analyzing-dns-logs-for-exfiltration

1# Analyzing DNS Logs for Exfiltration
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3## When to Use
4 
5Use this skill when:
6- SOC teams suspect data exfiltration through DNS tunneling to bypass firewall/proxy controls
7- Threat intelligence indicates adversaries using DNS-based C2 channels (e.g., Cobalt Strike DNS beacon)
8- UEBA detects anomalous DNS query volumes from specific hosts
9- Malware analysis reveals DNS-over-HTTPS (DoH) or DNS tunneling capabilities
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11**Do not use** for standard DNS troubleshooting or availability monitoring — this skill focuses on security-relevant DNS abuse detection.
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13## Prerequisites
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15- DNS query logging enabled (Windows DNS Server, Bind, Infoblox, or Cisco Umbrella)
16- DNS logs ingested into SIEM (Splunk with `Stream:DNS`, `dns` sourcetype, or Zeek DNS logs)
17- Passive DNS data for historical domain resolution analysis
18- Baseline of normal DNS behavior (query volume, domain distribution, TXT record frequency)
19- Python with `math` and `collections` libraries for entropy calculation
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21## Workflow
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23### Step 1: Detect DNS Tunneling via Subdomain Length Analysis
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25DNS tunneling encodes data in subdomain labels, creating unusually long queries:
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27```spl
28index=dns sourcetype="stream:dns" query_type IN ("A", "AAAA", "TXT", "CNAME", "MX")
29| eval domain_parts = split(query, ".")
30| eval subdomain = mvindex(domain_parts, 0, mvcount(domain_parts)-3)
31| eval subdomain_str = mvjoin(subdomain, ".")
32| eval subdomain_len = len(subdomain_str)
33| eval tld = mvindex(domain_parts, -1)
34…