Hcpy - Interface with Home Connect appliances in Python

Related tags

Deep Learninghcpy
Overview

dishwasher installed in a kitchen

Interface with Home Connect appliances in Python

This is a very, very beta interface for Bosch-Siemens Home Connect devices through their local network connection. It has some tools to find the TLS PSK (Pre-shared Key) that is used to allow local access, and a Python script that can construct the proper Websocket interface to subscribe to events.

WARNING: This is not ready for prime time!

The dishwasher has a local HTTPS port open (and the dryer seems to have unencrypted HTTP). Attempting to connect to the HTTPS port with curl results in a cryptic protocol error due to the non-standard cipher selection, ECDHE-PSK-CHACHA20-POLY1305. PSK also requires that both sides agree on a symetric key, so it is necessary to figure out what that key is before any further progress can be made.

Finding the PSK

application setup screen

You will need to set the dishwasher to "Local network only" in the setup application so that your phone will connect directly to it, rather than going through the cloud services.

You'll also need a rooted Android phone running frida-server and the find-psk.frida script. This will hook the callback from the OpenSSL library hcp::client_psk_callback that is called when OpenSSL has made a connection and now needs to establish the PSK.

frida --no-pause -f com.bshg.homeconnect.android.release -U -l find-psk.frida

It should start the Home Connect application and eventually print a message like:

psk callback hint 'HCCOM_Local_App'
psk 32 0x6ee63fb2f0
           0  1  2  3  4  5  6  7  8  9  A  B  C  D  E  F  0123456789ABCDEF
00000000  0e c8 1f d8 c6 49 fa d8 bc e7 fd 34 33 54 13 d4  .....I.....43T..
00000010  73 f9 2e 01 fc d8 26 80 49 89 4c 19 d7 2e cd cb  s.....&.I.L.....

Which gives you the 32-byte PSK value to copy into the hcpy program.

SSL logging

The Frida script will also dump all of the SSL traffic so that you can see different endpoints and things. Not much is documented yet.

Note that the TX from the phone on the websocket is "masked" with an repeating 4-byte XOR that is sent in the first part of each messages. The script could be augmented to decode those as well. The replies from the device are not masked so they can be read in the clear.

hcpy

The hcpy tool can contact your device, and if the PSK is correct, it will register for notification of events.

RX: {'sID': 2354590730, 'msgID': 3734589701, 'resource': '/ei/initialValues', 'version': 2, 'action': 'POST', 'data': [{'edMsgID': 3182729968}]}
TX: {"sID":2354590730,"msgID":3734589701,"resource":"/ei/initialValues","version":2,"action":"RESPONSE","data":[{"deviceType":"Application","deviceName":"py-hca","deviceID":"1234"}]}
TX: {"sID":2354590730,"msgID":3182729968,"resource":"/ci/services","version":1,"action":"GET"}
TX: {"sID":2354590730,"msgID":3182729969,"resource":"/iz/info","version":1,"action":"GET"}
TX: {"sID":2354590730,"msgID":3182729970,"resource":"/ei/deviceReady","version":2,"action":"NOTIFY"}
RX: {'sID': 2354590730, 'msgID': 3182729968, 'resource': '/ci/services', 'version': 1, 'action': 'RESPONSE', 'data': [{'service': 'ci', 'version': 3}, {'service': 'ei', 'version': 2}, {'service': 'iz', 'version': 1}, {'service': 'ni', 'version': 1}, {'service': 'ro', 'version': 1}]}
RX: {'sID': 2354590730, 'msgID': 3182729969, 'resource': '/iz/info', 'version': 1, 'action': 'RESPONSE', 'data': [{'deviceID': '....', 'eNumber': 'SX65EX56CN/11', 'brand': 'SIEMENS', 'vib': 'SX65EX56CN', 'mac': '....', 'haVersion': '1.4', 'swVersion': '3.2.10.20200911163726', 'hwVersion': '2.0.0.2', 'deviceType': 'Dishwasher', 'deviceInfo': '', 'customerIndex': '11', 'serialNumber': '....', 'fdString': '0201', 'shipSki': '....'}]}

Feature UID mapping

There are other things that can be hooked in the application to get the mappings of the uid to actual menu settings and XML files of the configuration parameters.

In the xml/ directory are some of the device descriptions and feature maps that the app downloads from the Home Connect servers. Note that the XML has unadorned hex, while the websocket messages are in decimal.

For instance, when the dishwasher door is closed and then re-opened, it sends the messages for 'uid':512, which is 0x020F hex:

RX: {... 'data': [{'uid': 527, 'value': 1}]}
RX: {... 'data': [{'uid': 527, 'value': 0}]}

In the xml/dishwasher-description.xml there is a statusList that says uid 0x020f is a readonly value that uses enum 0x0201:

">
    
  

In the xml/dishwasher-featuremap.xml there is a mapping of feature reference UIDs to names:

BSH.Common.Status.DoorState">
    
   
    BSH.Common.Status.DoorState
   

as well as mappings of enum ids to enum names and values:

Open Closed ">
    
   
      
    
     Open
    
      
    
     Closed
    
    
   
Owner
Trammell Hudson
I like to take things apart.
Trammell Hudson
Knowledge Management for Humans using Machine Learning & Tags

HyperTag HyperTag helps humans intuitively express how they think about their files using tags and machine learning.

Ravn Tech, Inc. 165 Nov 04, 2022
Human head pose estimation using Keras over TensorFlow.

RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild.

Rafael Berral Soler 71 Jan 05, 2023
Local-Global Stratified Transformer for Efficient Video Recognition

DualFormer This repo is the implementation of our manuscript entitled "Local-Global Stratified Transformer for Efficient Video Recognition". Our model

Sea AI Lab 19 Dec 07, 2022
Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"

RNN-for-Joint-NLU Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"

Kim SungDong 194 Dec 28, 2022
Memory efficient transducer loss computation

Introduction This project implements the optimization techniques proposed in Improving RNN Transducer Modeling for End-to-End Speech Recognition to re

Fangjun Kuang 51 Nov 25, 2022
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in

2 Aug 05, 2022
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data

58 Oct 26, 2022
Boostcamp AI Tech 3rd / Basic Paper reading w.r.t Embedding

Boostcamp AI Tech 3rd : Basic Paper Reading w.r.t Embedding TL;DR 1992년부터 2018년도까지 이루어진 word/sentence embedding의 중요한 줄기를 이루는 기초 논문 스터디를 진행하고자 합니다. 논

Soyeon Kim 14 Nov 14, 2022
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C

Robert-Jan Bruintjes 96 Dec 12, 2022
Predicting Price of house by considering ,house age, Distance from public transport

House-Price-Prediction Predicting Price of house by considering ,house age, Distance from public transport, No of convenient stores around house etc..

Musab Jaleel 1 Jan 08, 2022
A collection of papers about Transformer in the field of medical image analysis.

A collection of papers about Transformer in the field of medical image analysis.

Junyu Chen 377 Jan 05, 2023
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

Advanced Image Manipulation Lab @ Samsung AI Center Moscow 4.7k Dec 31, 2022
Official Implementation of DE-DETR and DELA-DETR in "Towards Data-Efficient Detection Transformers"

DE-DETRs By Wen Wang, Jing Zhang, Yang Cao, Yongliang Shen, and Dacheng Tao This repository is an official implementation of DE-DETR and DELA-DETR in

Wen Wang 61 Dec 12, 2022
Custom IMDB Dataset is extracted between 2020-2021 and custom distilBERT model is trained for movie success probability prediction

IMDB Success Predictor Project involves Web Scraping custom IMDB data between 2020 and 2021 of 10000 movies and shows sorted by number of votes ,fine

Gautam Diwan 1 Jan 18, 2022
Residual Dense Net De-Interlace Filter (RDNDIF)

Residual Dense Net De-Interlace Filter (RDNDIF) Work in progress deep de-interlacer filter. It is based on the architecture proposed by Bernasconi et

Louis 7 Feb 15, 2022
A tensorflow model that predicts if the image is of a cat or of a dog.

Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here

Tudor Matei 0 Mar 08, 2022
Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling

Permutation Invariant Graph Generation via Score-Based Generative Modeling This repo contains the official implementation for the paper Permutation In

64 Dec 29, 2022
[CVPR 2021 Oral] ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis [arxiv|pdf|v

Yinan He 78 Dec 22, 2022
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Somshubra Majumdar 15 Feb 10, 2022
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"

GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai

Big Data and Multi-modal Computing Group, CRIPAC 97 Jan 07, 2023