analyzing-ransomware-network-indicators
$
npx mdskill add mukul975/Anthropic-Cybersecurity-Skills/analyzing-ransomware-network-indicatorsDetect ransomware C2 and exfiltration via Zeek and NetFlow logs.
- Automates forensic analysis of network traffic for threat hunting.
- Requires Zeek conn.log files, NetFlow exports, and Python 3.8+.
- Correlates beaconing patterns against known TOR exit node lists.
- Outputs structured detection findings for SOC analysts and rule builders.
SKILL.md
.github/skills/analyzing-ransomware-network-indicatorsView on GitHub ↗
--- name: analyzing-ransomware-network-indicators description: Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis domain: cybersecurity subdomain: threat-hunting tags: [ransomware, c2-beaconing, zeek, netflow, tor, exfiltration, network-forensics] version: "1.0" author: mahipal license: Apache-2.0 --- # Analyzing Ransomware Network Indicators ## Overview Before and during ransomware execution, adversaries establish C2 channels, exfiltrate data, and download encryption keys. This skill analyzes Zeek conn.log and NetFlow data to detect beaconing patterns (regular-interval callbacks), connections to known TOR exit nodes, large outbound data transfers, and suspicious DNS activity associated with ransomware families. ## When to Use - When investigating security incidents that require analyzing ransomware network indicators - 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 - Zeek conn.log files or NetFlow CSV/JSON exports - Python 3.8+ with standard library - TOR exit node list (fetched from Tor Project or threat intel feeds) - Optional: Known ransomware C2 IOC list ## Steps 1. **Parse Connection Logs** — Ingest Zeek conn.log (TSV) or NetFlow records into structured format 2. **Detect Beaconing Patterns** — Calculate connection interval statistics (mean, stddev, coefficient of variation) to identify periodic callbacks 3. **Check TOR Exit Node Connections** — Cross-reference destination IPs against current TOR exit node list 4. **Identify Data Exfiltration** — Flag connections with unusually high outbound byte ratios to external IPs 5. **Analyze DNS Patterns** — Detect DGA-like domain queries and high-entropy subdomains 6. **Score and Correlate** — Apply composite risk scoring across all indicator types 7. **Generate Report** — Produce structured report with timeline and MITRE ATT&CK mapping ## Expected Output - JSON report with beaconing detections and interval statistics - TOR exit node connection alerts - Data exfiltration flow analysis - Composite ransomware risk score with MITRE mapping (T1071, T1573, T1041)