/BruteForceAI

Advanced LLM-powered brute-force tool combining AI intelligence with automated login attacks

Primary LanguagePythonOtherNOASSERTION

🤖 BruteForceAI - AI-Powered Login Brute Force Tool

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BruteForceAI Banner Python License AI Powered

Advanced LLM-powered brute-force tool combining AI intelligence with automated login attacks

Features • Installation • Usage • Examples • Configuration • License

🎯 About

BruteForceAI is an advanced penetration testing tool that revolutionizes traditional brute-force attacks by integrating Large Language Models (LLM) for intelligent form analysis. The tool automatically identifies login form selectors using AI, then executes sophisticated multi-threaded attacks with human-like behavior patterns.

🧠 LLM-Powered Form Analysis

  • Stage 1 (AI Analysis): LLM analyzes HTML content to identify login form elements and selectors
  • Stage 2 (Smart Attack): Executes intelligent brute-force attacks using AI-discovered selectors

🚀 Advanced Attack Features

  • Multi-threaded execution with synchronized delays
  • Bruteforce & Password Spray attack modes
  • Human-like timing with jitter and randomization
  • User-Agent rotation for better evasion
  • Webhook notifications (Discord, Slack, Teams, Telegram)
  • Comprehensive logging with SQLite database

🌟 Star History

Star History Chart

✨ Features

🔍 Intelligent Analysis

  • LLM-powered form selector identification (Ollama/Groq)
  • Automatic retry with feedback learning
  • DOM change detection for success validation
  • Smart HTML content extraction

⚡ Advanced Attacks

  • Bruteforce Mode: Try all username/password combinations
  • Password Spray Mode: Test each password against all usernames
  • Multi-threaded execution (1-100+ threads)
  • Synchronized delays between attempts for same user

🎭 Evasion Techniques

  • Random User-Agent rotation
  • Configurable delays with jitter
  • Human-like timing patterns
  • Proxy support
  • Browser visibility control

📊 Monitoring & Notifications

  • Real-time webhook notifications on success
  • Comprehensive SQLite logging
  • Verbose timestamped output
  • Success exit after first valid credentials
  • Skip existing attempts (duplicate prevention)

🛠️ Operational Features

  • Output capture to files
  • Colorful terminal interface
  • Network error retry mechanism
  • Force retry existing attempts
  • Database management tools
  • Automatic update checking from mordavid.com

🔧 Installation

Prerequisites

# Python 3.8 or higher
python --version

# Install Playwright browsers
playwright install chromium

Install Dependencies

pip install -r requirements.txt

Required packages:

  • playwright - Browser automation
  • requests - HTTP requests
  • PyYAML - YAML parsing for update checks

LLM Setup

Option 1: Ollama (Local)

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Pull recommended model
ollama pull llama3.2:3b

Option 2: Groq (Cloud)

  1. Get API key from Groq Console
  2. Use with --llm-provider groq --llm-api-key YOUR_KEY

🧠 Model Selection & Performance

Recommended Models by Provider

Ollama (Local):

  • llama3.2:3b - Default, good balance of speed and quality
  • llama3.2:1b - Fastest, smaller model for quick analysis
  • qwen2.5:3b - Alternative with good performance

Groq (Cloud):

  • llama-3.3-70b-versatile - Default & Best - Latest model with superior quality (1 attempt)
  • llama3-70b-8192 - Fast and reliable alternative (1 attempt)
  • gemma2-9b-it - Lightweight option, good for simple forms (1 attempt)
  • llama-3.1-8b-instant - ⚠️ Not recommended (rate limiting issues, 3+ attempts)

Performance Tips

# Best quality (recommended for complex forms)
python main.py analyze --urls targets.txt --llm-provider groq --llm-model llama-3.3-70b-versatile --llm-api-key YOUR_KEY

# Fast and reliable
python main.py analyze --urls targets.txt --llm-provider groq --llm-model llama3-70b-8192 --llm-api-key YOUR_KEY

# Lightweight for simple forms
python main.py analyze --urls targets.txt --llm-provider groq --llm-model gemma2-9b-it --llm-api-key YOUR_KEY

# Local processing (no API key needed)
python main.py analyze --urls targets.txt --llm-provider ollama --llm-model llama3.2:3b

📖 Usage

Basic Commands

Stage 1: Analyze Login Forms

python main.py analyze --urls urls.txt --llm-provider ollama

Stage 2: Execute Attack

python main.py attack --urls urls.txt --usernames users.txt --passwords passwords.txt --threads 10

Command Structure

python main.py <command> [options]

Available Commands

  • analyze - Analyze login forms with LLM
  • attack - Execute brute-force attacks
  • clean-db - Clean database tables
  • check-updates - Check for software updates

🎯 Examples

1. Complete Workflow

# Step 1: Analyze forms
python main.py analyze --urls targets.txt --llm-provider ollama --llm-model llama3.2:3b

# Step 2: Attack with 20 threads
python main.py attack --urls targets.txt --usernames users.txt --passwords passwords.txt --threads 20 --delay 5 --jitter 2

2. Advanced Attack Configuration

python main.py attack \
  --urls targets.txt \
  --usernames users.txt \
  --passwords passwords.txt \
  --mode passwordspray \
  --threads 15 \
  --delay 10 \
  --jitter 3 \
  --success-exit \
  --user-agents user_agents.txt \
  --verbose \
  --output results.txt

3. With Webhook Notifications

python main.py attack \
  --urls targets.txt \
  --usernames users.txt \
  --passwords passwords.txt \
  --discord-webhook "https://discord.com/api/webhooks/..." \
  --slack-webhook "https://hooks.slack.com/services/..." \
  --threads 10

4. Browser Debugging

python main.py analyze \
  --urls targets.txt \
  --show-browser \
  --browser-wait 5 \
  --debug \
  --llm-provider ollama

5. Check for Updates

# Check for software updates
python main.py check-updates

# Check with output to file
python main.py check-updates --output update_check.txt

Manual Check (Detailed)

# Check for updates manually (same as automatic but can save to file)
python main.py check-updates

# Check with output to file
python main.py check-updates --output update_check.txt

Skip Version Check

# Skip version check completely for faster startup
python main.py analyze --urls targets.txt --skip-version-check
python main.py attack --urls targets.txt --usernames users.txt --passwords passwords.txt --skip-version-check

# Also works as global flag (before subcommand)
python main.py --skip-version-check analyze --urls targets.txt

⚙️ Configuration Options

Analysis Options

Parameter Description Default
--llm-provider LLM provider (ollama/groq) ollama
--llm-model Model name llama3.2:3b (ollama), llama-3.3-70b-versatile (groq)
--llm-api-key API key for Groq None
--selector-retry Retry attempts for selectors 10
--force-reanalyze Force re-analysis False

Attack Options

Parameter Description Default
--mode Attack mode (bruteforce/passwordspray) bruteforce
--threads Number of threads 1
--delay Delay between attempts (seconds) 0
--jitter Random jitter (seconds) 0
--success-exit Stop after first success False
--force-retry Retry existing attempts False

Detection Options

Parameter Description Default
--dom-threshold DOM difference threshold 100
--retry-attempts Network retry attempts 3

Evasion Options

Parameter Description Default
--user-agents User-Agent file None
--proxy Proxy server None
--show-browser Show browser window False
--browser-wait Wait time when visible 0

Output Options

Parameter Description Default
--verbose Detailed timestamps False
--debug Debug information False
--output Save output to file None
--no-color Disable colors False

Webhook Options

Parameter Description
--discord-webhook Discord webhook URL
--slack-webhook Slack webhook URL
--teams-webhook Teams webhook URL
--telegram-webhook Telegram bot token
--telegram-chat-id Telegram chat ID

🔄 Update Management

BruteForceAI includes simple update checking to keep you informed about new releases.

Automatic Check

  • Checks for updates every time the tool starts
  • Shows one-line status: either "✅ up to date" or "🔄 Update available"
  • Quick 3-second timeout - no delays
  • Silent network failure (no error messages)
  • Skip with: --skip-version-check flag

Manual Check (Detailed)

# Check for updates manually (same as automatic but can save to file)
python main.py check-updates

# Check with output to file
python main.py check-updates --output update_check.txt

Update Information

  • Up to date: ✅ BruteForceAI v1.0.0 is up to date
  • Update available: 🔄 Update available: v1.0.0 → v1.1.0 | Download: https://github.com/...

Performance

  • Timeout: 3 seconds maximum
  • No delays: Instant if network unavailable
  • No spam: One simple line per check

Version Source

Updates are checked against: https://mordavid.com/md_versions.yaml

🗄️ Database Schema

BruteForceAI uses SQLite database (bruteforce.db) with two main tables:

form_analysis

Stores LLM analysis results for each URL.

brute_force_attempts

Logs all attack attempts with results and metadata.

Database Management

# Clean all data
python main.py clean-db

# View database
sqlite3 bruteforce.db
.tables
.schema

🔔 Webhook Integration

Discord Setup

  1. Create webhook in Discord server settings
  2. Use webhook URL with --discord-webhook

Slack Setup

  1. Create Slack app with incoming webhooks
  2. Use webhook URL with --slack-webhook

Teams Setup

  1. Add "Incoming Webhook" connector to Teams channel
  2. Use webhook URL with --teams-webhook

Telegram Setup

  1. Create bot with @BotFather
  2. Get bot token and chat ID
  3. Use --telegram-webhook TOKEN --telegram-chat-id CHAT_ID

⚠️ Legal Disclaimer

FOR EDUCATIONAL AND AUTHORIZED TESTING ONLY

This tool is designed for:

  • ✅ Authorized penetration testing
  • ✅ Security research and education
  • ✅ Testing your own applications
  • ✅ Bug bounty programs with proper scope

DO NOT USE FOR:

  • ❌ Unauthorized access to systems
  • ❌ Illegal activities
  • ❌ Attacking systems without permission

Users are responsible for complying with all applicable laws and regulations. The author assumes no liability for misuse of this tool.

📋 Changelog

v1.0.0 (Current)

  • ✨ Initial release
  • 🧠 LLM-powered form analysis
  • ⚡ Multi-threaded attacks
  • 🎭 Advanced evasion techniques
  • 🔔 Webhook notifications
  • 📊 Comprehensive logging
  • 🔄 Automatic update checking

👨‍💻 About the Author

Mor David - Offensive Security Specialist & AI Security Researcher

I specialize in offensive security with a focus on integrating Artificial Intelligence and Large Language Models (LLM) into penetration testing workflows. My expertise combines traditional red team techniques with cutting-edge AI technologies to develop next-generation security tools.

🔗 Connect with Me

🛡️ RootSec Community

Join our cybersecurity community for the latest in offensive security, AI integration, and advanced penetration testing techniques:

🔗 t.me/root_sec

RootSec is a community of security professionals, researchers, and enthusiasts sharing knowledge about:

  • Advanced penetration testing techniques
  • AI-powered security tools
  • Red team methodologies
  • Security research and development
  • Industry insights and discussions

📄 License

This project is licensed under the Non-Commercial License.

Terms Summary:

  • ✅ Permitted: Personal use, education, research, authorized testing
  • ❌ Prohibited: Commercial use, redistribution for profit, unauthorized attacks
  • 📋 Requirements: Attribution, same license for derivatives

See the LICENSE.md file for complete terms and conditions.

🙏 Acknowledgments

  • Playwright Team - For the excellent browser automation framework
  • Ollama Project - For making local LLM deployment accessible
  • Groq - For high-performance LLM inference
  • Security Community - For continuous feedback and improvements

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