Xupu Hu | Searcharxiv

arXiv2026

Inferring 1-Minimal Trigger Configurations for Assessing Linux Kernel CVE Triggerability

Vendors assessing Linux kernel CVEs need to know whether a bug is triggerable under production-tailored configurations, not merely whether a version is affected, yet upstream reproducers and vulnerability databases rarely provide configuration-level context. We study minimal trigger-configuration inference: given a CVE entry and a target kernel version (optionally a baseline .config), we synthesize a Kconfig-satisfiable option set that remains effective after make olddefconfig and, when a reproducer is available, still triggers under a specified evaluation protocol; we then prune it to a 1-minimal (subset-minimal) boundary for evaluation. Our framework FCC links vulnerability cues to build-system symbols, completes implicit prerequisites under olddefconfig feedback to avoid silent rollback, and performs runtime-validated minimization guided by dependency topology. We evaluate on KernJC and KernelCTF, totaling 88 CVEs across multiple kernel versions. On the 88-CVE set, FCC improves the post-make olddefconfig configuration success rate from 62.5% (55/88) to 96.6% (85/88) over an olddef-only injection baseline; on the KernJC set, FCC reduces the average candidate set size by 78.7% compared to KernJC (Avg. 14.72 vs. 69.00 options per CVE). A stage-wise analysis of time and token costs shows that Stage I dominates overhead, while CVE-focused evidence selection substantially reduces this cost. By returning an effective and auditable 1-minimal configuration boundary, FCC helps vendors scope triggerability against their deployment configurations with a clear, tool-supported decision line.

cs.CR↗

arXiv2025

Dynamic Vulnerability Patching for Heterogeneous Embedded Systems Using Stack Frame Reconstruction

Existing dynamic vulnerability patching techniques are not well-suited for embedded devices, especially mission-critical ones such as medical equipment, as they have limited computational power and memory but uninterrupted service requirements. Those devices often lack sufficient idle memory for dynamic patching, and the diverse architectures of embedded systems further complicate the creation of patch triggers that are compatible across various system kernels and hardware platforms. To address these challenges, we propose a hot patching framework called StackPatch that facilitates patch development based on stack frame reconstruction. StackPatch introduces different triggering strategies to update programs stored in memory units. We leverage the exception-handling mechanisms commonly available in embedded processors to enhance StackPatch's adaptability across different processor architectures for control flow redirection. We evaluated StackPatch on embedded devices featuring three major microcontroller (MCU) architectures: ARM, RISC-V, and Xtensa. In the experiments, we used StackPatch to successfully fix 102 publicly disclosed vulnerabilities in real-time operating systems (RTOS). We applied patching to medical devices, soft programmable logic controllers (PLCs), and network services, with StackPatch consistently completing each vulnerability remediation in less than 260 MCU clock cycles.

cs.CR↗