Analyzing Email Headers For Phishing Investigation

# 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

## 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

### Step 1: Extract Raw Email Headers

```bash
# 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 image
cp /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

```bash
# 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

```bash
# Extract the envelope sender domain
SENDER_DOMAIN="example-corp.com"

# Check SPF record
dig T