dEEpEst Posted July 28, 2019 Share Posted July 28, 2019 This is the hidden content, please Sign In or Sign Up ORBIT Blockchain Transactions Investigation Tool This is the hidden content, please Sign In or Sign Up This is the hidden content, please Sign In or Sign Up This is the hidden content, please Sign In or Sign Up Introduction Orbit is designed to explore network of a blockchain wallet by recursively crawling through transaction history. The data is rendered as a graph to reveal major sources, sinks and suspicious connections. Note: Orbit only runs on Python 3.2 and above. Usage Let's start by crawling transaction history of a wallet python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F Crawling multiple wallets is no different. python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F,1ETBbsHPvbydW7hGWXXKXZ3pxVh3VFoMaX Orbit fetches last 50 transactions from each wallet by default, but it can be tuned with -l option. python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F -l 100 Orbit's default crawling depth is 3 i.e. it fetches the history of target wallet(s), crawls the newly found wallets and then crawls the wallets in the result again. The crawling depth can be increased or decresead with -d option. python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F -d 2 Wallets that have made just a couple of interactions with our target may not be important, Orbit can be told to crawl top N wallets at each level by using the -t option. python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F -t 20 If you want to view the collected data with a graph viewer of your choice, you can use -o option. python3 orbit.py -s 1AJbsFZ64EpEfS5UAjAfcUG8pH8Jn3rn1F -o output.graphml Support Formats graphml (Supported by most graph viewers) json (For raw processing) This is your terminal dashboard. This is the hidden content, please Sign In or Sign Up Visualization Once the scan is complete, the graph will automatically open in your default browser. If it doesn't open, open quark.html manually. Don't worry if your graph looks messy like the one below or worse. This is the hidden content, please Sign In or Sign Up Select the Make Clusters option to form clusters using community detection algorithm. After that, you can use Color Clusters to give different colors to each community and then use Spacify option to fix overlapping nodes & edges. This is the hidden content, please Sign In or Sign Up The thickness of edges depends on the frequency of transactions between two wallets while the size of a node depends on both transaction frequency and the number of connections of the node. As Orbit uses This is the hidden content, please Sign In or Sign Up to render the graph, more information about the various features and controls is available in Quark's README. Download: This is the hidden content, please Sign In or Sign Up Link to comment Share on other sites More sharing options...
Recommended Posts