Replication Package for Ansible Sensitive Parameter Prediction Study|网络安全数据集|机器学习数据集

Replication package for the paper entitled "Smelling Secrets: Leveraging Machine Learning and Language Models for Sensitive Parameter Detection in Ansible Security Analysis", accepted for publication at the 25th IEEE International Conference on Source Code Analysis &amp; Manipulation (SCAM 2025).Contents<code>00_data_collection</code> — Scripts and results for data collection and ground truth construction.<code>RQ1_ml</code> — Scripts, results, and models for RQ1 (performance of machine learning classifiers)<code>RQ2_lm</code> — Scripts, results, and models for RQ2 (performance of language model classifiers)<code>RQ3_comparison</code> — Scripts and results for RQ3 (comparison of best models from RQ1 and RQ2 against baselines)<code>RQ4_unseen_params</code> — Scripts and results for RQ4 (prediction of unannotated parameters)LicenceData contained within this replication package is licenced under CC BY-NC 4.0.The source code contained within this package is dual-licenced. You are free to use it for <b>non-commercial</b> purposes under the conditions of the GPL 3.0 license.If you wish to use this product or any of its code commercially, contact us at: [e-mail]<br>