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Prompts Cobalt Strike Beacon Network Detection

security analyst security skill risk: medium

Cobalt Strike Beacon Network Detection

The prompt provides steps to detect Cobalt Strike beacons via TLS certificate analysis, beacon interval analysis, HTTP profile matching, and multi-indicator scoring using Zeek logs…

SKILL 4 files · 2 folders

SKILL.md
---
name: hunting-for-cobalt-strike-beacons
description: "Detect Cobalt Strike beacon network activity using default TLS certificate signatures (serial 8BB00EE), JA3/JA3S/JARM"
---
# 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.

REQUIRED CONTEXT

  • Zeek logs or PCAPs
  • Suricata ruleset

OPTIONAL CONTEXT

  • threat intel IOCs

EXPECTED OUTPUT

Format
structured_report
Schema
json_schema · detected beacon candidates, confidence scores, TLS fingerprints, timing analysis, HTTP profile matches, recommended response actions
Constraints
  • JSON report with confidence scores, fingerprints, timing analysis, profile matches, and response actions

CAVEATS

Dependencies
  • 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
Missing context
  • Exact Zeek/Suricata queries or Python snippets
  • Detailed JSON schema for the expected report
Ambiguities
  • Steps describe goals but provide no concrete commands, queries, or code.
  • Does not specify input format (PCAP path, log directory, etc.).

QUALITY

OVERALL
0.58
CLARITY
0.82
SPECIFICITY
0.68
REUSABILITY
0.28
COMPLETENESS
0.62

IMPROVEMENT SUGGESTIONS

  • Add concrete example queries or code blocks under each step.
  • Define the precise JSON structure and field names for the expected output.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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