Repo for FUZE project. I will also publish some Linux kernel LPE exploits for various real world kernel vulnerabilities here. the samples are uploaded for education purposes for red and blue teams.

Overview

Linux_kernel_exploits

Some Linux kernel exploits for various real world kernel vulnerabilities here. More exploits are yet to come.

This repo contains the exploits developed during a research project, as well as the code of FUZE to facilitate exploit generation.

What is FUZE

FUZE is a framework to facilitate linux kernel exploitation, here is the baisc idea of how it works:

  1. Critical information extraction we need to understand both spatial and temporal metadata of this vulnerability
  2. under context kernel fuzzing to find sensitive operation over the vulnerable object, e.g. dereferencing a dangling pointer
  3. partial symbolic execution After finding the dereference site of the vulnerable object, we start execution right before the dereference site, set the value in vulnerable object which can be controlled by us as symbolic bytes.

Dependency

angr, qemu-system-x86_64, ROPGadget, pwntools, GDB, gef, capstone, KASAN, ftrace

Install

To install FUZE, run the following command

git clone https://github.com/ww9210/Linux_kernel_exploits
cd Linux_kernel_exploits
python setup.py install --user

Documentation

TODO here, currently you can browser the code under fuze/test

Publication

For more details about facilitating linux kernel exploits, please refer to our USENIX paper:

@inproceedings{wu18fuze,
  title={FUZE: Towards Facilitating Exploit Generation for Kernel Use-After-Free Vulnerabilities},
  author={Wu, Wei and Chen, Yueqi and Xu, Jun and Xing, Xinyu and Gong, Xiaorui and Zou, Wei},
  booktitle={27th USENIX Security Symposium (USENIX Security 18)},
  organization={USENIX Association}
}

If this repo is of help to your research, we really appreciate you for citing the above paper.

Owner
Wei Wu
Visiting Researcher @ Penn State PhD Candidate @ University of Chinese Academy of Sciences. Pwner @ Team NeSE.
Wei Wu
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-dri

Neural Magic 1.5k Dec 30, 2022
HGCN: Harmonic Gated Compensation Network For Speech Enhancement

HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc

ScorpioMiku 33 Nov 14, 2022
Medical image analysis framework merging ANTsPy and deep learning

ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas

Advanced Normalization Tools Ecosystem 118 Dec 24, 2022
Implementation of ViViT: A Video Vision Transformer

ViViT: A Video Vision Transformer Unofficial implementation of ViViT: A Video Vision Transformer. Notes: This is in WIP. Model 2 is implemented, Model

Rishikesh (ऋषिकेश) 297 Jan 06, 2023
On the model-based stochastic value gradient for continuous reinforcement learning

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

Facebook Research 46 Dec 15, 2022
My implementation of Image Inpainting - A deep learning Inpainting model

Image Inpainting What is Image Inpainting Image inpainting is a restorative process that allows for the fixing or removal of unwanted parts within ima

Joshua V Evans 1 Dec 12, 2021
Code repo for "Transformer on a Diet" paper

Transformer on a Diet Reference: C Wang, Z Ye, A Zhang, Z Zhang, A Smola. "Transformer on a Diet". arXiv preprint arXiv (2020). Installation pip insta

cgraywang 31 Sep 26, 2021
Solving reinforcement learning tasks which require language and vision

Multimodal Reinforcement Learning JAX implementations of the following multimodal reinforcement learning approaches. Dual-coding Episodic Memory from

Henry Prior 31 Feb 26, 2022
Distance Encoding for GNN Design

Distance-encoding for GNN design This repository is the official PyTorch implementation of the DEGNN and DEAGNN framework reported in the paper: Dista

172 Nov 08, 2022
Official pytorch implementation for Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion (CVPR 2022)

Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion This repository contains a pytorch implementation of "Learning to Listen: Modeling

50 Dec 17, 2022
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c

Phil Wang 272 Dec 23, 2022
PlenOctree Extraction algorithm

PlenOctrees_NeRF-SH This is an implementation of the Paper PlenOctrees for Real-time Rendering of Neural Radiance Fields. Not only the code provides t

49 Nov 05, 2022
A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.

CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,

5 Apr 29, 2022
SmoothGrad implementation in PyTorch

SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro

SSKH 143 Jan 05, 2023
Repository of best practices for deep learning in Julia, inspired by fastai

FastAI Docs: Stable | Dev FastAI.jl is inspired by fastai, and is a repository of best practices for deep learning in Julia. Its goal is to easily ena

FluxML 532 Jan 02, 2023
RADIal is available now! Check the download section

Latest news: RADIal is available now! Check the download section. However, because we are currently working on the data anonymization, we provide for

valeo.ai 55 Jan 03, 2023
TensorFlow implementation of original paper : https://github.com/hszhao/PSPNet

Keras implementation of PSPNet(caffe) Implemented Architecture of Pyramid Scene Parsing Network in Keras. For the best compability please use Python3.

VladKry 386 Dec 29, 2022
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'

Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang News 2021.12.5 Release Deep

145 Jan 05, 2023
PyTorch framework for Deep Learning research and development.

Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati

Catalyst-Team 29 Jul 13, 2022
PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.

End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th

Liyan 52 Jan 04, 2023