> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/analytics-alerts/alerts-by-name/well-known-brand-in-sender-headers-with-header-inconsistencies.md).

# Well-known brand in sender headers with header inconsistencies

### Synopsis

| Field                | Value                                         |
| -------------------- | --------------------------------------------- |
| Activation Period    | 14 Days                                       |
| Training Period      | 30 Days                                       |
| Test Period          | N/A (single event)                            |
| Deduplication Period | 1 Day                                         |
| Required Data        | Microsoft 365 Emails                          |
| Detection Modules    | Email                                         |
| Detector Tags        | Brand Impersonation                           |
| ATT\&CK Tactic       | Stealth (TA0005)                              |
| ATT\&CK Technique    | Social Engineering: Impersonation (T1684.001) |
| Severity             | Informational                                 |

### Description

Sender headers include a well-known brand with header inconsistencies indicating possible impersonation.

### Attacker's Goals

Impersonate known legitimate brands or other technological entities to trick recipients into disclosing information or executing malicious code unwillingly.

### Investigative actions

* Identify the specific emails responsible for the accumulation of these alerts.
* Review their headers and content for patterns or anomalies.
* Assess the email's context and attack techniques to determine the potential risk.
* Review the email headers and metadata of each flagged email to identify potential spoofing techniques or unusual routing patterns.
* Analyze any URLs or attachments in a secure sandbox environment to detect possible malware or phishing attempts.
* Engage potentially affected users to understand if any actions were taken in response to these emails, which could increase the overall risk.
* Document and escalate findings in case this is a broader phenomenon.


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