Fuzzing JavaScript Engines with Aspect-preserving Mutation

Related tags

Deep LearningDIE
Overview

DIE

Repository for "Fuzzing JavaScript Engines with Aspect-preserving Mutation" (in S&P'20). You can check the paper for technical details.

Environment

Tested on Ubuntu 18.04 with following environment.

  • Python v3.6.10
  • npm v6.14.6
  • n v6.7.0

General Setup

For nodejs and npm,

$ sudo apt-get -y install npm
$ sudo npm install -g n
$ sudo n stable

For redis-server,

$ sudo apt install redis-server

we choose clang-6.0 to compile afl and browsers smoothly.

$ sudo apt-get -y install clang-6.0

DIE Setup

To setup environment for AFL,

$ cd fuzz/scripts
$ sudo ./prepare.sh

To compile whole project,

$ ./compile.sh

Server Setup

  • Make Corpus Directory (We used Die-corpus as corpus)
$ git clone https://github.com/sslab-gatech/DIE-corpus.git
$ python3 ./fuzz/scripts/make_initial_corpus.py ./DIE-corpus ./corpus
  • Make ssh-tunnel for connection with redis-server
$ ./fuzz/scripts/redis.py
  • Dry run with corpus
$ ./fuzz/scripts/populate.sh [target binary path] [path of DIE-corpus dir] [target js engine (ch/jsc/v8/ffx)]
# Example
$ ./fuzz/scripts/populate.sh ~/ch ./DIE-corpus ch

It's done! Your corpus is well executed and the data should be located on redis-server.

Tips

To check the redis-data,

$ redis-cli -p 9000
127.0.0.1:9000> keys *

If the result contains "crashBitmap", "crashQueue", "pathBitmap", "newPathsQueue" keys, the fuzzer was well registered and executed.

Client Setup

  • Make ssh-tunnel for connection with redis-server
$ ./fuzz/scripts/redis.py
  • Usage
$ ./fuzz/scripts/run.sh [target binary path] [path of DIE-corpus dir] [target js engine (ch/jsc/v8/ffx)]
# Example
$ ./fuzz/scripts/run.sh ~/ch ./DIE-corpus ch
  • Check if it's running
$ tmux ls

You can find a session named fuzzer if it's running.

Typer

We used d8 to profile type information. So, please change d8_path in fuzz/TS/typer/typer.py before execution.

cd fuzz/TS/typer
python3 typer.py [corpus directory]

*.jsi file will be created if instrumentation works well. *.t file will be created if profiling works well.

CVEs

If you find bugs and get CVEs by running DIE, please let us know.

  • ChakraCore: CVE-2019-0609, CVE-2019-1023, CVE-2019-1300, CVE-2019-0990, CVE-2019-1092
  • JavaScriptCore: CVE-2019-8676, CVE-2019-8673, CVE-2019-8811, CVE-2019-8816
  • V8: CVE-2019-13730, CVE-2019-13764, CVE-2020-6382

Contacts

Citation

@inproceedings{park:die,
  title        = {{Fuzzing JavaScript Engines with Aspect-preserving Mutation}},
  author       = {Soyeon Park and Wen Xu and Insu Yun and Daehee Jang and Taesoo Kim},
  booktitle    = {Proceedings of the 41st IEEE Symposium on Security and Privacy (Oakland)},
  month        = may,
  year         = 2020,
  address      = {San Francisco, CA},
}
Owner
gts3.org ([email protected])
https://gts3.org
gts3.org (<a href=[email protected])">
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).

Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em

Benedek Rozemberczki 69 Sep 22, 2022
Benchmark datasets, data loaders, and evaluators for graph machine learning

Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover

1.5k Jan 05, 2023
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)

Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification

Youngkyu 17 Jan 01, 2023
Equivariant GNN for the prediction of atomic multipoles up to quadrupoles.

Equivariant Graph Neural Network for Atomic Multipoles Description Repository for the Model used in the publication 'Learning Atomic Multipoles: Predi

16 Nov 22, 2022
Cognition-aware Cognate Detection

Cognition-aware Cognate Detection The repository which contains our code for our EACL 2021 paper titled, "Cognition-aware Cognate Detection". This wor

Prashant K. Sharma 1 Feb 01, 2022
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.

A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.

224 Jan 04, 2023
Python scripts form performing stereo depth estimation using the CoEx model in ONNX.

ONNX-CoEx-Stereo-Depth-estimation Python scripts form performing stereo depth estimation using the CoEx model in ONNX. Stereo depth estimation on the

Ibai Gorordo 8 Dec 29, 2022
PyTorch implementation of Weak-shot Fine-grained Classification via Similarity Transfer

SimTrans-Weak-Shot-Classification This repository contains the official PyTorch implementation of the following paper: Weak-shot Fine-grained Classifi

BCMI 60 Dec 02, 2022
Gauge equivariant mesh cnn

Geometric Mesh CNN The code in this repository is an implementation of the Gauge Equivariant Mesh CNN introduced in the paper Gauge Equivariant Mesh C

50 Dec 18, 2022
Generate image analogies using neural matching and blending

neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat

Adam Wentz 3.5k Jan 08, 2023
An addon uses SMPL's poses and global translation to drive cartoon character in Blender.

Blender addon for driving character The addon drives the cartoon character by passing SMPL's poses and global translation into model's armature in Ble

犹在镜中 153 Dec 14, 2022
VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

VOS This is the source code accompanying the paper VOS: Learning What You Don’t

248 Dec 25, 2022
NudeNet: Neural Nets for Nudity Classification, Detection and selective censoring

NudeNet: Neural Nets for Nudity Classification, Detection and selective censoring Uncensored version of the following image can be found at https://i.

notAI.tech 1.1k Dec 29, 2022
Pyramid Pooling Transformer for Scene Understanding

Pyramid Pooling Transformer for Scene Understanding Requirements: torch 1.6+ torchvision 0.7.0 timm==0.3.2 Validated on torch 1.6.0, torchvision 0.7.0

Yu-Huan Wu 119 Dec 29, 2022
Continual Learning of Electronic Health Records (EHR).

Continual Learning of Longitudinal Health Records Repo for reproducing the experiments in Continual Learning of Longitudinal Health Records (2021). Re

Jacob 7 Oct 21, 2022
DenseNet Implementation in Keras with ImageNet Pretrained Models

DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted

Felix Yu 568 Oct 31, 2022
This repository consists of Blender python scripts and corresponding assets to generate variants of the CANDLE dataset

candle-simulator This repository consists of Blender python scripts and corresponding assets to generate variants of the IITH-CANDLE dataset. The rend

1 Dec 15, 2021
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

Rahul Vigneswaran 1 Jan 17, 2022
A working implementation of the Categorical DQN (Distributional RL).

Categorical DQN. Implementation of the Categorical DQN as described in A distributional Perspective on Reinforcement Learning. Thanks to @tudor-berari

Florin Gogianu 98 Sep 20, 2022