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Python Detection Engine: Authentication Log Analyzer

Project Overview

This project is a lightweight Detection Engine designed to automate the analysis of authentication logs. It simulates the core logic of a SIEM (Security Information and Event Management) system by parsing login metadata to identify potential brute-force attacks and segmenting traffic based on network origin.

Key Features Threshold-Based Alerting: Automatically categorizes security events into four threat levels (Low, Medium, High, Critical) based on failed attempt counts. Traffic Segmentation: Differentiates between Internal (Trusted) and External (Untrusted) IP addresses using prefix validation. Incident Response Trigger: Features a "Security Threshold" logic that flags the entire system for action if multiple high-risk events are detected in a single session.

Logic Matrix

The engine evaluates incoming log data against the following security thresholds:

Failed Attempts Threat Level Response Action
100+ CRITICAL Immediate System Shutdown / Lockout
20 - 99 HIGH Priority Admin Investigation
10 - 19 MEDIUM Suspicious Activity Flag
1 - 9 LOW Routine Monitoring
0 SAFE No Action Required

Technical Stack

  • Language: Python 3.x
  • Libraries: Standard Library (No external dependencies for easy deployment)

Usage

  1. Clone the repository:
    git clone [https://github.com/manisha2580/Python-Detection-Engine.git](https://github.com/manisha2580/Python-Detection-Engine.git)

About

A Python-based security logic engine that parses authentication metadata, categorizes threat levels based on login failure thresholds, and segments traffic origin (Internal vs. External) for automated incident response.

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