24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2.7 KiB
| name | description | domain | subdomain | tags | version | author | license | nist_csf | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| hunting-for-cobalt-strike-beacons | Detect Cobalt Strike beacon network activity using default TLS certificate signatures (serial 8BB00EE), JA3/JA3S/JARM fingerprints, HTTP C2 profile pattern matching, beacon jitter analysis, and named pipe detection via Zeek, Suricata, and Python PCAP analysis. | cybersecurity | threat-hunting |
|
1.0 | mahipal | Apache-2.0 |
|
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 skill covers building detection capabilities using Zeek network logs, Suricata IDS rules, and Python-based PCAP analysis to identify beacon callbacks in network traffic.
When to Use
- When investigating security incidents that require hunting for cobalt strike beacons
- 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 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.