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
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.

132 Dec 23, 2022
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

Kakao Brain 72 Dec 28, 2022
This is the face keypoint train code of project face-detection-project

face-key-point-pytorch 1. Data structure The structure of landmarks_jpg is like below: |--landmarks_jpg |----AFW |------AFW_134212_1_0.jpg |------AFW_

I‘m X 3 Nov 27, 2022
Code for ICCV 2021 paper Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes using Scene Graphs

Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx

Helisa Dhamo 33 Jan 06, 2023
OSLO: Open Source framework for Large-scale transformer Optimization

O S L O Open Source framework for Large-scale transformer Optimization What's New: December 21, 2021 Released OSLO 1.0. What is OSLO about? OSLO is a

TUNiB 280 Nov 24, 2022
Simple Python project using Opencv and datetime package to recognise faces and log attendance data in a csv file.

Attendance-System-based-on-Facial-recognition-Attendance-data-stored-in-csv-file- Simple Python project using Opencv and datetime package to recognise

3 Aug 09, 2022
Code for CVPR2021 paper "Learning Salient Boundary Feature for Anchor-free Temporal Action Localization"

AFSD: Learning Salient Boundary Feature for Anchor-free Temporal Action Localization This is an official implementation in PyTorch of AFSD. Our paper

Tencent YouTu Research 146 Dec 24, 2022
This repo contains the code required to train the multivariate time-series Transformer.

Multi-Variate Time-Series Transformer This repo contains the code required to train the multivariate time-series Transformer. Download the data The No

Gregory Duthé 4 Nov 24, 2022
EfficientNetV2 implementation using PyTorch

EfficientNetV2-S implementation using PyTorch Train Steps Configure imagenet path by changing data_dir in train.py python main.py --benchmark for mode

Jahongir Yunusov 86 Dec 29, 2022
(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

IsoTree Fast and multi-threaded implementation of Extended Isolation Forest, Fair-Cut Forest, SCiForest (a.k.a. Split-Criterion iForest), and regular

141 Dec 29, 2022
EasyMocap is an open-source toolbox for markerless human motion capture from RGB videos.

EasyMocap is an open-source toolbox for markerless human motion capture from RGB videos. In this project, we provide the basic code for fitt

ZJU3DV 2.2k Jan 05, 2023
Source code for the paper "SEPP: Similarity Estimation of Predicted Probabilities for Defending and Detecting Adversarial Text" PACLIC 2021

Adversarial text generator Refer to "adversarial_text_generator"[https://github.com/quocnsh/SEPP_generator] project for generating adversarial texts A

0 Oct 05, 2021
Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxiang Wang, Han Zhao, Bo Li.

Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin

AI Secure 57 Dec 15, 2022
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting

N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting Recent progress in neural forecasting instigated significant improvements in the

Cristian Challu 82 Jan 04, 2023
Jupyter notebooks showing best practices for using cx_Oracle, the Python DB API for Oracle Database

Python cx_Oracle Notebooks, 2022 The repository contains Jupyter notebooks showing best practices for using cx_Oracle, the Python DB API for Oracle Da

Christopher Jones 13 Dec 15, 2022
Codebase for "Revisiting spatio-temporal layouts for compositional action recognition" (Oral at BMVC 2021).

Revisiting spatio-temporal layouts for compositional action recognition Codebase for "Revisiting spatio-temporal layouts for compositional action reco

Gorjan 20 Dec 15, 2022
Neural Articulated Radiance Field

Neural Articulated Radiance Field NARF Neural Articulated Radiance Field Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada ICCV 2021 [Paper] [Co

Atsuhiro Noguchi 144 Jan 03, 2023
Like Dirt-Samples, but cleaned up

Clean-Samples Like Dirt-Samples, but cleaned up, with clear provenance and license info (generally a permissive creative commons licence but check the

TidalCycles 39 Nov 30, 2022
IMBENS: class-imbalanced ensemble learning in Python.

IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a

Zhining Liu 176 Jan 04, 2023
Hyperbolic Procrustes Analysis Using Riemannian Geometry

Hyperbolic Procrustes Analysis Using Riemannian Geometry The code in this repository creates the figures presented in this article: Please notice that

Ronen Talmon's Lab 2 Jan 08, 2023