abusing-dpapi-for-cred…
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using…
Query a MISP (Malware Information Sharing Platform) instance via PyMISP
$ npx -y skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-threat-landscape-with-misp --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/analyzing-threat-landscape-with-mispContext preview
The summary Claude sees to decide when to auto-load this skill.
Query a MISP (Malware Information Sharing Platform) instance via PyMISP
name: analyzing-threat-landscape-with-misp 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
1. Install dependencies: `pip install pymisp` 2. Configure MISP URL and API key. 3. Run the agent to generate threat landscape analysis:
python scripts/agent.py --misp-url https://misp.local --api-key YOUR_KEY --days 90 --output landscape_report.json
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)
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0
Repo: mukul975/Anthropic-Cybersecurity-Skills
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