Evaluating Coding Agents on Kernel Exploit Generation

2026-09-21

AI Summary

研究通过KEX-bench评估编码代理生成内核漏洞利用原语的能力，揭示了从发现漏洞到构造利用之间的差距。

Abstract

Coding agents now find real vulnerabilities in production software. However, bug discovery results do not measure whether agents can construct exploit primitives. We introduce KEX-bench, a benchmark for evaluating coding agents on exploit primitive generation against real operating-system kernels. KEX-bench contains 45 task instances across 40 Linux and Windows CVEs, covering kernel address leak, instruction-pointer control, heap read, heap write, and arbitrary address write. Each task runs in an isolated virtual machine, exposes controlled tools, and uses a deterministic verifier to check primitive-specific success. We evaluate state-of-the-art coding agents paired with frontier and open-weight models under fixed tool-call budgets. Without a reference proof of concept (PoC), the strongest configuration solves 1 of 20 Windows tasks (5.0%) and 14 of 25 Linux tasks (56.0%). With a reference PoC, the strongest configuration solves 31 of 45 tasks (68.9%). This highlights the gap where agents reach kernel crashes but fail to shape kernel state into exploit primitives. We release KEX-bench for reproducible research on AI-assisted exploitation at https://kex-bench.github.io.

Problem

• Coding Agents
• Exploit Generation
• Kernel Vulnerabilities
• Benchmark Evaluation

Innovation

• KEX-bench
• exploit primitive generation
• coding agents
• kernel vulnerabilities
• deterministic verifier