Hunting for Cobalt Strike Beacons

Overview

Cobalt Strike is the most prevalent command-and-control framework used by both red teams and threat actors. Beacon, its primary payload, communicates with team servers using configurable HTTP/HTTPS/DNS profiles that can mimic legitimate traffic. However, default configurations and behavioral patterns remain detectable through TLS certificate analysis (default serial 8BB00EE), JA3/JA3S fingerprinting, beacon interval jitter analysis, and HTTP malleable profile pattern matching. This guide covers building detection capabilities using Zeek network logs, Suricata IDS rules, and Python-based PCAP analysis to identify beacon callbacks in network traffic.

Prerequisites

• Zeek 6.0+ with JA3 and HASSH packages installed
• Suricata 7.0+ with Emerging Threats ruleset
• Python 3.9+ with scapy and dpkt libraries
• Network traffic captures (PCAP) or live Zeek logs
• RITA (Real Intelligence Threat Analytics) for beacon scoring
• Threat intelligence feeds with known Cobalt Strike IOCs

Steps

Step 1: TLS Certificate Analysis

Detect default Cobalt Strike certificates using JA3S fingerprints, certificate serial numbers, and JARM fingerprints in Zeek ssl.log.

Step 2: Beacon Interval Analysis

Analyze connection timing patterns to identify regular callback intervals with configurable jitter, characteristic of beacon behavior.

Step 3: HTTP Profile Detection

Match HTTP request patterns (URI paths, headers, user-agents) against known malleable C2 profiles.

Step 4: Correlate and Score

Combine multiple indicators (TLS + timing + HTTP profile) into a composite beacon confidence score.

Expected Output

JSON report containing detected beacon candidates with confidence scores, TLS fingerprints, timing analysis, HTTP profile matches, and recommended response actions.

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 hunting-for-cobalt-strike-beacons

# Or load dynamically via MCP
grc.load_skill("hunting-for-cobalt-strike-beacons")

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.