How Syzkaller Powers Kernel Fuzzing on Android: Architecture and Workflow

Architecture Overview

Syzkaller is an unsupervised, coverage‑guided kernel fuzzing framework developed by Google security engineers. Since its 2015 release it has uncovered more than 4,800 kernel bugs, is fully open‑source, and has been customized by many vendors and researchers to improve Linux kernel security and to fuzz other kernels.

Principle Overview

Syzkaller’s design relies on three main features: (1) test case generation is based on system calls using a C‑like template language, making inputs intuitive and controllable; (2) kernel error‑checking mechanisms such as sanitizers (e.g., KASAN, KCSAN, KMSAN) capture bugs during execution; (3) a coverage feedback channel (KCOV) guides fuzzing toward uncovered code paths, improving efficiency.

Implementation Analysis – Initialization and Main Loop

Syzkaller runs in two environments: a stable host (the syz‑manager ) that manages fuzzing processes and records results, and one or more VMs that serve as fuzz targets. The manager reads a configuration file, verifies the build, and enters the RunManager initialization.

The VM abstraction provides a uniform interface for different platforms. Each VM implements methods such as Copy(), Forward(), Run(), Info(), Diagnose(), Close(), and MonitorExecution(). VM creation involves loading configuration options, locating the adb executable, and connecting to the target device on Android.

During manager creation, a reporter is set up, user‑specified ignore and interest lists are applied, and paths for parsing vulnerability sources are configured. The manager then loads the database and seed corpus, starts Prometheus metrics, launches an HTTP server for result reporting, and records timestamps of critical binaries to detect modifications during fuzzing.

The RPC server, separate from the user‑facing HTTP server, collects feedback from the test environments every ten seconds and updates manager statistics.

Auxiliary functions include periodic corpus benchmarking and graceful handling of Ctrl‑C to stop fuzzing. Finally, the vmLoop constitutes the main fuzzing loop: VMs are grouped into FuzzingVMs and ReproVMs, tasks are allocated with priority to repro, crashes are added to a repro list, and the runRepro procedure attempts to reproduce and minimize each crash.

Conclusion

Syzkaller is currently the most popular kernel fuzzing tool; its innovative design, extensible interfaces, and Google’s engineering expertise make it a valuable reference for security researchers and developers seeking to improve kernel robustness.