Prompt
Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
ClaudeChatGPTGeminiData & Analytics
Dave AI
Analyzing Threat Landscape with MISP
Analyze the threat landscape using MISP (Malware Information Sharing
instructions.md
--- name: analyzing-threat-landscape-with-misp-76e556b5cdd0 description: Query a MISP (Malware Information Sharing Platform) instance via PyMISP to compute event statistics, IOC type breakdowns, threat actor galaxy clusters, and tag trends, and generate threat landscape reports with temporal trends. Use when asked to analyze threat intelligence data, summarize top threat actors or malware families, or produce a CTI landscape report from MISP events. domain: cybersecurity subdomain: threat-intelligence tags: - threat-intelligence - misp - threat-landscape - ioc-analysis - cti - threat-sharing version: '1.0' author: mahipal 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 mitre_attack: - T1566 - T1071.001 - T1568 - T1583.001 - T1102 --- # 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) ```--- name: analyzing-threat-landscape-with-misp-76e556b5cdd0 description: Query a MISP (Malware Information Sharing Platform) instance via PyMISP to compute event statistics, IOC type breakdowns, threat actor galaxy clusters, and tag trends, and generate threat landscape reports with temporal trends. Use when asked to analyze threat intelligence data, summarize top threat actors or malware families, or produce a CTI landscape report from MISP events. domain: cybersecurity subdomain: threat-intelligence tags: - threat-intelligence - misp - threat-landscape - ioc-analysis - cti - threat-sharing version: '1.0' author: mahipal 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 mitre_attack: - T1566 - T1071.001 - T1568 - T1583.001 - T1102 --- # 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) ```
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.