Abstract:

In the context of cloud-edge collaboration, ensuring the security of firmware for massive edge devices faces dual challenges: difficulties in state perception and low execution efficiency. As firmware is typically released in binary form, state perception methods relying on source code instrumentation are no longer applicable. Meanwhile, efficient full-system emulation of heterogeneous architectures such as ARM on x86 platforms represents a bottleneck in existing technologies, significantly limiting the throughput of fuzz testing. To address these issues, this paper proposed an efficient fuzz testing framework tailored for ARM architecture firmware. To overcome the performance bottleneck of cross-architecture emulation, this work the fork mechanism internally within QEMU, designing and implementing a lightweight, cross-architecture full-system virtual machine snapshot technology that did not rely on specific hardware (e.g., Intel VT-x), significantly enhancing testing efficiency. To achieve state perception without source code, this paper implemented multiple state identification methods based on network packet analysis, memory data clustering, and call stack analysis. Additionally, a unified proxy module supported transparent testing of complex targets such as network services. Experimental results demonstrate that the proposed framework achieves approximately a 19% improvement in testing efficiency, successfully reproduces known vulnerabilities such as CVE-2019-15232, and validates its capability to model program states under source-code-absent conditions, providing an effective solution for security testing in cloud-edge collaborative scenarios.

Key words: cloud-edge collaboration, firmware fuzz testing, ARM emulation, system-level snapshot, state awareness