arXiv AI By Yizhi Wang, Xinghua Gao, Reachsak Ly, Alireza Shojaei

SmartHomeSecure: Automated Detection and Repair of Smart Home Configuration Errors Using Large Language Models

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arXiv:2607. 06748v1 Announce Type: cross Abstract: Smart home automation platforms increasingly rely on user-authored YAML configuration files to define device behaviors, but these files are prone to syntax, formatting, and semantic logic errors that can cause automation failures and safety risks.

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arXiv AI
Oct 23

RegoMender: A Multi-agent Framework for Automated Rego Policy Repair

RegoMender is a multi‑agent framework that automates the repair of Rego policies, a key component of Policy‑as‑Code in cloud‑native systems. It uses a shared blackboard and atomic toolkit to dynamically apply patching, rewriting, or rollback actions, achieving high syntactic (82.9%) and semantic (77.9%) success rates on the newly introduced RegoBench benchmark of 1,159 real‑world defects. The system also generalizes to other languages such as HCL and SQL, repairing 86.4% of 132 real‑world CVE vulnerabilities, thereby demonstrating robustness and practical security value.

By Ruijie Zhang, Huaxiao Yin, Li Hu, Fanqi Kong, Haozhe Liang, Shaoyin Cheng, Kun Zhang, Bibo Tu