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/analyzing-ransomware-network-indicators

Identify ransomware-related network indicators, including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange, by analyzing Zeek conn.log and NetFlow data. Use when threat hunting for active ransomware network activity or

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cybersecurity-skills
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Install
$ npx -y skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-ransomware-network-indicators --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/analyzing-ransomware-network-indicators

Context preview

The summary Claude sees to decide when to auto-load this skill.

Identify ransomware-related network indicators, including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange, by analyzing Zeek conn.log and NetFlow data. Use when threat hunting for active ransomware network activity or

SKILL.md

analyzing-ransomware-network-indicators.SKILL.md
name: analyzing-ransomware-network-indicators
description: Identify ransomware-related network indicators, including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange, by analyzing Zeek conn.log and NetFlow data. Use when threat hunting for active ransomware network activity or investigating suspected pre-encryption exfiltration during incident response.
domain: cybersecurity
subdomain: threat-hunting
tags:
- ransomware
- c2-beaconing
- zeek
- netflow
- tor
- exfiltration
- network-forensics
version: '1.0'
author: mahipal
license: Apache-2.0
d3fend_techniques:
- File Metadata Consistency Validation
- Certificate Analysis
- Application Protocol Command Analysis
- Content Format Conversion
- File Content Analysis
nist_csf:
- DE.CM-01
- DE.AE-02
- DE.AE-07
- ID.RA-05
mitre_attack:
- T1071.001
- T1573
- T1048
- T1567.002
- T1486
mitre_f3:
  version: '1.1'
  tactics:
  - positioning
  - monetization
  techniques:
  - id: T1219
    name: Remote Access Tools
    tactic: positioning
    source: attack
  - id: F1018
    name: Convert to Cryptocurrency
    tactic: monetization
    source: f3
  - id: F1047
    name: Transfer of funds
    tactic: monetization
    source: f3

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)
Read more
Ships withcybersecurity-skills

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

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