MPS: Email Hijacking Detection Using NLP and IOCs

Because the emails originate from a trusted account, traditional authentication controls alone may not be sufficient to identify the threat.

Mail Protection Service (MPS) addresses this challenge through advanced Email Hijacking Detection, combining Natural Language Processing (NLP) with traditional Indicators of Compromise (IOCs) to identify suspicious email activity in real time.

Beyond Traditional Email Security

Traditional email security technologies focus primarily on authentication and reputation checks, such as SPF, DKIM, and DMARC validation. While these controls are essential, they may not detect attacks originating from compromised accounts that are already authorized to send email.

To address this gap, Mail Protection Service analyzes both the technical characteristics of a message and its content, providing a more comprehensive assessment of risk.

Natural Language Processing (NLP) Analysis

Using NLP, MPS examines the language, tone, and intent of email messages to identify behaviors commonly associated with account takeover and fraud attempts.

Examples include:

• Unusual requests for urgent payments or wire transfers.
• Sudden changes in communication style.
• Requests for sensitive information or credentials.
• Language intended to create pressure, urgency, or secrecy.
• Messages that differ significantly from the sender's normal writing patterns.

By understanding the context of a message rather than simply looking for keywords, NLP helps identify sophisticated attacks that may bypass traditional filtering techniques.

Indicators of Compromise (IOCs)

In addition to content analysis, MPS evaluates multiple technical indicators that may suggest a compromised account:

• Logins from unusual geographic locations.
• Impossible travel scenarios.
• New or suspicious forwarding rules.
• Unusual sending volumes or patterns.
• Changes to mailbox permissions.
• Communication with known malicious domains or IP addresses.
• Previous phishing or malware activity associated with the sender.

These indicators provide valuable evidence that an account may have been taken over by an attacker.

Combining Content and Behavioral Intelligence

The real strength of Mail Protection Service lies in the combination of NLP and IOC analysis. A message requesting an urgent payment may not be suspicious on its own. However, if it is sent from a mailbox that recently authenticated from an unusual location and created a new forwarding rule, the overall risk becomes significantly higher.

By correlating multiple signals, MPS can distinguish legitimate business communication from potentially malicious activity with greater accuracy and fewer false positives.

Faster Detection, Reduced Risk

When suspicious behavior is detected, Mail Protection Service can automatically alert security teams, apply warning banners, quarantine messages, or trigger additional investigation workflows. This enables organizations to respond quickly before attackers can cause financial loss, data exposure, or reputational damage.

Conclusion

Email hijacking attacks continue to evolve, making traditional security controls alone insufficient for modern organizations. By combining Natural Language Processing, behavioral analytics, and technical Indicators of Compromise, Mail Protection Service provides a powerful layer of protection against account takeover and Business Email Compromise attacks. The result is faster detection, improved visibility, and stronger protection for users and business communications.