Piotr - IoT firmware emulation instrumentation for training and research

Related tags

Deep Learningpiotr
Overview

Piotr: Pythonic IoT exploitation and Research

Introduction to Piotr

Piotr is an emulation helper for Qemu that provides a convenient way to create, share and run virtual IoT devices. It only supports the ARM Architecture at the moment.

Piotr is heavily inspired from @therealsaumil's ARM-X framework and keeps the same approach: emulated devices run inside an emulated host that provides all the tools you may need and creates a fake environment for them. This approach allows remote debugging with gdbserver or fridaserver, provides a steady platform for vulnerability research, exploitation and training.

Moreover, Piotr is able to package any emulated device into a single file that may be shared and imported by other users, thus sharing its kernel, DTB file or even its host filesystem. This way, it is possible to create new emulated devices based upon existing ones, and to improve all of them by simply changing a single file (kernel, host filesystem, etc.).

How does Piotr work ?

Piotr stores everything it needs inside a specific user directory called .piotr, located in the user's home directory. This directory stores all the kernels, dtb files, host filesystems and emulated devices.

Each emulated device is stored in a specific subdirectory of your .piotr/devices directory, and must contain at least:

  • a config.yaml file containing the device's qemu configuration in a readable way
  • a root filesystem with correct permissions and groups and users

When Piotr is asked to emulate a specific device, it loads its config.yaml file, parses it and creates a Qemu emulated device with the corresponding specifications.

This emulated device can then be driven by Piotr's helper tools in order to:

  • list or kill running processes
  • dynamically configure network interfaces
  • debug any process running on the emulated device
  • ...

Reference documentation

Piotr's reference documentation is available on Read The Docs. If you want to start using Piotr as soon as possible, we recommend you to read our Quickstart guide !

License

Piotr is released under the MIT license, see LICENSE for more information.

Owner
Damien Cauquil
Proud dad, happy geek, random hacker.
Damien Cauquil
Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"

StyleAttack Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer" Prepare Pois

THUNLP 19 Nov 20, 2022
Yolov5 deepsort inference,使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中

使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中。

813 Dec 31, 2022
Stacs-ci - A set of modules to enable integration of STACS with commonly used CI / CD systems

Static Token And Credential Scanner CI Integrations What is it? STACS is a YARA

STACS 18 Aug 04, 2022
MagFace: A Universal Representation for Face Recognition and Quality Assessment

MagFace MagFace: A Universal Representation for Face Recognition and Quality Assessment in IEEE Conference on Computer Vision and Pattern Recognition

Qiang Meng 523 Jan 05, 2023
ScriptProfilerPy - Module to visualize where your python script is slow

ScriptProfiler helps you track where your code is slow It provides: Code lines t

Lucas BLP 3 Jun 02, 2022
paper list in the area of reinforcenment learning for recommendation systems

paper list in the area of reinforcenment learning for recommendation systems

HenryZhao 23 Jun 09, 2022
The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation"

SD-AANet The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation" [arxiv] Overview confi

cv516Buaa 9 Nov 07, 2022
Compare outputs between layers written in Tensorflow and layers written in Pytorch

Compare outputs of Wasserstein GANs between TensorFlow vs Pytorch This is our testing module for the implementation of improved WGAN in Pytorch Prereq

Hung Nguyen 72 Dec 20, 2022
[CVPR 2022] Official Pytorch code for OW-DETR: Open-world Detection Transformer

OW-DETR: Open-world Detection Transformer (CVPR 2022) [Paper] Akshita Gupta*, Sanath Narayan*, K J Joseph, Salman Khan, Fahad Shahbaz Khan, Mubarak Sh

Akshita Gupta 127 Dec 27, 2022
Pytorch code for semantic segmentation using ERFNet

ERFNet (PyTorch version) This code is a toolbox that uses PyTorch for training and evaluating the ERFNet architecture for semantic segmentation. For t

Edu 394 Jan 01, 2023
LaneDetectionAndLaneKeeping - Lane Detection And Lane Keeping

LaneDetectionAndLaneKeeping This project is part of my bachelor's thesis. The go

5 Jun 27, 2022
Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies.

Crypto_Bot Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies. Steps to get started using the bot: Sign up

21 Oct 03, 2022
The sixth place winning solution (6/220) in 2021 Gaofen Challenge.

SwinTransformer + OBBDet The sixth place winning solution (6/220) in the track of Fine-grained Object Recognition in High-Resolution Optical Images, 2

ming71 46 Dec 02, 2022
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.

Swin Transformer for Semantic Segmentation of satellite images This repo contains the supported code and configuration files to reproduce semantic seg

23 Oct 10, 2022
PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our paper

Flow Gaussian Mixture Model (FlowGMM) This repository contains a PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our pa

Pavel Izmailov 124 Nov 06, 2022
Official page of Patchwork (RA-L'21 w/ IROS'21)

Patchwork Official page of "Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor

Hyungtae Lim 254 Jan 05, 2023
Riemannian Convex Potential Maps

Modeling distributions on Riemannian manifolds is a crucial component in understanding non-Euclidean data that arises, e.g., in physics and geology. The budding approaches in this space are limited b

Facebook Research 61 Nov 28, 2022
Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer This repository contains the PyTorch code for Evo-ViT. This work proposes a slow-fas

YifanXu 53 Dec 05, 2022
Mini Software that give reminder to drink water as per your weight.

Water Notification Desktop Python The Mini Software built in Python (tkinter) that will remind you to drink water on specific time span based on your

Om Jogani 5 Dec 16, 2022
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a

62 Dec 05, 2022