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hunting-dns-tunneling-and-exfiltration

Detects DNS-based tunneling and data exfiltration in DNS logs: scoring high query volume to single domains, long/high-entropy subdomains, unusual record types, and encoded payload labels. Activates for requests to hunt DNS tunneling, detect DNS exfiltration, or analyze suspicious DNS query patterns.

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포함된 파일(4)

  • SKILL.md3.1 KB
  • LICENSE340 B
  • references/api-reference.md1.2 KB
  • scripts/analyst.py3.4 KB

SKILL.md(원문)

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Hunting DNS Tunneling and Exfiltration

When to Use

  • You have DNS query logs (resolver, Zeek dns.log, Windows DNS) and want to find tunneling or exfiltration over DNS.
  • You are testing a hypothesis that an implant uses DNS as a covert channel.
  • You need to rank domains by tunneling indicators across many queries.

Do not use query length alone as a verdict — CDNs, antivirus lookups, and some SaaS use long encoded labels legitimately; combine entropy, volume, and record-type signals.

Prerequisites

  • DNS logs with query name, query type, source, and timestamp, over a meaningful window.
  • A way to whitelist known-benign high-volume domains (security vendors, CDNs).

Workflow

Step 1: Aggregate by registered domain

Group queries under their registered/parent domain so per-domain volume and subdomain diversity are visible.

Step 2: Score tunneling indicators

Weight: high unique-subdomain count, long average label length, high subdomain entropy (encoded data), heavy TXT/NULL/CNAME usage, and high query rate to one domain.

python scripts/analyst.py hunt dns.json

Step 3: Estimate exfiltration volume

Sum encoded bytes implied by query lengths per domain; sustained high volume to a single nameserver suggests data egress.

Step 4: Whitelist and pivot

Remove known-benign high-entropy domains; for survivors, check domain age/registration, the authoritative nameserver, and the originating host.

Step 5: Confirm and respond

Validate by decoding sampled labels where possible and correlating with host activity; escalate confirmed tunnels and write a detection.

Validation

  • High-score domains combine multiple signals (entropy + volume + record type), not one alone.
  • Benign high-volume domains are whitelisted, keeping the list reviewable.
  • Confirmed tunnels tie to a specific host and a young/suspicious domain.

Pitfalls

  • Flagging long labels from CDNs and AV telemetry as tunneling.
  • Aggregating by full FQDN instead of registered domain, hiding subdomain diversity.
  • Ignoring record type; TXT/NULL carry far more data than A records.

References

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