analyzing-email-headers-for-phishing-investigation

Analyzing Email Headers For Phishing Investigation

Overview

Cybersecurity skill for analyzing email headers for phishing investigation. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "analyzing email headers for phishing investigation"

• "Parse and analyze email headers to trace the origin of phishing emails, verify s"

• When investigating a suspected phishing email to determine its true origin

• For verifying sender authenticity and detecting email spoofing

• During incident response when a user has clicked a phishing link

• When tracing the delivery path and relay servers of a suspicious email

• For validating SPF, DKIM, and DMARC alignment to identify forgery

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Raw email headers from the suspicious message (EML or MSG format)
• Understanding of SMTP protocol and email header fields
• Access to DNS lookup tools (dig, nslookup) for SPF/DKIM/DMARC verification
• Email header analysis tools (MHA, emailheaders.net concepts)
• Python with email parsing libraries for automated analysis
• Access to threat intelligence platforms for IP/domain reputation

Workflow

# 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. Scope the Analysis — Define what email headers artifacts or data sources to examine and the investigation timeline.
2. Preserve Evidence — Create forensic copies of relevant data. Maintain chain of custody documentation.
3. Extract Key Indicators — Use phishing investigation to parse and extract relevant email headers data points from collected artifacts.
4. Correlate Findings — Cross-reference extracted data with other sources (threat intel, logs, timelines).
5. Build Timeline — Construct a chronological sequence of events related to email headers.
6. Document Analysis — Write findings report with evidence, conclusions, and recommendations.