analyzing-threat-landscape-with-misp
This Claude Code skill integrates with MISP (Malware Information Sharing Platform) to analyze threat landscapes by aggregating event statistics, attribute distributions, MITRE ATT&CK technique mappings, and threat actor activity patterns. Use it when security operations center analysts need structured threat intelligence analysis, require detection rule validation, or must track temporal trends in indicators of compromise across a specified timeframe.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills /tmp/analyzing-threat-landscape-with-misp && cp -r /tmp/analyzing-threat-landscape-with-misp/skills/analyzing-threat-landscape-with-misp ~/.claude/skills/analyzing-threat-landscape-with-mispSKILL.md
# 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) ```
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket's dpapi.py, including domain-wide decryption via the DPAPI backup key. Use during authorized red-team credential-access engagements after gaining a foothold or when triaging DPAPI blobs pulled from a host.
Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target's NT hash without a password reset. Use when BloodHound shows GenericWrite/GenericAll/AddKeyCredentialLink over a target, as a stealthier alternative to ForceChangePassword, during authorized red-team engagements.
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Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.
Detect dangerous ACL misconfigurations in Active Directory using ldap3
Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect