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Analyzing Threat Landscape With Misp by xalgord

Name: Analyzing Threat Landscape With Misp
Author: xalgord

Analyzing Threat Landscape With Misp

Analyze 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.

xalgord Updated Sep 17, 2026

File contents

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

Detection Gaps & Validation

Attribute-type coverage: counting only ip-dst/domain/sha256 undercounts the landscape -- MISP also stores ip-src, hostname, url, md5, sha1, filename|sha256, and btc. Enumerate the full Attribute.type set or your IOC-type breakdown is biased.
Galaxy/tag inconsistency: actor attribution lives in galaxy clusters (mitre-intrusion-set, threat-actor) and free-text Tags applied unevenly -- APT28 may appear as "Sofacy", "Fancy Bear", or a galaxy UUID. Normalize via galaxy synonyms before ranking top actors.
Sharing/visibility gaps: API-key org permissions and event distribution levels mean search() returns only visible events; "top threat level" skews to what your org can see.
Stale events: old events inflate counts unless you bound by --days/timestamp.

To validate: confirm event totals from PyMISP search() match the MISP web UI for the same date range and filters; verify pagination is not truncating results (default page limits). Re-run the technique ranking with galaxy-synonym normalization and confirm duplicate actors collapse. Sanity-check that T1566-style technique counts come from ATT&CK galaxy clusters, not ad-hoc tags, before reporting a "top technique."

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

Install dependencies: pip install pymisp
Configure MISP URL and API key.
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

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)

---name: analyzing-threat-landscape-with-mispdescription: Analyze 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.license: Apache-2.0---# 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## Detection Gaps & Validation- **Attribute-type coverage:** counting only `ip-dst`/`domain`/`sha256` undercounts the landscape -- MISP also stores `ip-src`, `hostname`, `url`, `md5`, `sha1`, `filename|sha256`, and `btc`. Enumerate the full `Attribute.type` set or your IOC-type breakdown is biased.- **Galaxy/tag inconsistency:** actor attribution lives in `galaxy` clusters (`mitre-intrusion-set`, `threat-actor`) and free-text `Tag`s applied unevenly -- APT28 may appear as "Sofacy", "Fancy Bear", or a galaxy UUID. Normalize via galaxy synonyms before ranking top actors.- **Sharing/visibility gaps:** API-key org permissions and event `distribution` levels mean `search()` returns only visible events; "top threat level" skews to what your org can see.- **Stale events:** old events inflate counts unless you bound by `--days`/`timestamp`.To validate: confirm event totals from PyMISP `search()` match the MISP web UI for the same date range and filters; verify pagination is not truncating results (default page limits). Re-run the technique ranking with galaxy-synonym normalization and confirm duplicate actors collapse. Sanity-check that `T1566`-style technique counts come from ATT&CK galaxy clusters, not ad-hoc tags, before reporting a "top technique."## 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## Instructions1. 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```bashpython 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 daysEvents analyzed: 1,247Top 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)```

Frequently asked questions