Code for the USENIX 2017 paper: kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels

Overview

kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels

Blazing fast x86-64 VM kernel fuzzing framework with performant VM reloads for Linux, MacOS and Windows.

Published at USENIX Security 2017.

Currently missing:

  • full documentation
  • agents for macOS and Windows (except for our test driver)

BibTex:

@inproceedings{schumilo2017kafl,
    author = {Schumilo, Sergej and Aschermann, Cornelius and Gawlik, Robert and Schinzel, Sebastian and Holz, Thorsten},
    title = {{kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels}},
    year = {2017},
    booktitle = {USENIX Security Symposium} 
}

Trophies

Setup

This is a short introduction on how to setup kAFL to fuzz Linux kernel components.

Download kAFL and install necessary components

$ git clone https://github.com/RUB-SysSec/kAFL.git
$ cd kAFL
$ chmod u+x install.sh
$ sudo ./install.sh
$ sudo reboot

Setup VM

  • Create QEMU hard drive image:
$ qemu-img create -f qcow2 linux.qcow2 20G
  • Retrieve an ISO file of the desired OS and install it inside a VM (in this case Ubuntu 16.04 server):
$ wget -O /path/to/where/to/store/ubuntu.iso http://de.releases.ubuntu.com/16.04/ubuntu-16.04.3-server-amd64.iso
$ qemu-system-x86_64 -cpu host -enable-kvm -m 512 -hda linux.qcow2 -cdrom ubuntu.iso -usbdevice tablet
  • Download kAFL and compile the loader agent:
git clone https://github.com/RUB-SysSec/kAFL.git
cd path/to/kAFL/kAFL-Fuzzer/agents
chmod u+x compile.sh
./compile.sh
  • Shutdown the VM

Prepare VM for kAFL fuzzing

  • On the host: Create Overlay and Snapshot Files:
mkdir snapshot && cd snapshot
qemu-img create -b /absolute/path/to/hdd/linux.qcow2 -f qcow2 overlay_0.qcow2
qemu-img create -f qcow2 ram.qcow2 512
  • Start the VM using QEMU-PT:
cd /path/to/kAFL
./qemu-2.9.0/x86_64-softmmu/qemu-system-x86_64 -hdb /path/to/snapshot/ram.qcow2 -hda /path/to/snapshot/overlay_0.qcow2 -machine pc-i440fx-2.6 -serial mon:stdio -enable-kvm -k de -m 512
  • (Optional) Install and load the vulnerable Test Driver:
cd path/to/kAFl/kAFL-Fuzzer/vuln_drivers/simple/linux_x86-64/
chmod u+x load.sh
sudo ./load.sh
  • Execute loader binary which is in path/to/kAFL/kAFL-Fuzzer/agents/linux_x86_64/loader/ as root. VM should freeze. Switch to the QEMU management console and create a snapshot:
# press CTRL-a + c
savevm kafl
q 

Compile and configure kAFL components

  • Edit /path/to/kAFL/kAFL-Fuzzer/kafl.ini (qemu-kafl_location to point to path/to/kAFL/qemu-2.9.0/x86_64-softmmu/qemu-system-x86_64)

  • Compile agents:

cd <KERNEL_AFL_ROOT>/kAFL-Fuzzer/agents
chmod u+x compile.sh
./compile.sh
  • Retrieve address ranges of loaded drivers:
cd /path/to/kAFL/kAFL-Fuzzer
python kafl_info.py /path/to/snapshot/ram.qcow2 /path/to/snapshot/ agents/linux_x86_64/info/info 512 -v

Start Fuzzing!

python kafl_fuzz.py /path/to/snapshot/ram.qcow2 /path/to/snapshot agents/linux_x86_64/fuzzer/kafl_vuln_test 512 /path/to/input/directory /path/to/working/directory -ip0 0xffffffffc0287000-0xffffffffc028b000 -v --Purge

The value ip0 is the address range of the fuzzing target.

Owner
Chair for Sys­tems Se­cu­ri­ty
Chair for Sys­tems Se­cu­ri­ty
Bianace Prediction Pytorch Model

Bianace Prediction Pytorch Model Main Results ETHUSDT from 2021-01-01 00:00:00 t

RoyYang 4 Jul 20, 2022
Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)

Fast and Flexible Temporal Point Processes with Triangular Maps This repository includes a reference implementation of the algorithms described in "Fa

Oleksandr Shchur 20 Dec 02, 2022
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more

Ming 2k Jan 08, 2023
Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets"

Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Data

2 Oct 06, 2022
Camera calibration & 3D pose estimation tools for AcinoSet

AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild Daniel Joska, Liam Clark, Naoya Muramatsu, Ricardo Jericevich, Fre

African Robotics Unit 42 Nov 16, 2022
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

Spacetimeformer Multivariate Forecasting This repository contains the code for the paper, "Long-Range Transformers for Dynamic Spatiotemporal Forecast

QData 440 Jan 02, 2023
FOSS Digital Asset Distribution Platform built on Frappe.

Digistore FOSS Digital Assets Marketplace. Distribute digital assets, like a pro. Video Demo Here Features Create, attach and list digital assets (PDF

Mohammad Hussain Nagaria 30 Dec 08, 2022
Code for Ditto: Building Digital Twins of Articulated Objects from Interaction

Ditto: Building Digital Twins of Articulated Objects from Interaction Zhenyu Jiang, Cheng-Chun Hsu, Yuke Zhu CVPR 2022, Oral Project | arxiv News 2022

UT Robot Perception and Learning Lab 78 Dec 22, 2022
Irrigation controller for Home Assistant

Irrigation Unlimited This integration is for irrigation systems large and small. It can offer some complex arrangements without large and messy script

Robert Cook 176 Jan 02, 2023
MTA:SA Server Configer.

MTAConfiger MTA:SA Server Configer. Hi 👋 , I'm Alireza A Python Developer Boy 🔭 I’m currently working on my C# projects 🌱 I’m currently Learning CS

3 Jun 07, 2022
Implementation of Diverse Semantic Image Synthesis via Probability Distribution Modeling

Diverse Semantic Image Synthesis via Probability Distribution Modeling (CVPR 2021) Paper Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu,

tzt 45 Nov 17, 2022
RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

Nipun Sadvilkar 23 Oct 19, 2022
Spatial color quantization in Rust

rscolorq Rust port of Derrick Coetzee's scolorq, based on the 1998 paper "On spatial quantization of color images" by Jan Puzicha, Markus Held, Jens K

Collyn O'Kane 37 Dec 22, 2022
Texture mapping with variational auto-encoders

vae-textures This is an experiment with using variational autoencoders (VAEs) to perform mesh parameterization. This was also my first project using J

Alex Nichol 41 May 24, 2022
A particular navigation route using satellite feed and can help in toll operations & traffic managemen

How about adding some info that can quanitfy the stress on a particular navigation route using satellite feed and can help in toll operations & traffic management The current analysis is on the satel

Ashish Pandey 1 Feb 14, 2022
Tools for investing in Python

InvestOps Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction This is a Python package with simple and effective

24 Nov 26, 2022
Repository For Programmers Seeking a platform to show their skills

Programming-Nerds Repository For Programmers Seeking Pull Requests In hacktoberfest ❓ What's Hacktoberfest 2021? Hacktoberfest is the easiest way to g

42 Oct 29, 2022
Agent-based model simulator for air quality and pandemic risk assessment in architectural spaces

Agent-based model simulation for air quality and pandemic risk assessment in architectural spaces. User Guide archABM is a fast and open source agent-

Vicomtech 10 Dec 05, 2022
Pytorch-3dunet - 3D U-Net model for volumetric semantic segmentation written in pytorch

pytorch-3dunet PyTorch implementation 3D U-Net and its variants: Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Spar

Adrian Wolny 1.3k Dec 28, 2022
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes

Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc

103 Jan 06, 2023