Quick Start

Create your first pipeline in minutes

Your First Pipeline

This guide walks you through creating a simple HTTP automation pipeline in IronBullet. You’ll learn the core workflow and be able to build more complex pipelines afterward.

Make sure you’ve installed IronBullet before continuing.

Understanding the Interface

When you launch IronBullet, you’ll see three main areas:

• Left Panel: Block palette with 50+ blocks organized by category
• Center Canvas: Visual pipeline editor where you drag and connect blocks
• Right Panel: Block configuration settings

Creating a Simple HTTP Pipeline

Let’s create a pipeline that makes an HTTP request and extracts data from the response.

1. Launch IronBullet

   Start the application:

   Windows: Double-click ironbullet.exe

   Linux: Run ./start.sh or ./ironbullet

2. Add an HTTP Request Block

   1. In the left panel, expand the HTTP category
   2. Drag the HTTP Request block onto the canvas
   3. Click the block to select it
   4. In the right panel, configure:
      • URL: https://api.github.com/users/octocat
      • Method: GET
      • User-Agent: IronBullet/0.2.3

   The variable input system supports three modes:

   • RAW: Use the literal value as-is
   • EMBED: Embed variables with <variable> or {{variable}} syntax
   • VAR: Reference a variable directly
3. Add a JSON Parser Block

   1. Expand the Parsing category in the left panel
   2. Drag a JSON parsing block onto the canvas
   3. Connect the HTTP Request block output to the JSON parser input
   4. Configure the JSON parser:
      • JSON Path: $.name (extracts the “name” field)
      • Variable Name: username
      • Input Source: Response body
4. Add a Log Block

   1. Expand the Utilities category
   2. Drag a Log block onto the canvas
   3. Connect the JSON parser output to the Log block
   4. Configure the log block:
      • Message: Found username: <username>
      • Log Level: INFO

   The <username> syntax will be replaced with the extracted variable.

Testing Your Pipeline

1. Enter Debug Mode

   Press F5 or click the Debug button in the toolbar.

   Debug mode allows you to test your pipeline with sample data before running it against full datasets.

2. View the Results

   The debugger panel will show:

   • HTTP request details (URL, headers, method)
   • Response status code and headers
   • Response body
   • Extracted variables
   • Log output

   You should see:

   Found username: The Octocat
   
3. Inspect Variables

   Open the Variables panel to see all extracted variables and their values:

   • username: “The Octocat”
   • Any other variables created during execution

Running Against Datasets

Once your pipeline works in debug mode, you can run it against full datasets.

1. Create a Job

   1. Click the Jobs button in the toolbar
   2. Click New Job
   3. Configure:
      • Name: “GitHub User Checker”
      • Pipeline: Select your current pipeline
      • Data Source: Choose a data file or enter test data
      • Threads: 5 (adjust based on your needs)
2. Add Input Data

   IronBullet supports multiple data formats:

   • List: One item per line
   • CSV: Comma-separated values with headers
   • JSON: Array of objects

   For this example, you could create a list of GitHub usernames:

   octocat
   torvalds
   gvanrossum
   

   Then modify your HTTP URL to use the input:

   https://api.github.com/users/<input>
   
3. Start the Job

   Click Start to begin execution.

   Monitor progress in the Jobs panel:

   • Items processed
   • Success/failure counts
   • Execution time
   • Results preview
4. Export Results

   After completion, export results in various formats:

   • CSV
   • JSON
   • TXT

   Results include all extracted variables and their values for each input.

Essential Keyboard Shortcuts

• F5: Debug current pipeline with test data
• Ctrl+S: Save pipeline
• Ctrl+N: New pipeline
• Ctrl+O: Open pipeline
• Delete: Remove selected block

Block Categories Overview

Now that you’ve created a basic pipeline, explore these block categories:

HTTP

Make HTTP/HTTPS requests with full control over:

• Methods (GET, POST, PUT, DELETE, PATCH, etc.)
• Headers and cookies
• Authentication (Basic, Bearer, custom)
• Request bodies (JSON, form data, raw)
• Proxy support

Parsing

Extract data from responses:

• JSON: JSONPath expressions
• Regex: Pattern matching with capture groups
• CSS Selector: Query HTML with CSS selectors
• XPath: XML/HTML querying

Functions

Transform and manipulate data:

• String: Concatenate, substring, replace, encode/decode
• List: Split, join, filter, map
• Crypto: Hash (MD5, SHA1, SHA256), HMAC, AES encryption
• Math: Arithmetic operations, random numbers
• Time: Date/time parsing, formatting, timezone conversion

Control Flow

Build complex logic:

• IfElse: Conditional branching
• Loop: Iterate over lists or ranges
• Set Variable: Create and update variables
• Delay: Add pauses between requests

Browser Automation

Control browsers with Selenium:

• Navigate to URLs
• Click elements, fill forms
• Execute JavaScript
• Take screenshots
• Handle popups and frames

Protocols

Work with other protocols:

• TCP/UDP: Raw socket communication
• FTP: File transfers
• SSH: Remote command execution
• IMAP/SMTP: Email automation

Bypass

Handle anti-automation measures:

• Captcha: Integration with solving services
• Cloudflare: Bypass Cloudflare protection
• CSRF Token: Extract and use CSRF tokens

Utilities

• Log: Debug output
• Script: Execute custom JavaScript/Python
• Plugin: Load external plugins

Advanced Features

Variable System

IronBullet supports two variable syntaxes:

<variable>     # Angle bracket syntax
{{variable}}   # Double curly brace syntax

Use variables in:

• URLs: https://api.example.com/users/<userId>
• Headers: Authorization: Bearer <token>
• Request bodies: {"username": "<username>"}
• Log messages: User <username> logged in

Proxy Rotation

Configure proxy lists with automatic rotation:

1. Add proxies in the Data/Proxy panel
2. Enable proxy rotation in HTTP blocks
3. IronBullet handles ban detection and health checking

Export as Code

Export your pipeline as standalone Rust code:

1. Click Export in the toolbar
2. Select Export as Rust Code
3. Customize and compile the generated code

Import OpenBullet Configs

Migrate from OpenBullet:

1. Click Import in the toolbar
2. Select your OpenBullet config (.svb, .opk, or .loliScript)
3. IronBullet will convert it to blocks automatically

Some OpenBullet features may require manual adjustments after import.

Example: Login Flow

Here’s a more complex example showing a multi-step authentication flow:

1. Get CSRF Token

   1. HTTP GET to login page
   2. CSS Selector to extract CSRF token from form
   3. Store in csrf_token variable
2. Submit Login

   1. HTTP POST to login endpoint
   2. Request body:
      {
        "username": "<input.username>",
        "password": "<input.password>",
        "csrf_token": "<csrf_token>"
      }
      
   3. Parse response for session cookie
3. Verify Login

   1. HTTP GET to protected page
   2. Check for success indicators
   3. Log result: Login <status> for <input.username>

Troubleshooting

Pipeline Not Executing

• Check that all blocks are connected properly
• Verify input data is in the correct format
• Look for error messages in the debugger panel

Variables Not Resolving

• Ensure variable names match exactly (case-sensitive)
• Check that variables are created before they’re used
• Use the Variables panel to see all available variables

HTTP Requests Failing

• Verify the URL is correct and accessible
• Check headers and authentication
• Review proxy settings if using proxies
• Use the Network panel to inspect full request/response details

Next Steps

Block Reference

Explore all 50+ blocks and their configuration options

Variable System

Master the variable input system and data flow

Jobs & Execution

Learn advanced job configuration and optimization

Plugins

Extend IronBullet with custom plugins

Join the community on GitHub to share pipelines, get help, and request features: github.com/ZeraTS/ironbullet