A universal memory dumper using Frida

Related tags

Deep Learningfridump
Overview

Fridump

Fridump (v0.1) is an open source memory dumping tool, primarily aimed to penetration testers and developers. Fridump is using the Frida framework to dump accessible memory addresses from any platform supported. It can be used from a Windows, Linux or Mac OS X system to dump the memory of an iOS, Android or Windows application.

Usage

How to:

  fridump [-h] [-o dir] [-U] [-v] [-r] [-s] [--max-size bytes] process

The following are the main flags that can be used with fridump:

  positional arguments:
  process            the process that you will be injecting to

  optional arguments:
  -h, --help         show this help message and exit
  -o dir, --out dir  provide full output directory path. (def: 'dump')
  -U, --usb          device connected over usb
  -v, --verbose      verbose
  -r, --read-only    dump read-only parts of memory. More data, more errors
  -s, --strings      run strings on all dump files. Saved in output dir.
  --max-size bytes   maximum size of dump file in bytes (def: 20971520)

To find the name of a local process, you can use:

  frida-ps

For a process that is running on a USB connected device, you can use:

  frida-ps -U

Examples:

  fridump -U Safari   -   Dump the memory of an iOS device associated with the Safari app
  fridump -U -s com.example.WebApp   -  Dump the memory of an Android device and run strings on all dump files
  fridump -r -o [full_path]  -  Dump the memory of a local application and save it to the specified directory

More examples can be found here

Installation

To install Fridump you just need to clone it from git and run it:

  git clone https://github.com/Nightbringer21/fridump.git
        
  python fridump.py -h

Pre-requisites

To use fridump you need to have frida installed on your python environment and frida-server on the device you are trying to dump the memory from. The easiest way to install frida on your python is using pip:

pip install frida

More information on how to install Frida can be found here

For iOS, installation instructions can be found here.

For Android, installation instructions can be found here.

Note: On Android devices, make sure that the frida-server binary is running as root!

Disclaimer

  • This is version 0.1 of the software, so I expect some bugs to be present
  • I am not a developer, so my coding skills might not be the best

This tool has been tested on a Windows 7 and a Mac OS X laptop, dumping the memory of:

  • an iPad Air 2 running iOS 8.2
  • a Galaxy Tab running Cyanogenmod 4.4.4
  • a Windows 7 laptop.

Therefore, if this tool is not working for you, I apologise and I will try to fix it.

Any suggestions and comments are welcome!

A small demonstration of using WebDataset with ImageNet and PyTorch Lightning

A small demonstration of using WebDataset with ImageNet and PyTorch Lightning

Tom 50 Dec 16, 2022
TransReID: Transformer-based Object Re-Identification

TransReID: Transformer-based Object Re-Identification [arxiv] The official repository for TransReID: Transformer-based Object Re-Identification achiev

569 Dec 30, 2022
3D cascade RCNN for object detection on point cloud

3D Cascade RCNN This is the implementation of 3D Cascade RCNN: High Quality Object Detection in Point Clouds. We designed a 3D object detection model

Qi Cai 22 Dec 02, 2022
QueryInst: Parallelly Supervised Mask Query for Instance Segmentation

QueryInst is a simple and effective query based instance segmentation method driven by parallel supervision on dynamic mask heads, which outperforms previous arts in terms of both accuracy and speed.

Hust Visual Learning Team 386 Jan 08, 2023
PURE: End-to-End Relation Extraction

PURE: End-to-End Relation Extraction This repository contains (PyTorch) code and pre-trained models for PURE (the Princeton University Relation Extrac

Princeton Natural Language Processing 657 Jan 09, 2023
This repository is for our EMNLP 2021 paper "Automated Generation of Accurate & Fluent Medical X-ray Reports"

Introduction: X-Ray Report Generation This repository is for our EMNLP 2021 paper "Automated Generation of Accurate & Fluent Medical X-ray Reports". O

no name 36 Dec 16, 2022
Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving Abstract In this paper, we introduce SalsaNext f

308 Jan 04, 2023
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods

SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (

8 Dec 13, 2022
Vector.ai assignment

fabio-tests-nisargatman Low Level Approach: ###Tables: continents: id*, name, population, area, createdAt, updatedAt countries: id*, name, population,

Ravi Pullagurla 1 Nov 09, 2021
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha

Winnie Xu 95 Nov 26, 2021
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"

DSPoint Official implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion". Paper link: https://arxiv.org/abs/2111.10

Ziyao Zeng 14 Feb 26, 2022
EsViT: Efficient self-supervised Vision Transformers

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

Microsoft 352 Dec 25, 2022
This repo contains the official code of our work SAM-SLR which won the CVPR 2021 Challenge on Large Scale Signer Independent Isolated Sign Language Recognition.

Skeleton Aware Multi-modal Sign Language Recognition By Songyao Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li and Yun Fu. Smile Lab @ Northeastern

Isen (Songyao Jiang) 128 Dec 08, 2022
DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

DeepMetaHandles (CVPR2021 Oral) [paper] [animations] DeepMetaHandles is a shape deformation technique. It learns a set of meta-handles for each given

Liu Minghua 73 Dec 15, 2022
MaRS - a recursive filtering framework that allows for truly modular multi-sensor integration

The Modular and Robust State-Estimation Framework, or short, MaRS, is a recursive filtering framework that allows for truly modular multi-sensor integration

Control of Networked Systems - University of Klagenfurt 143 Dec 29, 2022
CKD - Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding

Collaborative Knowledge Distillation for Heterogeneous Information Network Embed

zhousheng 9 Dec 05, 2022
[AAAI 2021] EMLight: Lighting Estimation via Spherical Distribution Approximation and [ICCV 2021] Sparse Needlets for Lighting Estimation with Spherical Transport Loss

EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas

Fangneng Zhan 144 Jan 06, 2023
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)

[Japanese/English] GrabCut-Annotation-Tool GrabCut-Annotation-Tool.mp4 OpenCVのGrabCut()を利用したアノテーションツールです。 セマンティックセグメンテーション向けのデータセット作成にご使用いただけます。 ※Grab

KazuhitoTakahashi 30 Nov 18, 2022
Metadata-Extractor - Metadata Extractor Script can be used to read in exif metadata

Metadata Extractor The exifextract script can be used to read in exif metadata f

1 Feb 16, 2022
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System

Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System This repository contains code for the paper Schultheis,

2 Oct 28, 2022