A Kernel fuzzer focusing on race bugs

Related tags

Deep Learningrazzer
Overview

Razzer: Finding kernel race bugs through fuzzing

Environment setup

$ source scripts/envsetup.sh

scripts/envsetup.sh sets up necessary environment variables. One should select the kernel version during environment setup, for example, v4.17.

Install

Initialize kernels_repo submodule

Kernel source codes used in this project are in the other reprository which is included as a submodule. To initialize the submodule one should execute git submodule update command as a follow.

$ git submodule update --init --depth=1 kernels_repo

Dependencies

$ sudo apt install zlib libglib-dev python-setuptools quilt libssl-dev dwarfdump

Install toolchains / tools

$ scripts/install.sh

scripts/install.sh then installs all the rest necessary toolchains and tools.

Static analysis

The Razzer's static analysis is based on the LLVM toolchain and the SVF static analysis tool. See documents in docs/static-analysis.md.

Fuzzing

Razzer's two-phases fuzzing is based on Syzkaller. The deterministic scheduler is implemented using QEMU/KVM. See documents in docs/fuzzing.md.

Paper

Razzer: Finding Kernel Race Bugs through Fuzzing (IEEE S&P 2019)

Trophies

Contributors

Owner
Systems and Software Security Lab at Seoul National University (SNU)
Systems and Software Security Lab at Seoul National University (SNU)
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