{"ID":6237256,"CreatedAt":"2026-07-09T18:23:37.943547127Z","UpdatedAt":"2026-07-09T20:50:17.003448696Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.02748","arxiv_id":"2607.02748","title":"Characterizing and Bridging the Diagnostic Gap in eBPF Verifier Rejections","abstract":"eBPF lets developers run custom programs inside the Linux kernel, where a verifier proves each program safe. However, when the verifier rejects a program, the unclear error makes repair challenging: the error reports where verification stopped, not where the program lost the proof the verifier required. To quantify this gap, we conduct an empirical study of 235 reproduced rejections, showing that 47% of rejections return only EINVAL, one error string maps to as many as nine distinct root causes, and 10 of the 12 root causes are eBPF-specific. Repair thus requires both domain knowledge and locating where the proof was lost, yet existing tools only help developers read the error. We present bpfix, which reconstructs where the required proof was established and where it was lost from the verifier log, and prints a Rust-like diagnostic. To evaluate bpfix and the ability of LLMs to help repair, we construct a benchmark of 75 LLM repair tasks. Current models achieve 0-37% one-shot success with the raw log, and replacing the log with the bpfix localization improves repair by 11-21pp, suggesting that locating where the proof was lost is key to guiding repair. bpfix is available at https://github.com/eunomia-bpf/bpfix","short_abstract":"eBPF lets developers run custom programs inside the Linux kernel, where a verifier proves each program safe. However, when the verifier rejects a program, the unclear error makes repair challenging: the error reports where verification stopped, not where the program lost the proof the verifier required. To quantify thi...","url_abs":"https://arxiv.org/abs/2607.02748","url_pdf":"https://arxiv.org/pdf/2607.02748v1","authors":"[\"Yusheng Zheng\",\"Zhengjie Ji\",\"Weichen Tao\",\"Xiangyu Gao\",\"Jianchang Su\",\"Wei Zhang\",\"Andi Quinn\",\"Dan Williams\"]","published":"2026-07-02T20:33:32Z","proceeding":"cs.OS","tasks":"[\"cs.OS\",\"cs.PL\",\"cs.SE\"]","methods":"[\"Large Language Model\"]","has_code":false}