detecting-beaconing-patterns-with-zeek

name	detecting-beaconing-patterns-with-zeek
description	Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.
domain	cybersecurity
tags	["detecting","beaconing","patterns","with"]
subdomain	security-operations
version	1.0
author	oyi77
license	Apache-2.0
nist_csf	["DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02"]

Detecting Beaconing Patterns With Zeek

Overview

Cybersecurity skill for detecting beaconing patterns with zeek. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "detecting beaconing patterns with zeek"

• "When investigating security incidents that require detecting beaconing patterns"

• "When building detection rules or threat hunting queries for this domain"

• "When SOC analysts need structured procedures for this analysis type"

• When investigating security incidents that require detecting beaconing patterns with zeek

• 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

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Familiarity with security operations concepts and tools
• Access to a test or lab environment for safe execution
• Python 3.8+ with required dependencies installed
• Appropriate authorization for any testing activities

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. — Identify the specific beaconing patterns techniques or indicators to hunt. Map to MITRE ATT&CK tactics/techniques where applicable.