Out-of-Office Reply Blocking for Malicious Email Detection
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Solution Overview
Problem
Existing email systems fail to prevent the exposure of internal architecture information and links to malicious email senders, even when out-of-office replies are generated, as they do not effectively block identifying information and links from being sent to originators of malicious emails without interrupting the intended use of these replies.
Innovation Solution
A method and system that automatically identifies malicious emails by scanning parameters such as SMTP mail from and return path, evaluating the email travel path, analyzing the email domain, and identifying DKIM Signatures and X-UIDL fields, and blocks out-of-office replies if the email is determined to be malicious based on a calculated score exceeding a threshold value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If out of office automatic replies are generated to respond to external emails, then email communication efficiency is improved, but internal architecture information and identifying links are exposed to malicious senders
Solution Approach 1:
The system performs preliminary scanning and analysis of incoming emails before generating out-of-office replies. It evaluates multiple parameters including SMTP headers, email travel path, domain reputation, and DKIM signatures to pre-determine if an email is malicious, preventing information exposure before it occurs
Solution Approach 2:
The system introduces an intermediary security evaluation layer between the incoming email and the out-of-office reply generation. This intermediary analyzes email parameters and acts as a gatekeeper, allowing legitimate emails to receive automatic replies while blocking malicious ones, thus protecting internal information without compromising communication efficiency
2Reliability
If email parameters are scanned and analyzed to identify malicious emails, then security against malicious emails is improved, but system complexity and processing time increase
Solution Approach 1:
The security scanning system is segmented into multiple independent evaluation modules, each responsible for analyzing specific email parameters such as SMTP headers, email travel path, domain analysis, and DKIM signatures. This segmentation allows the system to process different aspects of email security separately, making the complex task more manageable and maintainable
Solution Approach 2:
The system creates a universal email evaluation framework that can assess multiple security parameters through a single integrated process. The same evaluation mechanism handles diverse parameters including SMTP mail from/return path, email travel path evaluation, domain analysis, DKIM signature verification, and X-UIDL field identification, reducing overall system complexity through consolidation
3Measurement precision
If multiple email parameters are evaluated and scored to determine malicious emails, then accuracy in identifying malicious emails is improved, but processing time and computational resources increase
Solution Approach 1:
The system transforms multiple email security parameters into a unified scoring mechanism. By converting diverse parameters (SMTP headers, travel path, domain reputation, DKIM signatures) into a common evaluation scale, the system enables efficient comparison and decision-making, balancing accuracy with processing speed
Data Source
AI summary
Systems and methods are provided for determining if an e-mail originating from an external source is deemed malicious and thereby preventing an out of office e-mail reply. One example method includes receiving, at a computing device of a service provider, an e-mail identified as originating from an external source, scanning the e-mail to identify at least one parameter only when an out of office reply is setup by a recipient of the e-mail, comparing the at least one scanned parameter to a set of known parameters, calculating a score of the e-mail based on the comparison of the at least one parameter to a set of known parameters, determining the e-mail to be a malicious e-mail if the score exceeds a threshold value and blocking an out of office reply based on the threshold value.