# analyzing-threat-landscape-with-misp

> Query MISP event statistics, attribute distributions, threat actor galaxy clusters, and tag trends over time to generate threat landscape reports.

- Skill: `mukul975/analyzing-threat-landscape-with-misp` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add mukul975/analyzing-threat-landscape-with-misp`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mukul975/analyzing-threat-landscape-with-misp/raw
- Safety review: CAUTION (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Tags: Ioc, Malware, Misp, Mitre Attck, Pymisp, Python, Threat Actor, Threat Intelligence
- License: Apache-2.0
- Author: mukul975 (https://skillmd.com/u/mukul975)
- Updated: 2026-07-06
- Page: https://skillmd.com/skills/mukul975/analyzing-threat-landscape-with-misp

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# Analyzing Threat Landscape with MISP


## When to Use

- 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

## 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

## Instructions

1. Install dependencies: `pip install pymisp`
2. Configure MISP URL and API key.
3. Run the agent to generate threat landscape analysis:
   - Pull event statistics by threat level and date range
   - Analyze attribute type distributions (IP, domain, hash, URL)
   - Identify top MITRE ATT&CK techniques from event tags
   - Track threat actor activity via galaxy clusters
   - Generate temporal trend analysis of IOC submissions

```bash
python scripts/agent.py --misp-url https://misp.local --api-key YOUR_KEY --days 90 --output landscape_report.json
```

## Examples

### Threat Landscape Summary
```
Period: Last 90 days
Events analyzed: 1,247
Top threat level: High (43%)
Top attribute type: ip-dst (31%), domain (22%), sha256 (18%)
Top MITRE technique: T1566 Phishing (89 events)
Top threat actor: APT28 (34 events)
```