Web Content Security Module for Malicious Steganographic Code
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional security software is ineffective in detecting and disabling malicious steganographic code embedded in web content, such as HTML, JavaScript, and media files, which can be covertly incorporated into unused portions or encoded within files, making it difficult to detect and render them unusable by bots.
Innovation Solution
A security module processes web content by modifying unused portions, renaming variables, adding characters, and rearranging segments to corrupt malicious code, while maintaining the functionality of the content, thereby rendering the malicious code unusable by bots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security software is used to detect malicious code, then the system is simple and easy to operate, but it cannot detect malicious steganographic code hidden in web content
Solution Approach 1:
The patent introduces a security module as an intermediary component that sits between the web content and the user's browser. This module intercepts web content, processes it through multiple analysis techniques (static analysis, dynamic analysis, sandboxing), and delivers sanitized content to the browser. The intermediary handles the complexity of malicious code detection and neutralization, protecting the user system while maintaining operational simplicity.
Solution Approach 2:
The security module divides the detection and neutralization process into multiple independent segments: static analysis of web content, dynamic execution in sandboxed environments, pattern matching against known malicious signatures, and behavioral analysis. Each segment handles specific aspects of detection, allowing the system to process different types of malicious code through appropriate specialized techniques rather than a monolithic approach.
2Adaptability or versatility
If malicious steganographic code is embedded in web content, then the web content can function normally, but the malicious code becomes difficult to detect by security software
Solution Approach 1:
The security module employs dynamic analysis techniques that execute web content in controlled sandboxed environments to observe actual runtime behavior. Instead of relying solely on static patterns, the system monitors dynamic characteristics such as network connections, file system modifications, and process creation during execution. This dynamic approach detects steganographic code that attempts to hide by appearing benign in static analysis but exhibits malicious behavior when executed.
Solution Approach 2:
The system implements feedback loops where results from static analysis, dynamic analysis, and pattern matching continuously inform and adjust each other. When static analysis identifies suspicious patterns, the system increases scrutiny during dynamic execution. When dynamic behavior deviates from expected patterns, the system retroactively re-examines the static content with new hypotheses. This feedback mechanism progressively narrows down and identifies steganographic code that evades initial detection.
3Reliability
If security software processes all web content to detect malicious code, then detection thoroughness is improved, but processing time and system performance deteriorate
Solution Approach 1:
The security module applies partial processing to most web content and excessive (full) processing only when needed. It first performs lightweight static analysis on all content to identify obviously malicious patterns, then applies more intensive dynamic analysis and sandboxing only to content that triggers suspicion thresholds. This selective approach processes the majority of benign content quickly while maintaining thorough detection capability for suspicious content.
Solution Approach 2:
Different levels of security processing are applied to different portions of web content based on their risk characteristics. Headlines and metadata receive minimal processing, while script sections and embedded content receive intensive analysis. The system dynamically adjusts processing depth based on local characteristics of each content segment, such as file type, source reputation, and detected patterns, rather than applying uniform processing to all content.
Data Source
AI summary
A computer-implemented method for processing web content may comprise receiving web content encoded with malicious steganographic code. Before presenting the web content, the method may comprise modifying the web content to create modified content such that information conveyed by the malicious steganographic code is at least partially corrupted in the modified content. Additionally, a functionality of the modified content may be at least substantially similar to a functionality of the web content following modification of the web content to create the modified content. Various other methods, computer-readable media, and systems are also disclosed.