What is IoC Research designed for?

IoC Research is a tool that integrates multiple OSINT sources to provide agentic AI models (like Gemini, Claude, Copilot) with comprehensive, structured threat intelligence on Indicators of Compromise (IoCs).

What types of IoCs can be analyzed using this tool?

IoC Research supports the analysis of various Indicators of Compromise, including domains, IP addresses, file hashes (MD5, SHA1, SHA256), and URLs.

How does IoC Research support AI models?

It acts as a FastMCP Python-based server, allowing LLM clients (such as Gemini, Claude, and Copilot) to programmatically query and receive structured data for enhanced IoC research.

Is API key management secure with IoC Research?

Yes, IoC Research prioritizes security by reading all API keys from environment variables, ensuring they are never stored directly in prompts or configuration files.

IoC Research

Name: IoC Research
Author: CyberPanther232

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Facilitates OSINT research on Indicators of Compromise (IoCs) by integrating multiple threat intelligence sources for agentic AI models.

This FastMCP Python-based server empowers agentic AI models like Copilot, Gemini, and Claude to conduct comprehensive OSINT research on Indicators of Compromise (IoCs). It programmatically gathers intelligence on domains, IPs, hashes, and URLs by integrating with multiple OSINT sources, including VirusTotal, Shodan, ThreatFox, and MalwareBazaar. Designed to enhance security analyses, it allows AI applications to leverage external threat intelligence securely, using environment variables for API keys and providing structured output for further analysis.

主な機能

010 GitHub stars

02Supports various IoC types: domains, IPs, hashes, URLs

03Securely manages API keys via environment variables

04Assists agentic AI models (Copilot, Gemini, Claude) with IoC research

05Provides structured output for follow-on analysis

06Integrates multiple OSINT sources (VirusTotal, Shodan, ThreatFox, MalwareBazaar)

ユースケース

01Automating OSINT lookups for security investigations by AI agents

02Programmatic gathering of threat intelligence for Incident Response

03Enhancing LLM capabilities with real-time IoC reputation checks