Agentic AI Security Operations Platform

An Agentic AI-powered Security Operations Platform that automates security investigations through a coordinated multi-agent workflow. The platform combines threat detection, threat intelligence enrichment, MITRE ATT&CK mapping, case management, FastAPI services, and a React dashboard to help analysts investigate and prioritize security incidents.

The project demonstrates practical implementation of Agentic AI architectures, Model Context Protocol (MCP), Pydantic AI, multi-agent systems, and security automation within a modern Security Operations Center (SOC) environment.

Key Features

Agentic AI Investigation Workflow

Security incidents are processed through a coordinated multi-agent pipeline where each agent performs a specialized security function before passing context to the next stage.

Agents include:

• Log Collection Agent

• Detection Agent

• MITRE ATT&CK Agent

• Threat Intelligence Agent

• Correlation Agent

• Severity Escalation Agent

• Case Management Agent

• Investigation Agent

The workflow produces structured investigation outputs containing threat intelligence enrichment, MITRE ATT&CK mappings, escalation decisions, and analyst recommendations.

Threat Intelligence Enrichment

• IP Reputation Analysis

• Geographic Attribution

• Threat Scoring

• Risk Prioritization

• Security Context Enrichment

MITRE ATT&CK Integration

The platform maps security events to MITRE ATT&CK techniques and tactics, helping analysts understand attacker behavior and investigation priorities.

Case Management

• Case Creation

• Case Search

• Analyst Notes

• Investigation Updates

• Escalation Decisions

• Severity Tracking

• Investigation History

Security Monitoring Dashboard

• Security Overview Metrics

• Incident Tracking

• AI Escalated Cases

• Threat Intelligence Panel

• MITRE ATT&CK Context

• Executive Dashboard

• Threat Hunting Workspace

• Interactive Investigation Portal

Related MCP server: Ioc Search MCP Server

Architecture

flowchart TD
    A[Windows Logs] --> G[Log Collection]
    B[Linux Logs] --> G
    C[AWS Logs] --> G
    D[Azure Logs] --> G
    E[Firewall Logs] --> G
    F[Application Logs] --> G

    G --> H[Detection Engine]
    H --> I[Threat Intelligence]
    I --> J[MITRE ATT&CK Mapping]
    J --> K[Multi-Agent Workflow]
    K --> L[Case Management]
    L --> M[FastAPI Services]
    M --> N[React Dashboard]

Multi-Agent Investigation Workflow

flowchart TD
    A[Security Event] --> B[Log Collection Agent]
    B --> C[Detection Agent]
    C --> D[MITRE ATT&CK Agent]
    D --> E[Threat Intelligence Agent]
    E --> F[Correlation Agent]
    F --> G[Severity Escalation Agent]
    G --> H[Case Management Agent]
    H --> I[Investigation Agent]
    I --> J[Final Investigation Report]

Security Capabilities

Threat Detection

• SQL Injection Detection

• Brute Force Detection

• Cross-Site Scripting (XSS) Detection

• API Abuse Detection

• Session Hijacking Detection

• Correlated Multi-Vector Attacks

Investigation & Response

• Incident Correlation

• Threat Prioritization

• Severity Escalation

• Investigation Tracking

• Analyst Notes

• Executive Reporting

AI Technologies

Agentic AI

The platform uses a coordinated multi-agent architecture where specialized agents collaborate to investigate security incidents and generate investigation outcomes.

Pydantic AI

Used for:

• Structured investigation outputs

• Data validation

• Agent communication

• Investigation reporting

• Workflow orchestration

Model Context Protocol (MCP)

Used for:

• Security investigation tools

• Threat intelligence enrichment

• Incident analysis workflows

• Agent-to-tool communication

• Extensible security integrations

Local LLM Ready Architecture

The platform is designed for future integration with local Large Language Models including:

• Ollama

• Qwen

• On-premise Security LLM Deployments

This architecture enables future AI-generated investigation summaries and analyst recommendations while maintaining local control of security data.

Backend Technologies

• Python

• FastAPI

• Pydantic AI

• MCP

• REST APIs

• JSON Investigation Pipeline

• Multi-Agent Workflow Engine

• GitHub Actions CI/CD

Frontend Technologies

• React

• Vite

• React Router

• Axios

• Socket.IO

• Responsive Security Dashboard

API Endpoints

Platform Statistics

GET /statistics

High Priority Cases

GET /high-priority

Case Search

GET /cases

Case Details

GET /case/{case_id}

CI/CD

GitHub Actions automatically validates the platform by:

• Installing project dependencies

• Verifying Python syntax

• Executing the Multi-Agent Orchestrator

• Validating investigation workflow functionality

• Ensuring successful builds before deployment

Learning Objectives

This project demonstrates practical implementation of:

• Agentic AI Architectures

• Security Operations Center (SOC) Workflows

• Multi-Agent Systems

• Pydantic AI

• Model Context Protocol (MCP)

• Threat Intelligence

• MITRE ATT&CK

• FastAPI Development

• React Dashboards

• CI/CD Pipelines

• Security Automation

Future Enhancements

• Ollama + Qwen Investigation Agent

• AI-Generated Executive Summaries

• Automated Threat Hunting

• Advanced Correlation Rules

• Database Persistence

• Docker Deployment

• Cloud-Native Security Integrations

Author

Navid Ghobadpour

Agentic AI Security Operations Platform

Built to explore the intersection of Cybersecurity, Agentic AI, Multi-Agent Systems, Pydantic AI, MCP, Threat Intelligence, and Security Automation.