QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing

Overview

QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing

Environment

  • Tested on Ubuntu 14.04 64bit and 16.04 64bit

Installation

# disable ptrace_scope for PIN
$ echo 0|sudo tee /proc/sys/kernel/yama/ptrace_scope

# install z3 and system deps
$ ./setup.sh

# install using virtual env
$ virtualenv venv
$ source venv/bin/activate
$ pip install .

Installation using Docker

# disable ptrace_scope for PIN
$ echo 0|sudo tee /proc/sys/kernel/yama/ptrace_scope

# build docker image
$ docker build -t qsym ./

# run docker image
$ docker run --cap-add=SYS_PTRACE -it qsym /bin/bash

Installation using vagrant

Since QSYM is dependent on underlying kernel because of its old PIN, we decided to provide a convenient way to install QSYM with VM. Please take a look our vagrant directory.

Run hybrid fuzzing with AFL

# require to set the following environment variables
#   AFL_ROOT: afl directory (http://lcamtuf.coredump.cx/afl/)
#   INPUT: input seed files
#   OUTPUT: output directory
#   AFL_CMDLINE: command line for a testing program for AFL (ASAN + instrumented)
#   QSYM_CMDLINE: command line for a testing program for QSYM (Non-instrumented)

# run AFL master
$ $AFL_ROOT/afl-fuzz -M afl-master -i $INPUT -o $OUTPUT -- $AFL_CMDLINE
# run AFL slave
$ $AFL_ROOT/afl-fuzz -S afl-slave -i $INPUT -o $OUTPUT -- $AFL_CMDLINE
# run QSYM
$ bin/run_qsym_afl.py -a afl-slave -o $OUTPUT -n qsym -- $QSYM_CMDLINE

Run for testing

$ cd tests
$ python build.py
$ python -m pytest -n $(nproc)

Troubleshooting

If you find that you can't get QSYM to work and you get the undefined symbol: Z3_is_seq_sort error in pin.log file, please make sure that you compile and make the target when you're in the virtualenv (env) environment. When you're out of this environment and you compile the target, QSYM can't work with the target binary and issues the mentioned error in pin.log file. This will save your time a lot to compile and make the target from env and then run QSYM on the target, then QSYM will work like a charm!

Authors

Publications

QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing

@inproceedings{yun:qsym,
  title        = {{QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing}},
  author       = {Insu Yun and Sangho Lee and Meng Xu and Yeongjin Jang and Taesoo Kim},
  booktitle    = {Proceedings of the 27th USENIX Security Symposium (Security)},
  month        = aug,
  year         = 2018,
  address      = {Baltimore, MD},
}
Owner
gts3.org ([email protected])
https://gts3.org
gts3.org (<a href=[email protected])">
Implementation of the paper titled "Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees"

Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees Implementation of the paper titled "Using Sampling to

MIDAS, IIIT Delhi 2 Aug 29, 2022
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L

Facebook Research 281 Dec 22, 2022
Python wrapper to access the amazon selling partner API

PYTHON-AMAZON-SP-API Amazon Selling-Partner API If you have questions, please join on slack Contributions very welcome! Installation pip install pytho

Michael Primke 330 Jan 06, 2023
A minimal TPU compatible Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

NeRF Minimal Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Result of Tiny-NeRF RGB Depth

Soumik Rakshit 11 Jul 24, 2022
SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images.

SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images (IEEE GRSL 2021) Code (based on mmdetection) for SSPNet: Scale Selec

Italian Cannon 37 Dec 28, 2022
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,

Yuanming Hu 719 Dec 29, 2022
Training deep models using anime, illustration images.

animeface deep models for anime images. Datasets anime-face-dataset Anime faces collected from Getchu.com. Based on Mckinsey666's dataset. 63.6K image

Tomoya Sawada 61 Dec 25, 2022
Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch

Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch Reference Paper URL Author: Yi Tay, Dara Bahri, Donald Metzler

Myeongjun Kim 66 Nov 30, 2022
Supercharging Imbalanced Data Learning WithCausal Representation Transfer

ECRT: Energy-based Causal Representation Transfer Code for Supercharging Imbalanced Data Learning With Energy-basedContrastive Representation Transfer

Zidi Xiu 11 May 02, 2022
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

Pranav 39 Nov 21, 2022
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

yueliu1999 297 Dec 27, 2022
Introducing neural networks to predict stock prices

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Vivek Palaniappan 637 Jan 04, 2023
Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

IDRL 330 Jan 07, 2023
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models

AdvBox 1.3k Dec 25, 2022
NeuroGen: activation optimized image synthesis for discovery neuroscience

NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio

3 Aug 17, 2022
Experiments with the Robust Binary Interval Search (RBIS) algorithm, a Query-Based prediction algorithm for the Online Search problem.

OnlineSearchRBIS Online Search with Best-Price and Query-Based Predictions This is the implementation of the Robust Binary Interval Search (RBIS) algo

S. K. 1 Apr 16, 2022
Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors.

PairRE Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors. This implementation of PairRE for Open Graph Benchmak datasets (

Alipay 65 Dec 19, 2022
The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach

The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach

ycj_project 1 Jan 18, 2022
[ACM MM 2021] TSA-Net: Tube Self-Attention Network for Action Quality Assessment

Tube Self-Attention Network (TSA-Net) This repository contains the PyTorch implementation for paper TSA-Net: Tube Self-Attention Network for Action Qu

ShunliWang 18 Dec 23, 2022
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees

Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe

cmusatyalab 260 Dec 28, 2022