niherhalder/AI_Log_Analyzer

# AI Log Analyzer AI-powered cybersecurity log analysis tool developed in Python for detecting suspicious activities, analyzing security events, and generating automated SOC-style incident reports. ## Project Overview This project simulates a lightweight Security Operations Center (SOC) log monitoring workflow. The tool is designed for: - Security monitoring practice - Threat detection automation - SOC analyst portfolio demonstration - Basic incident investigation workflows - Python-based cybersecurity automation ## Features - Automated log file analysis - Suspicious activity detection - Severity classification - Security event counting - Risk level estimation - Automated report generation - SOC-style reporting workflow - Simple and lightweight Python implementation ## Severity Levels Detected The analyzer detects and counts the following log severity levels: - INFO - WARNING - ERROR - FAILED ## Technologies Used - Python - File Handling - String Processing - Log Parsing - Cybersecurity Automation - Security Log Analysis ## Project Structure AI_Log_Analyzer/ │ ├── screenshots/ │ ├── project_folder.png │ ├── report.png │ └── terminal_execution.png │ ├── README.md ├── requirements.txt ├── log_analyzer.py ├── sample_logs.txt └── analysis_report.txt ## Installation Install required libraries: pip install -r requirements.txt ## Run the Project python log_analyzer.py ## Output The analyzer generates: analysis_report.txt The report includes: - Total log entries analyzed - Severity count - Suspicious event summary - Risk level assessment - Security analysis summary ## Example Detection Scenarios The tool can identify: - Failed login attempts - Suspicious warning patterns - Error-based security events - Possible unauthorized access indicators - Repeated abnormal log events ## Screenshots Project screenshots are available in the `screenshots` folder. Included screenshots: - Project folder structure - Terminal execution - Generated analysis report ## Cybersecurity Focus This project demonstrates practical skills related to: - SOC operations - Log investigation - Threat detection - Security monitoring - Incident analysis - Security automation - Detection engineering foundations ## Future Improvements Planned enhancements: - AI-generated incident explanation - Real-time log monitoring - Threat scoring system - Email alert integration - Dashboard visualization - SIEM integration simulation - CSV/XLSX export support ## Version Current Version: `v1.0` ### v1.0 Features - Log file analysis - Severity counting - Suspicious event detection - Risk level estimation - Automated report generation - Screenshot documentation ## Author Niher Halder Cybersecurity Engineer | Threat Modeling & Detection Analytics | Security Automation