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
A hybrid framework (neural mass model + ML) for SC-to-FC prediction

The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass

Yilin Liu 1 Jan 26, 2022
A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation

A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation This repository contains the source code of the paper A Differentiable

Bernardo Aceituno 2 May 05, 2022
An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

Yige-Li 84 Jan 04, 2023
The Simplest DCGAN Implementation

DCGAN in TensorLayer This is the TensorLayer implementation of Deep Convolutional Generative Adversarial Networks. Looking for Text to Image Synthesis

TensorLayer Community 310 Dec 13, 2022
Some useful blender add-ons for SMPL skeleton's poses and global translation.

Blender add-ons for SMPL skeleton's poses and trans There are two blender add-ons for SMPL skeleton's poses and trans.The first is for making an offli

ηŠΉεœ¨ι•œδΈ­ 154 Jan 04, 2023
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

tensordiffeq 74 Dec 09, 2022
Official implementation of "Implicit Neural Representations with Periodic Activation Functions"

Implicit Neural Representations with Periodic Activation Functions Project Page | Paper | Data Vincent Sitzmann*, Julien N. P. Martel*, Alexander W. B

Vincent Sitzmann 1.4k Jan 06, 2023
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
Addition of pseudotorsion caclulation eta, theta, eta', and theta' to barnaba package

Addition to Original Barnaba Code: This is modified version of Barnaba package to calculate RNA pseudotorsion angles eta, theta, eta', and theta'. Ple

Mandar Kulkarni 1 Jan 11, 2022
Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

van_der_Schaar \LAB 89 Dec 07, 2022
Official source code of Fast Point Transformer, CVPR 2022

Fast Point Transformer Project Page | Paper This repository contains the official source code and data for our paper: Fast Point Transformer Chunghyun

182 Dec 23, 2022
Introduction to CPM

CPM CPM is an open-source program on large-scale pre-trained models, which is conducted by Beijing Academy of Artificial Intelligence and Tsinghua Uni

Tsinghua AI 136 Dec 23, 2022
[NeurIPS'20] Multiscale Deep Equilibrium Models

Multiscale Deep Equilibrium Models πŸ’₯ πŸ’₯ πŸ’₯ πŸ’₯ This repo is deprecated and we will soon stop actively maintaining it, as a more up-to-date (and simple

CMU Locus Lab 221 Dec 26, 2022
[IEEE TPAMI21] MobileSal: Extremely Efficient RGB-D Salient Object Detection [PyTorch & Jittor]

MobileSal IEEE TPAMI 2021: MobileSal: Extremely Efficient RGB-D Salient Object Detection This repository contains full training & testing code, and pr

Yu-Huan Wu 52 Jan 06, 2023
Reinforcement Learning for the Blackjack

Reinforcement Learning for Blackjack Author: ZHA Mengyue Math Department of HKUST Problem Statement We study playing Blackjack by reinforcement learni

Dolores 3 Jan 24, 2022
Convert scikit-learn models to PyTorch modules

sk2torch sk2torch converts scikit-learn models into PyTorch modules that can be tuned with backpropagation and even compiled as TorchScript. Problems

Alex Nichol 101 Dec 16, 2022
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"

[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas

PatatiPatata 28 Oct 18, 2022
Official respository for "Modeling Defocus-Disparity in Dual-Pixel Sensors", ICCP 2020

Official respository for "Modeling Defocus-Disparity in Dual-Pixel Sensors", ICCP 2020 BibTeX @INPROCEEDINGS{punnappurath2020modeling, author={Abhi

Abhijith Punnappurath 22 Oct 01, 2022
Implementation of FitVid video prediction model in JAX/Flax.

FitVid Video Prediction Model Implementation of FitVid video prediction model in JAX/Flax. If you find this code useful, please cite it in your paper:

Google Research 62 Nov 25, 2022
ICCV2021 Papers with Code

ICCV2021 Papers with Code

Amusi 1.4k Jan 02, 2023