Analysis of Malicious JavaScript

Title: A Dual Approach for Decoding and Analyzing Malicious JavaScript Code


This research paper presents a comprehensive approach to detecting and decoding malicious code within JavaScript, employing both manual and automated methods. The work is categorized into two primary sections:

  1. Manual Approach: This involves a meticulous, step-by-step process to search, identify, scan, and interpret JavaScript on a webpage. By closely analyzing each script’s contents and characteristics, this method aims to discern whether a given script is malicious. Key stages include identifying the total number of JavaScripts on a page, manually scanning them for suspicious functionality, locating the scripts in the page, and assessing and alerting on the threat level.
  2. Automated Approach: Building on the manual process, the automated approach utilizes custom-built programs to conduct the same tasks with more efficiency. Two main programs are developed:
    1. Line Checker Program: Scans lines to search for script tags, identifying the total number of scripts.
    2. Script Processing Program: Performs in-depth analysis of each script, matching patterns with known malicious behaviors, and generating alerts and notifications if potential harm is detected.

The combination of these two approaches offers a robust methodology for understanding and countering JavaScript-based threats. The manual analysis provides a detailed understanding of the obfuscation techniques used by attackers, while the automated process leverages this understanding to quickly and accurately identify potential threats.

The paper elaborates on the methodologies and algorithms used, presenting both a textual explanation and flow diagrams to elucidate the process. The research has practical applications in malware detection, web security, and contributes valuable insights into the complex landscape of JavaScript threats.

By merging human-driven insights with algorithmic efficiency, this work stands as a significant contribution to the field of cybersecurity, offering a nuanced and effective strategy to detect and decode malicious JavaScript.