Browser Extension DOM Analysis for Phishing Detection
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Solution Overview
Problem
Current methods for detecting phishing attempts, such as blacklisting and whitelisting, are ineffective against sophisticated spoofing attacks that mimic legitimate email sources, particularly for businesses with extensive online presence, as they often require email opening to verify legitimacy, exposing users to potential intrusion.
Innovation Solution
Implementing a web browser extension that uses document object model (DOM) elements to compare email links with previous transmission characteristics, such as timestamps and file sizes, stored in an email log database, to verify the authenticity of emails before they are opened, generating alerts for potential malicious content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blacklists or whitelists are used to block or allow emails from known sources, then common phishing attempts can be prevented, but sophisticated spoofing attacks with minor variations in email addresses or domains can bypass these measures
Solution Approach 1:
The system performs preliminary analysis of email characteristics (DOM elements, links, metadata) before the user opens the email. By pre-screening emails and comparing them against known legitimate transmission patterns, the system detects phishing attempts before they can compromise the user, resolving the contradiction by maintaining high detection accuracy while adapting to subtle spoofing variations through proactive analysis rather than reactive blocking.
Solution Approach 2:
The system introduces an intermediary screening layer between the email and the user that analyzes DOM elements and compares them against legitimate transmission characteristics. This intermediary mechanism bridges the gap between simple blacklist/whitelist methods and sophisticated spoofing detection, enabling the system to maintain reliability while adapting to subtle variations by mediating the interaction between email content and user exposure.
2Measurement precision
If users open emails to verify legitimacy, then they can determine if the source is authentic, but they expose themselves to potential intrusion and attacks
Solution Approach 1:
The system performs verification actions before the user opens the email by analyzing DOM elements, links, and metadata in advance. This preliminary verification maintains measurement precision by accurately assessing email legitimacy while eliminating the need for users to open potentially malicious emails, thus preventing exposure to intrusion while preserving verification accuracy.
Solution Approach 2:
The system acts as an intermediary that performs the verification function between the email and the user. By analyzing email characteristics and comparing them against legitimate patterns, the intermediary provides verification accuracy without requiring user interaction with potentially harmful content, thereby maintaining precision while eliminating exposure to intrusion.
3Ease of manufacture
If traditional screening methods are used, then they are simple to implement, but they fail to detect subtle spoofing attacks that mimic legitimate email sources
Solution Approach 1:
The system replaces simple mechanical blacklist/whitelist matching with a more sophisticated analysis mechanism that examines DOM elements, links, and metadata. This substitution maintains ease of implementation through automated browser extension integration while dramatically improving detection effectiveness by analyzing multiple characteristics rather than relying on simple string matching, thus resolving the contradiction between simplicity and reliability.
Data Source
AI summary
Methods, media and systems for screening content for malicious content in a web browser are disclosed. Document object model (DOM) elements are retrieved from the content displayed in the web browser. A link to visit a web site included in the DOM elements is identified. The identified link is compared to a list of permitted sources. Information is scanned to determine whether the information matches records of content transmitted by a primary source among the permitted sources. An alert is generated after determining a mismatch between the information in the DOM elements and records of content transmitted by the primary source.