hunting-for-beaconing-with-frequency-analysis
Makes your agent identify 'malware' communication patterns by analyzing network traffic. It helps detect suspicious activities and connections to command and control servers.
What it does
This tool helps find computers on your network that might be secretly communicating with a malicious server. It does this by looking for communication patterns that repeat at regular intervals, like a 'signal' sent back to a 'commander'.
When to use it
- ✓When you suspect a computer might be compromised.
- ✓If you've received warnings about new threats that could affect your network.
- ✓When you see computers connecting to strange places on the internet at regular intervals.
Example of what to ask your AI
“Look for signs of secret communication on our network.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool analyzes network connection logs to find repeating communication patterns. It calculates the time between connections and checks for a regular pattern, while ignoring normal communications like software updates.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill hunting-for-beaconing-with-frequency-analysisOr download just the file:
curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/hunting-for-beaconing-with-frequency-analysis/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Hunting for Beaconing with Frequency Analysis
When to Use
- When proactively searching for compromised endpoints calling back to C2 infrastructure
- After threat intelligence reports indicate active C2 frameworks targeting your sector
- When network logs show periodic outbound connections to unfamiliar destinations
- During purple team exercises validating C2 detection capabilities
- When investigating a potential breach and need to identify active C2 channels
Prerequisites
- Network proxy/firewall logs with timestamps and destination data (minimum 24 hours)
- Zeek conn.log, dns.log, and ssl.log or equivalent NetFlow/IPFIX data
- SIEM platform with statistical analysis capability (Splunk, Elastic, Microsoft Sentinel)
- RITA (Real Intelligence Threat Analytics) or AC-Hunter for automated beacon analysis
- Threat intelligence feeds for domain/IP reputation enrichment
Workflow
- Define Beacon Parameters: Establish detection thresholds -- coefficient of variation (CV) below 0.20 indicates strong periodicity, minimum 50 connections over 24 hours, average interval between 30 seconds and 24 hours.
- Collect Network Telemetry: Aggregate proxy logs, DNS queries, firewall connection logs, and Zeek metadata into the analysis platform.
- Calculate Connection Intervals: For each source-destination pair, compute the time delta between consecutive connections and derive mean interval, standard deviation, and CV.
- Apply Jitter Analysis: Sophisticated C2 frameworks like Cobalt Strike add jitter (randomness) to beacon intervals. The Sunburst backdoor beaconed every 15 minutes plus/minus 90 seconds. Analyze jitter patterns to detect even randomized beaconing.
- Filter Legitimate Periodic Traffic: Exclude known-good beaconing sources including Windows Update, antivirus definition updates, NTP synchronization, SaaS heartbeat services, and CDN health checks.
- Analyze Data Size Consistency: C2 heartbeat packets typically have consistent payload sizes. Calculate the CV of bytes transferred per connection -- low variance suggests automated communication.
- Enrich with Threat Intelligence: Check identified beaconing destinations against VirusTotal, WHOIS registration data (flag domains under 30 days old), certificate transparency logs, and passive DNS history.
- Correlate with Endpoint Telemetry: Map beaconing source IPs to endpoint hostnames via DHCP logs, then correlate with process creation events (Sysmon Event ID 1, 3) to identify the responsible process.
- Score and Prioritize: Assign risk scores based on CV value, domain age, TI matches, data size consistency, and suspicious port usage. Escalate high-confidence findings.
Key Concepts
| Concept | Description |
|---|---|
| T1071.001 | Application Layer Protocol: Web Protocols -- HTTP/HTTPS beaconing |
| T1071.004 | Application Layer Protocol: DNS -- DNS-based C2 tunneling |
| T1573 | Encrypted Channel -- TLS/SSL encrypted C2 communication |
| T1568.002 | Dynamic Resolution: Domain Generation Algorithms |
| Coefficient of Variation | Standard deviation divided by mean; values below 0.20 indicate periodicity |
| Jitter | Random variation added to beacon interval to evade detection |
| RITA Beacon Score | Composite score from connection regularity, data size consistency, and connection count |
| JA3/JA4 Fingerprinting | TLS client fingerprinting to identify C2 framework signatures |
| Fast-Flux DNS | Rapidly changing DNS resolution used to protect C2 infrastructure |
Tools & Systems
| Tool | Purpose |
|---|---|
| RITA (Real Intelligence Threat Analytics) | Automated beacon scoring from Zeek logs |
| AC-Hunter | Commercial threat hunting platform with beacon detection |
| Splunk | SPL-based statistical beacon analysis with streamstats |
| Elastic Security | ML anomaly detection for periodic network behavior |
| Zeek | Network metadata collection (conn.log, dns.log, ssl.log) |
| Suricata | Network IDS with JA3/JA4 TLS fingerprint extraction |
| FLARE | C2 profile and beacon pattern detection |
| VirusTotal | Domain and IP reputation enrichment |
Detection Queries
Splunk -- HTTP/S Beacon Frequency Analysis
index=proxy OR index=firewall
| where NOT match(dest, "(?i)(microsoft|google|amazonaws|cloudflare|akamai)")
| bin _time span=1s
| stats count by src_ip dest _time
| streamstats current=f last(_time) as prev_time by src_ip dest
| eval interval=_time-prev_time
…
FAQ
What is 'beaconing'?
It's when an infected computer sends regular signals to a control server, like a beacon flashing to guide a ship.
What is 'jitter'?
It's a small random variation in the timing between signals. Hackers use this to try and disguise the regular pattern and avoid detection.
Why do I need network logs for at least 24 hours?
To have enough data to identify repeating communication patterns over time, distinguishing them from normal, sporadic activity.
Details
Original description by the author
Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.
Popularity
- GitHub stars
- 35k
- Ranking position
- #5786
- License
- Apache-2.0
- Updated
- 8/31/2026
Comments
- …
More skills from this repository
abusing-dpapi-for-credential-access
Gives your AI agent ready-made instructions for a specific task, so it does it better and faster.
mukul975/Anthropic-Cybersecurity-Skills
abusing-shadow-credentials-for-privesc
Teaches your AI agent to write clear, well-structured text.
mukul975/Anthropic-Cybersecurity-Skills
achieving-cmmc-level-2-compliance
Helps your agent prepare an environment for CMMC Level 2 compliance. It implements security requirements and manages necessary documentation.
mukul975/Anthropic-Cybersecurity-Skills
acquiring-disk-image-with-dd-and-dcfldd
Helps your agent create exact copies of hard drives. This is useful for ensuring no information is lost or altered during investigations.
mukul975/Anthropic-Cybersecurity-Skills
Similar skills
data-throughput-accelerator
Makes your agent speed up the movement of large data volumes. It finds bottlenecks and ensures data is transferred quickly and correctly.
affaan-m/ECC
inventory-demand-planning
Helps your agent predict product demand in stores. It optimizes stock and plans when to run promotions to sell more.
affaan-m/ECC
market-research
Helps your agent conduct market research and competitive analysis. Provides summaries with source attribution.
affaan-m/ECC