investigating-phishing-email-incident
Investigates phishing email incidents from initial user report through header analysis, URL/attachment detonation, impacted user identification, and containment actions using SOC tools like Splunk, Microsoft Defender, and sandbox analysis platforms. Use when a reported phishing email requires full incident investigation to determine scope and impact.
What this skill does
# Investigating Phishing Email Incident
## When to Use
Use this skill when:
- A user reports a suspicious email via the phishing report button or helpdesk ticket
- Email security gateway flags a message that bypassed initial filters
- Automated detection identifies credential harvesting URLs or malicious attachments
- A phishing campaign targeting the organization requires scope assessment
**Do not use** for spam or marketing emails without malicious intent — route those to email administration for filter tuning.
## Prerequisites
- Access to email gateway logs (Proofpoint, Mimecast, or Microsoft Defender for Office 365)
- Splunk or SIEM with email log ingestion (O365 Message Trace, Exchange tracking logs)
- Sandbox access (Any.Run, Joe Sandbox, or Hybrid Analysis) for URL/attachment detonation
- Microsoft Graph API or Exchange Admin Center for email search and purge operations
- URLScan.io and VirusTotal API keys
## Workflow
### Step 1: Extract and Analyze Email Headers
Obtain the full email headers (`.eml` file) from the reported message:
```python
import email
from email import policy
with open("phishing_sample.eml", "rb") as f:
msg = email.message_from_binary_file(f, policy=policy.default)
# Extract key headers
print(f"From: {msg['From']}")
print(f"Return-Path: {msg['Return-Path']}")
print(f"Reply-To: {msg['Reply-To']}")
print(f"Subject: {msg['Subject']}")
print(f"Message-ID: {msg['Message-ID']}")
print(f"X-Originating-IP: {msg['X-Originating-IP']}")
# Parse Received headers (bottom-up for true origin)
for header in reversed(msg.get_all('Received', [])):
print(f"Received: {header[:120]}")
# Check authentication results
print(f"Authentication-Results: {msg['Authentication-Results']}")
print(f"DKIM-Signature: {msg.get('DKIM-Signature', 'NONE')[:80]}")
```
Key checks:
- **SPF**: Does `Return-Path` domain match sending IP? Look for `spf=pass` or `spf=fail`
- **DKIM**: Is the signature valid? `dkim=pass` confirms the email was not modified in transit
- **DMARC**: Does the `From` domain align with SPF/DKIM domains? `dmarc=fail` indicates spoofing
### Step 2: Analyze URLs and Attachments
**URL Analysis:**
```python
import requests
# Submit URL to URLScan.io
url_to_scan = "https://evil-login.example.com/office365"
response = requests.post(
"https://urlscan.io/api/v1/scan/",
headers={"API-Key": "YOUR_KEY", "Content-Type": "application/json"},
json={"url": url_to_scan, "visibility": "unlisted"}
)
scan_id = response.json()["uuid"]
print(f"Scan URL: https://urlscan.io/result/{scan_id}/")
# Check VirusTotal for URL reputation
import vt
client = vt.Client("YOUR_VT_API_KEY")
url_id = vt.url_id(url_to_scan)
url_obj = client.get_object(f"/urls/{url_id}")
print(f"VT Score: {url_obj.last_analysis_stats}")
client.close()
```
**Attachment Analysis:**
```python
import hashlib
# Calculate file hashes
with open("attachment.docx", "rb") as f:
content = f.read()
md5 = hashlib.md5(content).hexdigest()
sha256 = hashlib.sha256(content).hexdigest()
print(f"MD5: {md5}")
print(f"SHA256: {sha256}")
# Submit to MalwareBazaar for lookup
response = requests.post(
"https://mb-api.abuse.ch/api/v1/",
data={"query": "get_info", "hash": sha256}
)
print(response.json()["query_status"])
```
Submit to sandbox (Any.Run or Joe Sandbox) for dynamic analysis of macros, PowerShell execution, and C2 callbacks.
### Step 3: Determine Campaign Scope
Search for all recipients of the same phishing email in Splunk:
```spl
index=email sourcetype="o365:messageTrace"
(SenderAddress="[email protected]" OR Subject="Urgent: Password Reset Required"
OR MessageId="<[email protected]>")
earliest=-7d
| stats count by RecipientAddress, DeliveryStatus, MessageTraceId
| sort - count
```
Alternatively, use Microsoft Graph API:
```python
import requests
headers = {"Authorization": f"Bearer {access_token}"}
params = {
"$filter": f"subject eq 'Urgent: Password Reset Required' and "
f"receivedDateTime ge 2024-03-14T00:00:00Z",
"$select": "sender,toRecipients,subject,receivedDateTime",
"$top": 100
}
response = requests.get(
"https://graph.microsoft.com/v1.0/users/[email protected]/messages",
headers=headers, params=params
)
messages = response.json()["value"]
print(f"Found {len(messages)} matching messages")
```
### Step 4: Identify Impacted Users (Who Clicked)
Check proxy/web logs for users who visited the phishing URL:
```spl
index=proxy dest="evil-login.example.com" earliest=-7d
| stats count, values(action) AS actions, latest(_time) AS last_access
by src_ip, user
| lookup asset_lookup_by_cidr ip AS src_ip OUTPUT owner, category
| sort - count
| table user, src_ip, owner, actions, count, last_access
```
Check if credentials were submitted (POST requests to phishing domain):
```spl
index=proxy dest="evil-login.example.com" http_method=POST earliest=-7d
| stats count by src_ip, user, url, status
```
### Step 5: Containment Actions
**Purge emails from all mailboxes:**
```powershell
# Microsoft 365 Compliance Search and Purge
New-ComplianceSearch -Name "Phishing_Purge_2024_0315" `
-ExchangeLocation All `
-ContentMatchQuery '(From:[email protected]) AND (Subject:"Urgent: Password Reset Required")'
Start-ComplianceSearch -Identity "Phishing_Purge_2024_0315"
# After search completes, execute purge
New-ComplianceSearchAction -SearchName "Phishing_Purge_2024_0315" -Purge -PurgeType SoftDelete
```
**Block indicators:**
- Add sender domain to email gateway block list
- Add phishing URL domain to web proxy block list
- Add attachment hash to endpoint detection block list
- Create DNS sinkhole entry for phishing domain
**Reset compromised credentials:**
```powershell
# Force password reset for impacted users
$impactedUsers = @("[email protected]", "[email protected]")
foreach ($user in $impactedUsers) {
Set-MsolUserPassword -UserPrincipalName $user -ForceChangePassword $true
Revoke-AzureADUserAllRefreshToken -ObjectId (Get-AzureADUser -ObjectId $user).ObjectId
}
```
### Step 6: Document and Report
Create incident report with full timeline, IOCs, impacted users, and remediation actions taken.
```spl
| makeresults
| eval incident_id="PHI-2024-0315",
reported_time="2024-03-15 09:12:00",
sender="attacker@evil-domain[.]com",
subject="Urgent: Password Reset Required",
url="hxxps://evil-login[.]example[.]com/office365",
recipients_count=47,
clicked_count=5,
credentials_submitted=2,
emails_purged=47,
passwords_reset=2,
domains_blocked=1,
disposition="True Positive - Credential Phishing Campaign"
| table incident_id, reported_time, sender, subject, url, recipients_count,
clicked_count, credentials_submitted, emails_purged, passwords_reset, disposition
```
## Key Concepts
| Term | Definition |
|------|-----------|
| **SPF (Sender Policy Framework)** | DNS TXT record specifying which mail servers are authorized to send on behalf of a domain |
| **DKIM** | DomainKeys Identified Mail — cryptographic signature proving email content was not altered in transit |
| **DMARC** | Domain-based Message Authentication, Reporting and Conformance — policy combining SPF and DKIM alignment |
| **Credential Harvesting** | Phishing technique using fake login pages to capture username/password combinations |
| **Business Email Compromise (BEC)** | Social engineering attack using compromised or spoofed executive email for financial fraud |
| **Message Trace** | O365/Exchange log showing email routing, delivery status, and filtering actions for forensic analysis |
## Tools & Systems
- **Microsoft Defender for Office 365**: Email security platform with Safe Links, Safe Attachments, and Threat Explorer for investigation
- **URLScan.io**: Free URL analysis service capturing screenshots, DOM, cookies, and network requests
- **Any.Run**: Interactive sandbox for detonating malicious files and URLs with real-time behRelated in Productivity
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