skills/mukul975/anthropic-cybersecurity-skills/performing-dns-tunneling-detection

performing-dns-tunneling-detection

SKILL.md

Performing DNS Tunneling Detection

Instructions

Analyze DNS traffic for indicators of DNS tunneling using entropy analysis and statistical methods on query name characteristics.

import math
from collections import Counter

def shannon_entropy(data):
    if not data:
        return 0
    counter = Counter(data)
    length = len(data)
    return -sum((c/length) * math.log2(c/length) for c in counter.values())

# Legitimate domain: low entropy (~3.0-3.5)
print(shannon_entropy("www.google.com"))
# DNS tunnel: high entropy (~4.0-5.0)
print(shannon_entropy("aGVsbG8gd29ybGQ.tunnel.example.com"))

Key detection indicators:

  1. High Shannon entropy in query names (> 3.5 for subdomain labels)
  2. Unusually long query names (> 50 characters)
  3. High volume of TXT record requests to a single domain
  4. High unique subdomain count per parent domain
  5. Non-standard character distribution in labels

Examples

from scapy.all import rdpcap, DNS, DNSQR
packets = rdpcap("dns_traffic.pcap")
for pkt in packets:
    if pkt.haslayer(DNSQR):
        query = pkt[DNSQR].qname.decode()
        entropy = shannon_entropy(query)
        if entropy > 4.0:
            print(f"Suspicious: {query} (entropy={entropy:.2f})")
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