arXiv.2305.06161"},{"key":"23_CR21","doi-asserted-by":"publisher","unstructured":"Liu, Z., et al.: Rethinking smart contract fuzzing: fuzzing with invocation ordering and important branch revisiting. IEEE Trans. Inf. Forensics Secur. 18, 1237\u20131251 (2023). https:\/\/doi.org\/10.1109\/TIFS.2023.3237370. https:\/\/ieeexplore.ieee.org\/document\/10018241. Conference Name: IEEE Transactions on Information Forensics and Security","DOI":"10.1109\/TIFS.2023.3237370"},{"key":"23_CR22","doi-asserted-by":"publisher","unstructured":"Luo, Z., et al.: WizardCoder: empowering code large language models with evol-instruct, June 2023. https:\/\/doi.org\/10.48550\/arXiv.2306.08568, arXiv:2306.08568 [cs]","DOI":"10.48550\/arXiv.2306.08568"},{"key":"23_CR23","unstructured":"Lutz, O., et al.: ESCORT: ethereum smart contracts vulnerability detection using deep neural network and transfer learning. arXiv:2103.12607 [cs], March 2021, arXiv: 2103.12607"},{"key":"23_CR24","doi-asserted-by":"publisher","unstructured":"Luu, L., Chu, D.H., Olickel, H., Saxena, P., Hobor, A.: Making smart contracts smarter. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, CCS 2016, pp. 254\u2013269. Association for Computing Machinery, New York, October 2016. https:\/\/doi.org\/10.1145\/2976749.2978309","DOI":"10.1145\/2976749.2978309"},{"key":"23_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1007\/978-3-540-78800-3_24","volume-title":"Tools and Algorithms for the Construction and Analysis of Systems","author":"L de Moura","year":"2008","unstructured":"de Moura, L., Bj\u00f8rner, N.: Z3: an efficient SMT solver. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 337\u2013340. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-78800-3_24"},{"key":"23_CR26","doi-asserted-by":"publisher","unstructured":"OpenAI: GPT-4 Technical Report, March 2023. https:\/\/doi.org\/10.48550\/arXiv.2303.08774, arXiv:2303.08774 [cs]","DOI":"10.48550\/arXiv.2303.08774"},{"key":"23_CR27","unstructured":"OpenAI: new models and developer products announced at DevDay, June 2023. https:\/\/openai.com\/blog\/new-models-and-developer-products-announced-at-devday"},{"key":"23_CR28","doi-asserted-by":"publisher","unstructured":"Ouyang, L., et al.: Training language models to follow instructions with human feedback, March 2022. https:\/\/doi.org\/10.48550\/arXiv.2203.02155, arXiv:2203.02155 [cs]","DOI":"10.48550\/arXiv.2203.02155"},{"key":"23_CR29","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"23_CR30","unstructured":"Peng, A., Wu, M., Allard, J., Heidel, S.: GPT-3.5 Turbo fine-tuning and API updates, August 2023. https:\/\/openai.com\/blog\/gpt-3-5-turbo-fine-tuning-and-api-updates"},{"key":"23_CR31","unstructured":"Rozi\u00e8re, B., et al.: Code Llama: Open Foundation Models for Code, August 2023. https:\/\/arxiv.org\/abs\/2308.12950v2"},{"key":"23_CR32","doi-asserted-by":"crossref","unstructured":"Shou, C., Tan, S., Sen, K.: ItyFuzz: snapshot-based fuzzer for smart contract. In: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023, pp. 322\u2013333. Association for Computing Machinery, New York, July 2023","DOI":"10.1145\/3597926.3598059"},{"key":"23_CR33","unstructured":"Siegel, D.: Understanding The DAO Attack, June 2016. https:\/\/www.coindesk.com\/learn\/understanding-the-dao-attack\/. Section: Learn"},{"key":"23_CR34","unstructured":"Solidity Team: Solidity 0.8.22 Release Announcement, October 2023. https:\/\/soliditylang.org\/blog\/2023\/10\/25\/solidity-0.8.22-release-announcement"},{"key":"23_CR35","unstructured":"Tann, W.J.W., Han, X.J., Gupta, S.S., Ong, Y.S.: Towards safer smart contracts: a sequence learning approach to detecting security threats. arXiv:1811.06632 [cs], June 2019"},{"key":"23_CR36","unstructured":"Taori, R., et al.: Alpaca: A Strong, Replicable Instruction-Following Model. https:\/\/crfm.stanford.edu\/2023\/03\/13\/alpaca.html"},{"key":"23_CR37","doi-asserted-by":"publisher","unstructured":"Tikhomirov, S., Voskresenskaya, E., Ivanitskiy, I., Takhaviev, R., Marchenko, E., Alexandrov, Y.: SmartCheck: static analysis of ethereum smart contracts. In: Proceedings of the 1st International Workshop on Emerging Trends in Software Engineering for Blockchain, WETSEB 2018, pp. 9\u201316. Association for Computing Machinery, New York, May 2018. https:\/\/doi.org\/10.1145\/3194113.3194115. https:\/\/dl.acm.org\/doi\/10.1145\/3194113.3194115","DOI":"10.1145\/3194113.3194115"},{"key":"23_CR38","doi-asserted-by":"crossref","unstructured":"Torres, C.F., Iannillo, A.K., Gervais, A., State, R.: ConFuzzius: a data dependency-aware hybrid fuzzer for smart contracts, March 2021. arXiv:2005.12156 [cs]","DOI":"10.1109\/EuroSP51992.2021.00018"},{"key":"23_CR39","doi-asserted-by":"publisher","unstructured":"Torres, C.F., Sch\u00fctte, J., State, R.: Osiris: hunting for integer bugs in ethereum smart contracts. In: Proceedings of the 34th Annual Computer Security Applications Conference, ACSAC 2018, pp. 664\u2013676. Association for Computing Machinery, New York, December 2018. https:\/\/doi.org\/10.1145\/3274694.3274737. https:\/\/dl.acm.org\/doi\/10.1145\/3274694.3274737","DOI":"10.1145\/3274694.3274737"},{"key":"23_CR40","unstructured":"Yashavant, C.S.: ScrawlD: A Dataset of Real World Ethereum Smart Contracts Labelled with Vulnerabilities, September 2023. https:\/\/github.com\/sujeetc\/ScrawlD. Original-date: 2022-03-04T16:42:58Z"},{"key":"23_CR41","doi-asserted-by":"publisher","unstructured":"Yashavant, C.S., Kumar, S., Karkare, A.: ScrawlD: a dataset of real world ethereum smart contracts labelled with vulnerabilities, February 2022. https:\/\/doi.org\/10.48550\/arXiv.2202.11409, arXiv:2202.11409 [cs]","DOI":"10.48550\/arXiv.2202.11409"}],"container-title":["Lecture Notes in Computer Science","Information Security and Privacy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5101-3_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,14]],"date-time":"2024-07-14T18:05:17Z","timestamp":1720980317000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5101-3_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819751006","9789819751013"],"references-count":41,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5101-3_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"15 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACISP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Conference on Information Security and Privacy","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"acisp2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.acisp24.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}