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
Implementation of SiameseXML (ICML 2021)

SiameseXML Code for SiameseXML: Siamese networks meet extreme classifiers with 100M labels Best Practices for features creation Adding sub-words on to

Extreme Classification 35 Nov 06, 2022
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering

[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt

Sai Kumar Dwivedi 83 Nov 27, 2022
Tree LSTM implementation in PyTorch

Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati

Riddhiman Dasgupta 529 Dec 10, 2022
Code for technical report "An Improved Baseline for Sentence-level Relation Extraction".

RE_improved_baseline Code for technical report "An Improved Baseline for Sentence-level Relation Extraction". Requirements torch = 1.8.1 transformers

Wenxuan Zhou 74 Nov 29, 2022
Official pytorch implementation of "Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization" ACMMM 2021 (Oral)

Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization This is an official implementation of "Feature Stylization and Domain-

22 Sep 22, 2022
This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer

OODformer: Out-Of-Distribution Detection Transformer This repo is the official the implementation of the OODformer: Out-Of-Distribution Detection Tran

34 Dec 02, 2022
An implementation of Deep Forest 2021.2.1.

Deep Forest (DF) 21 DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than

LAMDA Group, Nanjing University 795 Jan 03, 2023
PyTorch implementation of Pointnet2/Pointnet++

Pointnet2/Pointnet++ PyTorch Project Status: Unmaintained. Due to finite time, I have no plans to update this code and I will not be responding to iss

Erik Wijmans 1.2k Dec 29, 2022
End-to-End Referring Video Object Segmentation with Multimodal Transformers

End-to-End Referring Video Object Segmentation with Multimodal Transformers This repo contains the official implementation of the paper: End-to-End Re

608 Dec 30, 2022
Tooling for GANs in TensorFlow

TensorFlow-GAN (TF-GAN) TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs). Can be installed with pip

803 Dec 24, 2022
AbelNN: Deep Learning Python module from scratch

AbelNN: Deep Learning Python module from scratch I have implemented several neural networks from scratch using only Numpy. I have designed the module

Abel 2 Apr 12, 2022
Controlling the MicriSpotAI robot from scratch

Project-MicroSpot-AI Controlling the MicriSpotAI robot from scratch Colaborators Alexander Dennis Components from MicroSpot The MicriSpotAI has the fo

Dennis Núñez-Fernández 5 Oct 20, 2022
基于深度强化学习的原神自动钓鱼AI

原神自动钓鱼AI由YOLOX, DQN两部分模型组成。使用迁移学习,半监督学习进行训练。 模型也包含一些使用opencv等传统数字图像处理方法实现的不可学习部分。

4.2k Jan 01, 2023
A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK

Pytorch-MBNet A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK Training To train a new model, please ru

46 Dec 28, 2022
Keras implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 8.9k Jan 04, 2023
Unbalanced Feature Transport for Exemplar-based Image Translation (CVPR 2021)

UNITE and UNITE+ Unbalanced Feature Transport for Exemplar-based Image Translation (CVPR 2021) Unbalanced Intrinsic Feature Transport for Exemplar-bas

Fangneng Zhan 183 Nov 09, 2022
VD-BERT: A Unified Vision and Dialog Transformer with BERT

VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia

Salesforce 44 Nov 01, 2022
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

yobi byte 29 Oct 09, 2022
A web application that provides real time temperature and humidity readings of a house.

About A web application which provides real time temperature and humidity readings of a house. If you're interested in the data collected so far click

Ben Thompson 3 Jan 28, 2022
[SDM 2022] Towards Similarity-Aware Time-Series Classification

SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie

Daochen Zha 49 Dec 27, 2022