Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.
Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.
Analyzing Email Headers for Phishing Investigation
When to Use
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
Detection Gaps & Validation
Most-missed header evidence: analysts read From/Received and stop. Also parse Authentication-Results/ARC-Authentication-Results (the receiver's own verdict, harder to forge than Received-SPF), Return-Path vs From (envelope mismatch), the Message-ID domain vs the sender domain, and X-Originating-IP. Everything below your own perimeter MTA in the Received chain is attacker-controlled and forgeable - trust only hops you operate.
SPF/DKIM "pass" is not "legitimate": a pass only proves the message left authorized infrastructure - fully consistent with a compromised mailbox, a shared ESP (SendGrid/Mailchimp) abused by another tenant, or a lookalike domain with its own valid records. Verify DKIM with the d=/s= selector via dig TXT s._domainkey.d and check alignment, not just the pass flag.
Cross-corroborate the finding: validate the sending IP against the SPF record AND reverse DNS AND reputation (AbuseIPDB/VirusTotal); confirm a phishing URL against URLhaus/PhishTank; hash attachments and check VT - do not call "spoofed" on a header mismatch alone.
Anti-forensics / evasion: punycode/homoglyph display names, Reply-To differing from From, HTML hyperlink text masking the real href, and forwarded copies that strip the original Received chain. Always work from the original .eml/.msg, never a forwarded screenshot.
Interpretation pitfalls (false positives): mailing lists and forwarders legitimately break SPF (rely on ARC); Date timezone and MTA clock skew misorder the hop timeline; and a p=none DMARC failure means "not enforced," not "confirmed forgery."
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
Python with email parsing libraries for automated analysis
Access to threat intelligence platforms for IP/domain reputation
Workflow
Step 1: Extract Raw Email Headers
# Export from Outlook: Open email > File > Properties > Internet Headers# Export from Gmail: Open email > Three dots > Show original# Export from Thunderbird: View > Message Source# If working with EML file from forensic imagecp /mnt/evidence/Users/suspect/AppData/Local/Microsoft/Outlook/phishing_email.eml \
/cases/case-2024-001/email/
# If working with PST file, extract individual messages
pip install pypff
python3 << 'PYEOF'
import pypff
pst = pypff.file()
pst.open("/cases/case-2024-001/email/outlook.pst")
root = pst.get_root_folder()
def extract_messages(folder, path=""):
for i in range(folder.get_number_of_sub_messages()):
msg = folder.get_sub_message(i)
headers = msg.get_transport_headers()
subject = msg.get_subject()
if headers:
filename = f"/cases/case-2024-001/email/msg_{i}_{subject[:30]}.txt"
with open(filename, 'w') as f:
f.write(headers)
for i in range(folder.get_number_of_sub_folders()):
extract_messages(folder.get_sub_folder(i))
extract_messages(root)
PYEOF
Step 2: Parse the Email Header Chain
# Parse headers using Python email library
python3 << 'PYEOF'
import email
from email import policy
with open('/cases/case-2024-001/email/phishing_email.eml', 'r') as f:
msg = email.message_from_file(f, policy=policy.default)
print("=== KEY HEADER FIELDS ===")
print(f"From: {msg['From']}")
print(f"To: {msg['To']}")
print(f"Subject: {msg['Subject']}")
print(f"Date: {msg['Date']}")
print(f"Message-ID: {msg['Message-ID']}")
print(f"Reply-To: {msg['Reply-To']}")
print(f"Return-Path: {msg['Return-Path']}")
print(f"X-Mailer: {msg['X-Mailer']}")
print(f"X-Originating-IP: {msg['X-Originating-IP']}")
print("\n=== RECEIVED HEADERS (bottom-up = chronological) ===")
received_headers = msg.get_all('Received')
if received_headers:
for i, header in enumerate(reversed(received_headers)):
print(f"\nHop {i+1}: {header.strip()}")
print("\n=== AUTHENTICATION RESULTS ===")
auth_results = msg.get_all('Authentication-Results')
if auth_results:
for result in auth_results:
print(result)
print(f"\nARC-Authentication-Results: {msg.get('ARC-Authentication-Results', 'Not present')}")
print(f"Received-SPF: {msg.get('Received-SPF', 'Not present')}")
print(f"DKIM-Signature: {msg.get('DKIM-Signature', 'Not present')}")
PYEOF
Step 3: Validate SPF, DKIM, and DMARC Records
# Extract the envelope sender domain
SENDER_DOMAIN="example-corp.com"# Check SPF record
dig TXT $SENDER_DOMAIN +short | grep "v=spf1"# Example: "v=spf1 include:_spf.google.com include:sendgrid.net ~all"# Check DKIM record (selector from DKIM-Signature header, e.g., "s=selector1")
DKIM_SELECTOR="selector1"
dig TXT ${DKIM_SELECTOR}._domainkey.${SENDER_DOMAIN} +short
# Check DMARC record
dig TXT _dmarc.${SENDER_DOMAIN} +short
# Example: "v=DMARC1; p=reject; rua=mailto:dmarc@example-corp.com; pct=100"# Verify the sending IP against SPF# Extract IP from first Received header
SENDING_IP="203.0.113.45"# Manual SPF check using python
python3 << 'PYEOF'
import spf # pip install pyspf
result, explanation = spf.check2(
i='203.0.113.45',
s='sender@example-corp.com',
h='mail.example-corp.com'
)
print(f"SPF Result: {result}")
print(f"Explanation: {explanation}")
# Results: pass, fail, softfail, neutral, none, temperror, permerror
PYEOF
# Check if sending IP is in known malicious IP lists# Query AbuseIPDB or VirusTotal
curl -s "https://api.abuseipdb.com/api/v2/check?ipAddress=${SENDING_IP}" \
-H "Key: YOUR_API_KEY" -H "Accept: application/json" | python3 -m json.tool
Step 4: Analyze Sender Domain and Infrastructure
# WHOIS lookup on sender domain
whois $SENDER_DOMAIN | grep -iE '(registrar|creation|expiration|registrant|nameserver)'# Check domain age (recently registered domains are suspicious)# DNS record investigation
dig A $SENDER_DOMAIN +short
dig MX $SENDER_DOMAIN +short
dig NS $SENDER_DOMAIN +short
# Reverse DNS on sending IP
dig -x $SENDING_IP +short
# Check for lookalike/typosquatting domains# Compare with legitimate domain using visual similarity
python3 << 'PYEOF'
import Levenshtein # pip install python-Levenshtein
legitimate = "microsoft.com"
suspicious = "micr0soft.com"
distance = Levenshtein.distance(legitimate, suspicious)
ratio = Levenshtein.ratio(legitimate, suspicious)
print(f"Edit distance: {distance}")
print(f"Similarity ratio: {ratio:.2%}")
if ratio > 0.8:
print("WARNING: Likely typosquatting/lookalike domain!")
PYEOF
# Check domain reputation on VirusTotal
curl -s "https://www.virustotal.com/api/v3/domains/${SENDER_DOMAIN}" \
-H "x-apikey: YOUR_VT_API_KEY" | python3 -m json.tool
# Check if the Reply-To differs from From (common phishing indicator)
python3 -c "
import email
with open('/cases/case-2024-001/email/phishing_email.eml') as f:
msg = email.message_from_file(f)
from_addr = email.utils.parseaddr(msg['From'])[1]
reply_to = email.utils.parseaddr(msg.get('Reply-To', msg['From']))[1]
if from_addr != reply_to:
print(f'WARNING: From ({from_addr}) != Reply-To ({reply_to})')
else:
print('From and Reply-To match')
"
Step 5: Examine Email Body and Attachments
# Extract URLs from email body
python3 << 'PYEOF'
import email
import re
from email import policy
with open('/cases/case-2024-001/email/phishing_email.eml', 'r') as f:
msg = email.message_from_file(f, policy=policy.default)
body = msg.get_body(preferencelist=('html', 'plain'))
if body:
content = body.get_content()
urls = re.findall(r'https?://[^\s<>"\']+', content)
print("=== URLs FOUND IN EMAIL BODY ===")
for url in set(urls):
print(f" {url}")
# Check for URL obfuscation (display text != href)
href_pattern = re.findall(r'<a[^>]*href=["\']([^"\']+)["\'][^>]*>(.*?)</a>', content, re.DOTALL)
print("\n=== HYPERLINK ANALYSIS ===")
for href, text in href_pattern:
display_url = re.findall(r'https?://[^\s<]+', text)
if display_url and display_url[0] != href:
print(f" MISMATCH: Display='{display_url[0]}' -> Actual='{href}'")
# Extract and hash attachments
print("\n=== ATTACHMENTS ===")
for part in msg.walk():
if part.get_content_disposition() == 'attachment':
filename = part.get_filename()
content = part.get_payload(decode=True)
import hashlib
sha256 = hashlib.sha256(content).hexdigest()
print(f" File: {filename}, Size: {len(content)}, SHA-256: {sha256}")
with open(f'/cases/case-2024-001/email/attachments/{filename}', 'wb') as af:
af.write(content)
PYEOF
# Submit attachment hashes to VirusTotal
# Submit URLs to URLhaus or PhishTank for reputation check
Key Concepts
Concept
Description
SPF (Sender Policy Framework)
DNS record specifying authorized mail servers for a domain
Policy framework combining SPF and DKIM for sender authentication
Received headers
Server-added headers showing each hop in the delivery chain (read bottom to top)
Return-Path
Envelope sender address used for bounce messages; may differ from From
Message-ID
Unique identifier assigned by the originating mail server
X-Originating-IP
Original sender IP address (added by some mail services)
Header forgery
Attackers can forge From, Reply-To, and other headers but not Received chains
Tools & Systems
Tool
Purpose
MXToolbox
Online email header analyzer and DNS lookup
dig/nslookup
DNS record queries for SPF, DKIM, DMARC verification
pyspf
Python SPF record validation library
dkimpy
Python DKIM signature verification library
PhishTool
Specialized phishing email analysis platform
VirusTotal
URL and file reputation checking service
AbuseIPDB
IP address reputation database
whois
Domain registration information lookup
Common Scenarios
Scenario 1: CEO Fraud / Business Email Compromise
The email claims to be from the CEO but Reply-To points to a Gmail address, SPF fails because the sending IP is not authorized for the spoofed domain, DKIM is missing, and the From domain is a lookalike (ceo-company.com vs company.com).
Scenario 2: Credential Harvesting Phishing
Email contains a link that displays "login.microsoft.com" but href points to a lookalike domain, the attachment is an HTML file containing a fake login page with credential exfiltration JavaScript, the sending domain was registered 3 days ago.
Scenario 3: Malware Delivery via Attachment
Email with an Office document attachment containing macros, the sender domain passes SPF but the account was compromised, DKIM signature is valid (sent from legitimate infrastructure), attachment SHA-256 matches known malware on VirusTotal.
Scenario 4: Spear Phishing with Legitimate Service
Attacker uses a legitimate email marketing service to send phishing, SPF and DKIM pass because the service is authorized, the phishing is in the content not the infrastructure, requires URL and content analysis rather than header authentication checks.
Output Format
Email Header Analysis Report:
Subject: "Urgent: Invoice Payment Required"
From: accounting@examp1e-corp.com (SPOOFED)
Reply-To: payments.urgent@gmail.com (MISMATCH)
Return-Path: <bounce@mail-server.xyz>
Date: 2024-01-15 09:23:45 UTC
Delivery Path (4 hops):
Hop 1: mail-server.xyz [203.0.113.45] -> relay1.isp.com
Hop 2: relay1.isp.com -> mx.target-company.com
Hop 3: mx.target-company.com -> internal-filter.target.com
Hop 4: internal-filter.target.com -> mailbox
Authentication:
SPF: FAIL (203.0.113.45 not authorized for examp1e-corp.com)
DKIM: NONE (no signature present)
DMARC: FAIL (p=none, no enforcement)
Indicators of Phishing:
- Lookalike domain (examp1e-corp.com vs example-corp.com, 96% similar)
- From/Reply-To mismatch
- Domain registered 2 days before email sent
- URL in body points to credential harvesting page
- Attachment: invoice.xlsm (SHA-256: a3f2...) - Known malware on VT
Risk Level: HIGH
