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mukul975
886658219f
- Add mitre_f3 frontmatter block to 94 fraud-relevant skills (phishing, account takeover, banking malware, BEC, identity/KYC, payment/card fraud, money-mule/cash-out, ransomware extortion, DFIR, threat intel) - Map each skill to F3 v1.1 tactics + precise technique IDs, including the two F3-specific tactics ATT&CK lacks: Positioning (FA0001) and Monetization (FA0002) - All 123 F3 v1.1 technique IDs validated against the upstream STIX bundle (github.com/center-for-threat-informed-defense/fight-fraud-framework): 0 invalid IDs, 0 invalid tactics, 0 name mismatches, no placeholder IDs - mitre_f3 kept as a separate block from mitre_attack (F3 redefines several ATT&CK tactics for the fraud context) - Add docs/mitre-f3-mapping.md schema reference - Update README: F3 as the 6th framework, dedicated F3 section + badge
93 lines
3.0 KiB
Markdown
93 lines
3.0 KiB
Markdown
---
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name: analyzing-ransomware-network-indicators
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description: Identify ransomware network indicators including C2 beaconing patterns,
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TOR exit node connections, data exfiltration flows, and encryption key exchange
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via Zeek conn.log and NetFlow analysis
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domain: cybersecurity
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subdomain: threat-hunting
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tags:
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- ransomware
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- c2-beaconing
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- zeek
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- netflow
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- tor
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- exfiltration
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- network-forensics
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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d3fend_techniques:
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- File Metadata Consistency Validation
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- Certificate Analysis
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- Application Protocol Command Analysis
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- Content Format Conversion
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- File Content Analysis
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nist_csf:
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- DE.CM-01
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- DE.AE-02
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- DE.AE-07
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- ID.RA-05
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mitre_attack:
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- T1071.001
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- T1573
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- T1048
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- T1567.002
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- T1486
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mitre_f3:
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version: '1.1'
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tactics:
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- positioning
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- monetization
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techniques:
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- id: T1219
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name: Remote Access Tools
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tactic: positioning
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source: attack
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- id: F1018
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name: Convert to Cryptocurrency
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tactic: monetization
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source: f3
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- id: F1047
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name: Transfer of funds
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tactic: monetization
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source: f3
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---
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# Analyzing Ransomware Network Indicators
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## Overview
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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.
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## When to Use
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- When investigating security incidents that require analyzing ransomware network indicators
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- When building detection rules or threat hunting queries for this domain
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- When SOC analysts need structured procedures for this analysis type
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- When validating security monitoring coverage for related attack techniques
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## Prerequisites
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- Zeek conn.log files or NetFlow CSV/JSON exports
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- Python 3.8+ with standard library
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- TOR exit node list (fetched from Tor Project or threat intel feeds)
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- Optional: Known ransomware C2 IOC list
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## Steps
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1. **Parse Connection Logs** — Ingest Zeek conn.log (TSV) or NetFlow records into structured format
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2. **Detect Beaconing Patterns** — Calculate connection interval statistics (mean, stddev, coefficient of variation) to identify periodic callbacks
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3. **Check TOR Exit Node Connections** — Cross-reference destination IPs against current TOR exit node list
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4. **Identify Data Exfiltration** — Flag connections with unusually high outbound byte ratios to external IPs
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5. **Analyze DNS Patterns** — Detect DGA-like domain queries and high-entropy subdomains
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6. **Score and Correlate** — Apply composite risk scoring across all indicator types
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7. **Generate Report** — Produce structured report with timeline and MITRE ATT&CK mapping
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## Expected Output
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- JSON report with beaconing detections and interval statistics
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- TOR exit node connection alerts
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- Data exfiltration flow analysis
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- Composite ransomware risk score with MITRE mapping (T1071, T1573, T1041)
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