DNS4 Network Fingerprinting

DNS4 is DNS Science's proprietary network fingerprinting suite that identifies devices, software, and threats by analyzing network traffic patterns. Unlike traditional fingerprinting tools, DNS4 uniquely correlates network behavior with DNS intelligence, providing unprecedented visibility into infrastructure and security posture.

Problems DNS4 Solves

• What devices are on my network? Mobile, IoT, servers, unknown devices
• What software versions are running? Outdated clients, vulnerable services
• Are there malicious actors? C2 traffic, data exfiltration, botnet activity
• Who's using VPNs/proxies? Legitimate privacy tools vs. threat actor obfuscation
• Is this traffic bot or human? Automated scrapers vs. real users

TLS Server Analysis

curl -X POST https://api.dnsscience.io/v1/dns4/tls \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "target": "example.com",
    "port": 443
  }'

Python SDK

pip install dnsscience

from dnsscience import DNS4Client

client = DNS4Client(api_key="YOUR_API_KEY")

# TLS analysis
tls = client.tls.analyze("example.com")
print(f"Server: {tls.server_software}")
print(f"Score: {tls.security_score}/100")

# Unified analysis
analysis = client.analyze("example.com", methods=["tls", "http", "cert"])
print(f"Risk Score: {analysis.threat_summary.risk_score}/100")

DNS4-TLS Response

{
  "fingerprint": "t13d1516h2_e92c3fa1e5d2_a4b8c9",
  "server_software": "nginx/1.21.6",
  "tls_version": "TLS 1.3",
  "cipher_suite": "TLS_AES_256_GCM_SHA384",
  "security_score": 95,
  "certificate": {
    "issuer": "Let's Encrypt",
    "subject": "example.com",
    "valid_to": "2024-04-01T00:00:00Z"
  },
  "threat_intel": {
    "is_malicious": false,
    "is_blacklisted": false
  },
  "dns_correlation": {
    "domain_age_days": 3650,
    "registrar": "Example Registrar Inc.",
    "recent_ip_changes": false
  }
}