analyzing-threat-landscape-with-misp

name	analyzing-threat-landscape-with-misp
description	Use when analyzing the threat landscape using MISP (Malware Information Sharing Platform) by querying event statistics, attribute distributions, threat actor galaxy clusters, and tag trends over time. Uses PyMISP to pull event data, compute IOC type breakdowns, identify top threat actors and malware families, and generate threat landscape reports with temporal trends.
domain	cybersecurity
tags	["analyzing","threat","landscape","with"]
subdomain	threat-intelligence
version	1.0
author	oyi77
license	Apache-2.0
d3fend_techniques	["File Metadata Consistency Validation","Application Protocol Command Analysis","Identifier Analysis","Content Format Conversion","Message Analysis"]
nist_csf	["ID.RA-01","ID.RA-05","DE.CM-01","DE.AE-02"]

Analyzing Threat Landscape With Misp

Overview

Cybersecurity skill for analyzing threat landscape with misp. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "analyzing threat landscape with misp"

• "Analyze the threat landscape using MISP (Malware Information Sharing Platform) b"

• When investigating security incidents that require analyzing threat landscape with misp

• When building detection rules or threat hunting queries for this domain

• When SOC analysts need structured procedures for this analysis type

• When validating security monitoring coverage for related attack techniques

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Familiarity with threat intelligence concepts and tools
• Access to a test or lab environment for safe execution
• Python 3.8+ with required dependencies installed
• Appropriate authorization for any testing activities

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Scope the Analysis — Define what threat landscape artifacts or data sources to examine and the investigation timeline.
2. Preserve Evidence — Create forensic copies of relevant data. Maintain chain of custody documentation.