# Analyzing Ransomware Network Indicators

> 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

- Skill: `thedixitjain/analyzing-ransomware-network-indicators` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add thedixitjain/analyzing-ransomware-network-indicators`
- Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/analyzing-ransomware-network-indicators/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: thedixitjain (https://skillmd.com/u/thedixitjain)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/thedixitjain/analyzing-ransomware-network-indicators

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# 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)

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**Source:** [`mukul975/Anthropic-Cybersecurity-Skills`](https://github.com/mukul975/Anthropic-Cybersecurity-Skills) → `skills/analyzing-ransomware-network-indicators/SKILL.md`

