Overview
I have developed an Instacheck clone for all of us Mac and Linux users. It is written in node.js and you guessed it - the data is displayed in the web browser. This means you can actually capture the packets on a different computer than you use and see the results via web interface. I am currently running the program on my raspberry pi
Screenshot.
Prerequisites
I don't have any 1-click installers though - you need to be a hobbyist to get it running.
First you need to install required dependencies: C compiler, node.js, npm and libpcap-dev. Maybe git.
On Mac, you should first install Xcode to get a compiler. Pcap files are already on your computer. Node.js can be installed any way - I used homebrew.
On Linux, instructions vary depending on your distro. Raspberry Pi has its own version of Node.js build for ARM computers. On Mac, just navigate to System Preferences -> Shares. There is one-click Internet sharing given that you have two Internet connections on your computer.
Then, you need to be able to route the 3DS wireless traffic via your computer. Basically, you need to be able to create a wireless hotspot on your computer and still be connected to Internet. This should be very simple on Mac OSX and Ubuntu at least.
Installing
Get the program from https://github.com/lamperi/pokemon-pcap and initialize its dependencies with npm install. Edit config.json to have your 3DS Mac address and legal setuid user and setgid group, as well as the network interface. On my raspberry pi, wlan0 is a possible choice for interface. Mac uses most likely en0 or en1, depending on whether you have Macbook Air or some other model.
Finally run the program with sudo node main.js. Unfortunately sudo must be used to start the packet capturing on the network device, but the code tries to drop sudo privileges pretty quickly.
If anybody manages or even wants to run it, I am eager to help by answering question or providing support.
Resources
Current issues
I have developed an Instacheck clone for all of us Mac and Linux users. It is written in node.js and you guessed it - the data is displayed in the web browser. This means you can actually capture the packets on a different computer than you use and see the results via web interface. I am currently running the program on my raspberry pi
Screenshot.
Prerequisites
I don't have any 1-click installers though - you need to be a hobbyist to get it running.
First you need to install required dependencies: C compiler, node.js, npm and libpcap-dev. Maybe git.
On Mac, you should first install Xcode to get a compiler. Pcap files are already on your computer. Node.js can be installed any way - I used homebrew.
On Linux, instructions vary depending on your distro. Raspberry Pi has its own version of Node.js build for ARM computers. On Mac, just navigate to System Preferences -> Shares. There is one-click Internet sharing given that you have two Internet connections on your computer.
Then, you need to be able to route the 3DS wireless traffic via your computer. Basically, you need to be able to create a wireless hotspot on your computer and still be connected to Internet. This should be very simple on Mac OSX and Ubuntu at least.
Installing
Get the program from https://github.com/lamperi/pokemon-pcap and initialize its dependencies with npm install. Edit config.json to have your 3DS Mac address and legal setuid user and setgid group, as well as the network interface. On my raspberry pi, wlan0 is a possible choice for interface. Mac uses most likely en0 or en1, depending on whether you have Macbook Air or some other model.
Finally run the program with sudo node main.js. Unfortunately sudo must be used to start the packet capturing on the network device, but the code tries to drop sudo privileges pretty quickly.
If anybody manages or even wants to run it, I am eager to help by answering question or providing support.
Resources
Current issues
- Does not export to CSV
- Difficult to setup
- UI to scale better on lower resolutions
- Improve UI other ways
- Publish the NPM package?
- Instructions on how to setup on Raspberry Pi and Macbook Air
Last edited: