From IOCs to Regex: Automating CTI Operationalization for SOC with LLMs

Computer Science > Cryptography and Security [Submitted on 14 Apr 2026] From IOCs to Regex: Automating CTI Operationalization for SOC with LLMs Pei-Yu Tseng (1), Lan Zhang (2), ZihDwo Yeh (1), Xiaoyan Sun (3), Xushu Dai (1), Peng Liu (1) ((1) The Pennsylvania State University, USA, (2) Northern Arizona University, USA, (3) Worcester Polytechnic Institute, USA) Cyber Threat Intelligence (CTI) reports contain Indicators of Compromise (IOCs) that are critical for security operations. To operationalize these IOCs across heterogeneous logs, analysts often convert them into regular expressions (regexes) for tasks such as digital forensics, log parsing, and SIEM rule creation. However, regex construction is still largely manual, requiring analysts to extract IOCs from CTI reports and transform them into syntactically valid and semantically precise patterns. This process is slow, error-prone, and increasingly impractical as CTI volumes grow. Although recent studies have applied Large Language Models (LLMs) to IOC extraction, they typically output plain strings rather than regexes, limiting practical deployment. Plain IOCs cannot effectively capture variations in system context, log format, or attacker behavior. To address this gap, we propose IOCRegex-gen, a fully automated LLM-based regex generation system that converts IOCs into regexes. The system introduces two key innovations: (i) a group-aware mechanism that identifies which IOC segments should be represented as capture or non-capture groups, and (ii) an iterative reasoning and multi-stage validation pipeline to ensure syntactic validity and semantic correctness. Experiments on over 3,000 real CTI reports and 2,400 ground-truth strings from the MITRE ATT&CK Evaluation framework show that IOCRegex-gen achieves an average hit rate of 99.1% and a false-positive rate of only 0.8%, demonstrating its effectiveness for large-scale CTI processing and automated regex generation. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2604.12228 [cs.CR]   (or arXiv:2604.12228v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.12228 Focus to learn more Submission history From: PeiYu Tseng [view email] [v1] Tue, 14 Apr 2026 03:08:46 UTC (606 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)