Avahi Integration and Network Connection

Project Description

This project aims to integrate Avahi service on a Linux server to manage and control network connections between mobile devices and televisions. The goal is to establish a 1-to-1 connection between specific mobile devices on the 192.168.10.x network and TVs on the 192.168.20.x network, acting as a controlled intermediary.

Why Start This Project?

The project is initiated to address the challenges of uncontrolled network connections facilitated by Avahi. By creating a custom C/C++ program, we aim to restrict and secure connections between mobile and TV networks, allowing specific devices to connect only to designated TVs.

Goal for this Hackweek

The primary objective for this Hackweek is to develop and implement the C/C++ program that will interface with Avahi, handling mDNS queries and unicast responses. We intend to demonstrate the controlled forwarding of packets between networks, achieving the goal of establishing a secure 1-to-1 connection.

To be more specific: For this hackweed we want to achieve

  • successfully install avahi on the system
  • check /usr/include > cd avahi- avahi-client/ avahi-common/ avahi-compat-libdns_sd/ avahi-core/ avahi-libevent/
  • use sudo zypper install avahi-compat-libdns_sd-devel
  • run using gcc -o avahiexample avahiexample.c -lavahi-client -lavahi-common ./avahi_example
  • output finally > avahi-browse -a

Resources

Other Resources

Keywords

  • Avahi
  • Network Connection
  • mDNS
  • Linux
  • C/C++ Programming
  • Hackweek
  • Network Security
  • Integration

Looking for hackers with the skills:

c c++ avahi linux tumbleweed suse github

This project is part of:

Hack Week 23

Activity

  • about 1 year ago: renxt0310 liked this project.
  • about 1 year ago: vojha added keyword "c" to this project.
  • about 1 year ago: vojha added keyword "c++" to this project.
  • about 1 year ago: vojha added keyword "avahi" to this project.
  • about 1 year ago: vojha added keyword "linux" to this project.
  • about 1 year ago: vojha added keyword "tumbleweed" to this project.
  • about 1 year ago: vojha added keyword "suse" to this project.
  • about 1 year ago: vojha added keyword "github" to this project.
  • about 1 year ago: vojha liked this project.
  • about 1 year ago: vojha started this project.
  • about 1 year ago: vojha originated this project.

  • Comments

    • vojha
      about 1 year ago by vojha | Reply

      Scenario Overview

      This scenario involves establishing a 1-to-1 connection between mobile devices (192.168.10.x network) and televisions (192.168.20.x network) through a Linux server acting as an intermediary. The goal is to allow specific mobile devices to discover and connect only to certain TVs, creating a controlled connection process between networks.

      Problem and Objective

      Avahi Disabled Scenario

      When Avahi is disabled: - Mobile devices on the 192.168.10.x network cannot discover any TVs on the 192.168.20.x network.

      Avahi Enabled Scenario

      When Avahi is enabled: - All mobile devices can discover all TVs, allowing connections between any mobile and TV on the network.

      Proposed Solution and Process

      Create a C/C++ Program

      The program will interface with Avahi, handling the detection and communication between mobile and TV networks. It identifies the source (mobile) and target (TV) IP addresses and manages mDNS queries.

      Purpose of the C/C++ Program

      When Avahi is disabled, the program will handle and manipulate mDNS queries, allowing a 1-to-1 connection. The program ensures controlled forwarding of packets between networks, establishing specific connections between mobile devices and TVs.

      Steps to Implement

      1. Install and start the Avahi service.
      2. Create the C/C++ program to handle mDNS queries and unicast responses between the mobile and TV networks. The program will act as a proxy server, forwarding and restricting packets between the specified mobile and TV.

      Testing Procedure

      Validate the C program's functionality by sending mDNS queries from mobile devices and forwarding them to the TV network. Test and confirm that the forwarded responses are unicast and specific to the intended mobile device.

      Desired Outcomes & Future Works

      The desired outcome is to establish controlled 1-to-1 connections between specific mobile devices and TVs without Avahi automatically forwarding mDNS packets. This will ensure a restricted and secure network connection, allowing specific mobile devices to connect only to certain TVs.

      Note: Ensure that Avahi doesn't automatically forward packets unless the integration program is actively running.

      Result and Outcome

      I was able to run a simple service publication.

      Service Publication

      Publishes a service named "MyService" of type "example.tcp" on all network interfaces and protocols (IPv4 and IPv6) on port 12345. This service can be discovered on the local network.

      Output

      The output indicates the successful publication of the service. When the service is successfully published, the entry_group_callback function is called, and it prints: "Service 'MyService' successfully published."

      To run the C program, use the following example:

      ```bash gcc -o avahiintegration avahiintegration.c -lavahi-client -lavahi-common ./avahi_integration There are .sh files to install Avahi on Ubuntu, stop and start the daemon services as well, which makes life easier when testing different scenarios.

      Output En02 smart_tv found.

      bash Copy code $ ./avahiintegration Resolved service: Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa, _googlecast.tcp, local, a56831aa-ef2a-1db0-9c3f-d6b56ff217fa.local:8009 Resolved service: Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa, googlecast.tcp, local, a56831aa-ef2a-1db0-9c3f-d6b56ff217fa.local:8009 ^C In another tab:

      bash Copy code avahi-browse -a Output:

      bash Copy code eno2 IPv6 Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa googlecast.tcp local eno2 IPv4 Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa googlecast.tcp local eno1 IPv4 dap2230 Web Site local eno2 IPv6 Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa googlecast.tcp local eno2 IPv6 Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa googlecast.tcp local eno2 IPv4 Smart-2K-ATV4-a56831aaef2a1db09c3fd6b56ff217fa googlecast.tcp local Client failure, exiting: Daemon connection failed. The message appeared when we stopped the Avahi daemon using sudo systemctl stop avahi-daemon. Note that the ./avahi_integration ELF file was running in another tab, and nothing happened.

    • vojha
      about 1 year ago by vojha | Reply

      Avahi Integration and Network Connection README

      What is Avahi?

      Avahi is a system that facilitates service discovery on a local network. It implements Zeroconf networking specifications, including mDNS (multicast Domain Name System) and DNS-SD (DNS-based Service Discovery). Avahi enables devices to automatically discover and utilize services on the local network without requiring manual configuration.

      For more information, visit the Avahi website.

      Run in SUSE Linux OpenSUSE Tumbleweed

      The Avahi files were successfully installed on the system, and the following steps were performed:

      ```bash cd /usr/include/avahi- avahi-client/ avahi-common/ avahi-compat-libdns_sd/ avahi-core/ avahi-libevent/ To compile and run the example program:

      bash Copy code gcc -o avahiexample avahiexample.c -lavahi-client -lavahi-common ./avahi_example To browse services:

      bash Copy code avahi-browse -a

    • vojha
      about 1 year ago by vojha | Reply

      All the programs and shell scripts

      Everything is posted in github, feel free to check the codes and implement the same at your end. See you in next Hackweek

      https://github.com/varunkojha/avahi-c

      Desired Outcomes & Future Works

      The desired outcome is to establish controlled 1-to-1 connections between specific mobile devices and TVs without Avahi automatically forwarding mDNS packets. This will ensure a restricted and secure network connection, allowing specific mobile devices to connect only to certain TVs.

    • vojha
      about 1 year ago by vojha | Reply

      GitHub Code add-emoji

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    We are currently at GHC-9.8.x, which a bit old. So I'd like to take a shot at the latest version of the compiler, GHC-9.10.x. This is gonna be interesting because the new version requires major updates to all kinds of libraries and base packages, which typically means patching lots of packages to make them build again.

    Goals

    Have working builds of GHC-9.10.x and the required Haskell packages in 'devel:languages:haskell` so that we can compile:

    • git-annex
    • pandoc
    • xmonad
    • cabal-install

    Resources

    • https://build.opensuse.org/project/show/devel:languages:haskell/
    • https://github.com/opensuse-haskell/configuration/
    • #discuss-haskell
    • https://www.twitch.tv/peti343


    Tumbleweed on Mars-CM (RISC-V board) by ph03nix

    RISC-V is awesome, Tumbleweed is awesome, chocolate cake is awesome. I'm planning to combine all of them in one project.

    Project Description

    I recently purchased a MILK-V Mars CM and managed to setup it up already using Debian Linux. My project for this Hackweek is to see how far I can get to run Tumbleweed on this compute module board.

    Goal for this Hackweek

    • Run Tumbleweed on the Compute Module

    Resources

    • http://milkv.io/mars-cm
    • https://en.opensuse.org/HCL:VisionFive2


    SUSE AI Meets the Game Board by moio

    Use tabletopgames.ai’s open source TAG and PyTAG frameworks to apply Statistical Forward Planning and Deep Reinforcement Learning to two board games of our own design. On an all-green, all-open source, all-AWS stack!
    A chameleon playing chess in a train car, as a metaphor of SUSE AI applied to games


    Results: Infrastructure Achievements

    We successfully built and automated a containerized stack to support our AI experiments. This included:

    A screenshot of k9s and nvtop showing PyTAG running in Kubernetes with GPU acceleration

    ./deploy.sh and voilà - Kubernetes running PyTAG (k9s, above) with GPU acceleration (nvtop, below)

    Results: Game Design Insights

    Our project focused on modeling and analyzing two card games of our own design within the TAG framework:

    • Game Modeling: We implemented models for Dario's "Bamboo" and Silvio's "Totoro" and "R3" games, enabling AI agents to play thousands of games ...in minutes!
    • AI-driven optimization: By analyzing statistical data on moves, strategies, and outcomes, we iteratively tweaked the game mechanics and rules to achieve better balance and player engagement.
    • Advanced analytics: Leveraging AI agents with Monte Carlo Tree Search (MCTS) and random action selection, we compared performance metrics to identify optimal strategies and uncover opportunities for game refinement .

    Cards from the three games

    A family picture of our card games in progress. From the top: Bamboo, Totoro, R3

    Results: Learning, Collaboration, and Innovation

    Beyond technical accomplishments, the project showcased innovative approaches to coding, learning, and teamwork:

    • "Trio programming" with AI assistance: Our "trio programming" approach—two developers and GitHub Copilot—was a standout success, especially in handling slightly-repetitive but not-quite-exactly-copypaste tasks. Java as a language tends to be verbose and we found it to be fitting particularly well.
    • AI tools for reporting and documentation: We extensively used AI chatbots to streamline writing and reporting. (Including writing this report! ...but this note was added manually during edit!)
    • GPU compute expertise: Overcoming challenges with CUDA drivers and cloud infrastructure deepened our understanding of GPU-accelerated workloads in the open-source ecosystem.
    • Game design as a learning platform: By blending AI techniques with creative game design, we learned not only about AI strategies but also about making games fun, engaging, and balanced.

    Last but not least we had a lot of fun! ...and this was definitely not a chatbot generated line!

    The Context: AI + Board Games