Hunting For Domain Fronting C2 Traffic

Hunting for Domain Fronting C2 Traffic

Overview

Domain fronting (MITRE ATT&CK T1090.004) is a technique where attackers use different domain names in the TLS SNI field and the HTTP Host header to disguise C2 traffic behind legitimate CDN-hosted domains. This skill detects domain fronting by parsing proxy/web gateway logs for SNI-Host header mismatches, analyzing TLS certificates for CDN provider identification, flagging connections where the SNI points to a high-reputation domain but the Host header targets an attacker-controlled domain, and correlating with known CDN provider IP ranges.

When to Use

Trigger phrases:

• "hunting for domain fronting c2 traffic"

• "Detect domain fronting C2 traffic by analyzing SNI vs HTTP Host header mismatche"

• When investigating security incidents that require hunting for domain fronting c2 traffic

• 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

Prerequisites

• Web proxy or secure web gateway logs with SNI and Host header fields
• Python 3.8+ with pyOpenSSL and cryptography libraries
• TLS inspection enabled on proxy for Host header visibility
• CDN provider IP range lists (CloudFront, Azure CDN, Cloudflare)

Steps

# 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. Parse proxy logs for connections with both SNI and Host header fields
2. Compare SNI domain against HTTP Host header for mismatches
3. Extract TLS certificate Subject and SAN fields using pyOpenSSL
4. Identify CDN-hosted connections via certificate issuer and IP ranges
5. Flag high-confidence domain fronting where SNI and Host differ on CDN IPs
6. Score alerts based on domain reputation differential
7. Generate detection report with network flow context

Expected Output

JSON report containing detected domain fronting indicators with SNI-Host pairs, certificate details, CDN provider identification, confidence scores, and MITRE ATT&CK technique mapping.

When NOT to Use

• You're responding to a known incident (use IR skills)
• Task is about analyzing confirmed malware (use analyzing-* skills)
• You need to implement detection rules (use implementing-* skills)
• Task is about vulnerability scanning (use scanning tools)
• You don't have access to endpoint/network data
• Task requires compliance auditing (use auditing-* skills)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Capturing traffic on networks without authorization or privacy considerations
• Leaving packet captures containing sensitive data unencrypted on disk
• Deploying inline blocking rules without testing for false positives first

Process

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Captures verified as complete with no dropped packets
• Detection rules tested against known-benign traffic for false positive rate
• Alert thresholds validated and tuned to reduce noise

Anti-Rationalization Table