AI Security SOC Agent

An AI Agent system automatic analyzes server logs, rates security threats by LLM AP, automatic problem responses (SOAR) and send real-time alerts via a Telegram Bot.

The project is performance-optimized using Multi-threading to process large log files concurrently.

---

Features

• Automated Log Parsing**: Reads and extracts essential log data (IP, Port, Failed logins).
• AI-Powered Threat Analysis**: Utilizes Gemini 3.5 Flash to evaluate attack contexts, assess threat risk levels (Low/Medium/High/Critical), and recommend immediate remadiation steps for system administrators.
• Multi-threaded Execution**: Employs concurrent.futures.ThreadPoolExecutor to process multiple high-risk IPs concurrently, significantly cutting down API wait times.
• SOAR Active Response**: Automatically extracts and appends policy-violating IP addresses to a local blacklist blacklisted_ips.txt.
• Real-time Telegram Alerting**: Connects with the Telegram Bot API to deliver imediate push notifications to SOC Analysts upon dectecting threats.
• Security Best Practices**: Manages sensitive credentials (API Keys and Bot Tokens) securely via environment variables ('.env') to prevent secret exposure on public repositories.

System Architecture & Workflow

[ Server Logs ] 
       │
       ▼
[ Log Parser & Threat Detection ] ──(Safe IP)──► [ Pass / Ignore ]
       │
 (Suspicious IP)
       │
       ├──────────────────────────────────────────┐
       ▼                                          ▼
[ Multi-threaded Worker Pool ]          [ Local Blacklist ]
       │                           (Save to blacklisted_ips.txt)
       ▼
[ Gemini AI Analysis Engine ]
       │
       ▼
[ Telegram Bot Notification ] ──► 🚨 Real-time Alert to Telegram

Getting Started

1.Prerequisites

• Python 3.9+
• A Telegram Account (with a Bot created via @BotFather)
• A Google Gemini API Key

2.Installation

1. Clone the repository:

   git clone [https://github.com/dungpmuit/Lab_ai-log-analyzer.git](https://github.com/dungpmuit/Lab_ai-log-analyzer.git)
   cd Lab_ai-log-analyzer

2. Create and activate a Virtual Environment:

   python3 -m venv .venv
   source .venv/bin/activate

3. Install required dependencies:

   pip install -r requirements.txt

Configuration

• Create a .env file in the root directory of the project and populate it with your secret keys:

  GEMINI_API_KEY=your_gemini_api_key_here
  TELEGRAM_BOT_TOKEN=your_telegram_bot_token_here
  TELEGRAM_CHAT_ID=your_telegram_chat_id_here

Usage

1. Add or edit log entries in server_logs.txt:

192.168.1.10,80,0
10.0.0.15,22,5
172.16.0.4,443,1

2. Run the AI SOC Agent:

python3 log_file_analyzer.py

Project Structure

Lab_ai-log-analyzer/
├── .env                  # Environment variables (Excluded from Git)
├── .gitignore            # Git ignore configuration
├── log_file_analyzer.py  # Core script for AI SOC Agent
├── server_logs.txt       # Sample input log file
├── blacklisted_ips.txt   # Output file containing blocked IP addresses
├── requirements.txt      # Python dependencies list
└── README.md             # Project documentation
```

Author

• Dung Pham Minh
• Github: @dungpmuit