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.

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)

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.2 (Anomaly Detection), CC7.3 (Incident Identification)
• ISO 27001: A.12.4 (Logging & Monitoring), A.16.1 (Security Incident Management)
• NIST 800-53: SI-4 (System Monitoring), IR-4 (Incident Handling), RA-5 (Vulnerability Scanning)
• NIST CSF: DE.AE (Anomalies & Events), DE.CM (Continuous Monitoring), DE.DP (Detection Processes)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add analyzing-ransomware-network-indicators

# Or load dynamically via MCP
grc.load_skill("analyzing-ransomware-network-indicators")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.