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

# 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