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syzkaller

syzkaller is an open-source kernel fuzzer developed by Google that automatically generates and executes test cases to find bugs in operating system kernels. It supports Linux, FreeBSD, Windows, OpenBSD, NetBSD, Fuchsia, and gVisor, and has discovered numerous real vulnerabilities across multiple platforms.

Source: GitHub — github.com/google/syzkaller
6.3k
GitHub stars
1.4k
Forks
Go
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositorygoogle/syzkaller
Ownergoogle
Primary languageGo
LicenseApache-2.0 — OSI-approved
Stars6.3k
Forks1.4k
Open issues605
Latest releaseUnknown
Last updated2026-07-08
Sourcehttps://github.com/google/syzkaller

What syzkaller is

syzkaller is a coverage-guided, unsupervised fuzzer written in Go that instruments kernel code to track execution paths and generate syscall sequences targeting uncovered areas. It uses feedback-driven test case generation to maximize code coverage and expose kernel bugs, with support for multiple OS targets through OS-specific harnesses.

Quickstart

Get the syzkaller source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/google/syzkaller.gitcd syzkaller# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Kernel Security Testing & Vulnerability Discovery

Ideal for continuous fuzzing of OS kernels to proactively discover memory corruption, use-after-free, and logic bugs before production deployment. Organizations maintaining or hardening kernel code benefit from automated, scalable bug detection.

Pre-Release Kernel Validation

Suitable for kernel development teams validating stability and security of new kernel releases or patches. Can run across multiple kernel versions and configurations to ensure broad compatibility and robustness.

Custom OS & Hypervisor Fuzzing

Applicable to teams developing custom kernels (Fuchsia, gVisor) or hypervisors where coverage-guided fuzzing can expose subtle synchronization and isolation bugs that manual testing misses.

Implementation considerations

  • Requires Go toolchain and kernel build environment (gcc, clang, kernel headers) for target OS; build and execution time can be substantial for full kernel fuzzing.
  • Effective use demands understanding of kernel syscall semantics and OS-specific setup (KASAN/MSAN instrumentation, VM or hardware environment). Refer to OS-specific docs (Linux, FreeBSD, Windows, etc.) for configuration details.
  • No official release versioning (latestRelease: n/a); track main branch or specific commits. Verify compatibility between syzkaller version and target kernel version before deployment.
  • Generated test cases and crash logs are verbose; requires automated triage and deduplication to manage large fuzzing campaigns. Integration with bug tracking or CI/CD pipelines is recommended.
  • Multi-target setup (Linux + FreeBSD + Windows) requires separate harness and VM/hardware infrastructure per OS; plan resource allocation and automation accordingly.

When to avoid it — and what to weigh

  • User-Space Application Testing Only — syzkaller is kernel-focused; if your primary need is fuzzing user-space applications or libraries, lighter-weight fuzzers (libFuzzer, AFL) may be more appropriate and easier to integrate.
  • No Kernel Source Code Access — syzkaller requires kernel source and instrumentation capabilities. If you cannot modify or instrument the target kernel, effectiveness is severely limited.
  • Real-Time Correctness Verification — syzkaller finds bugs through fuzzing but does not formally verify kernel properties or prove absence of bugs. For critical systems requiring formal verification, supplementary proof methods are necessary.
  • Minimal Infrastructure or Expertise — Setting up syzkaller for a new OS target or kernel version demands significant systems knowledge, custom harness development, and distributed infrastructure. Not suitable for teams lacking kernel development expertise.

License & commercial use

Apache License 2.0 (Apache-2.0), a permissive OSI-approved license permitting commercial use, modification, and distribution with appropriate attribution and liability disclaimer.

Apache-2.0 permits commercial use. However, this is not an official Google product (per README disclaimer). Ensure your organization's legal team reviews the license terms. No commercial support, SLA, or warranty from Google; community support via mailing list only.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationStrong
License clarityClear
Deployment complexityHigh
DEV.co fitGood
Assessment confidenceHigh
Security considerations

syzkaller is designed to find kernel bugs; it does not secure the kernel itself. Fuzzing campaigns generate many test cases and may trigger crashes; isolate fuzzing infrastructure from production. Discovered bugs must be responsibly disclosed per kernel vendor policy. The fuzzer's own security posture (Go runtime, dependency security) should be assessed separately.

Alternatives to consider

AFL (American Fuzzy Lop)

Widely-used, lighter-weight fuzzer for user-space binaries and libraries; simpler setup but less specialized for kernel fuzzing and multi-OS coverage guidance.

libFuzzer

In-process fuzzer for libraries and user-space code; excellent for targeted fuzzing but not designed for kernel-level syscall generation and OS-wide coverage tracking.

Custom kernel testing frameworks (Trinity, LTP)

Linux-specific, manual or semi-automated syscall testing; lower barrier to entry but lack coverage-guided feedback and require explicit test case authoring versus unsupervised generation.

Software development agency

Build on syzkaller with DEV.co software developers

syzkaller enables automated, coverage-guided kernel testing. Assess your infrastructure, kernel expertise, and OS target before starting. Review setup.md and join the mailing list for guidance. Consider Devco for help integrating fuzzing into your CI/CD and security workflows.

Talk to DEV.co

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syzkaller FAQ

Can I use syzkaller on Windows or macOS kernels?
Yes. syzkaller supports Windows, macOS (Darwin/XNU), FreeBSD, NetBSD, OpenBSD, Fuchsia, and gVisor. Each OS requires platform-specific setup and harnesses; see OS-specific docs (docs/windows/README.md, docs/darwin/README.md, etc.).
Does syzkaller require source code changes to my kernel?
Effective fuzzing requires kernel instrumentation (KASAN, MSAN, or coverage instrumentation). You do not need to patch the kernel, but you must build it with instrumentation flags enabled, which syzkaller docs detail per OS.
What infrastructure do I need to run syzkaller?
Minimum: Linux host, Go toolchain, kernel source, and a VM or hardware target. At scale: multiple VMs/machines for parallel fuzzing, centralized crash storage, and automated triage. Refer to setup.md and syzbot docs for recommended configurations.
Is there official support or SLA?
No. syzkaller is not an official Google product. Support is community-driven via the mailing list ([email protected]) and GitHub issues. No SLA, commercial support, or guarantee of response time.

Custom software development services

Adopting syzkaller is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source testing software in production.

Ready to Fuzz Your Kernel?

syzkaller enables automated, coverage-guided kernel testing. Assess your infrastructure, kernel expertise, and OS target before starting. Review setup.md and join the mailing list for guidance. Consider Devco for help integrating fuzzing into your CI/CD and security workflows.