https://github.com/s0md3v/Orbit

Blockchain Transactions Investigation Tool
https://github.com/s0md3v/Orbit

bitcoin blockchain osint

Last synced: 11 days ago
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Blockchain Transactions Investigation Tool

• Host: GitHub
• URL: https://github.com/s0md3v/Orbit
• Owner: s0md3v
• License: gpl-3.0
• Created: 2018-07-10T14:38:34.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-07-15T09:47:59.000Z (over 2 years ago)
• Last Synced: 2024-10-28T20:45:32.200Z (11 days ago)
• Topics: bitcoin, blockchain, osint
• Language: Python
• Homepage:
• Size: 56.6 KB
• Stars: 526
• Watchers: 34
• Forks: 154
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


  

  


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Blockchain Transactions Investigation Tool



  

    

  

  

      

  

  



![graph-demo](https://i.ibb.co/rx76Ryt/Screenshot-2019-07-26-03-41-34.png)

### 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.

![demo-terminal](https://i.ibb.co/pZG24vT/Screenshot-2019-07-26-08-07-10.png)

### 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.

![graph-setup](https://i.ibb.co/xJ38DF9/Screenshot-2019-07-26-08-21-18.png)

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.

![graph-fixed](https://i.ibb.co/SsGhkJN/Screenshot-2019-07-26-09-21-08.png)

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 ![Quark](https://github.com/s0md3v/Quark) to render the graph, more information about the various features and controls is available in Quark's README.