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Skill

/analyzing-ransomware-network-indicators

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration

From plugin
sectinel
11200 skills
Install
$ npx -y skills add Mikaru0Mystic/sectinel --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 network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration

SKILL.md

analyzing-ransomware-network-indicators.SKILL.md
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
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

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
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Open-source security arsenal for AI coding agents: 784 cybersecurity skills, scanner integrations, and a security MCP for Claude Code, Cursor, opencode, Gemini CLI, Cline, and any agentskills.io agent. Mapped to OWASP, MITRE ATT&CK, NIST CSF, D3FEND, ATLAS.

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