mirror of
https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
synced 2026-07-23 21:21:00 +03:00
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
68 lines
2.6 KiB
Markdown
68 lines
2.6 KiB
Markdown
---
|
|
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)
|