Web application server-side vulnerability testing method and device

By parsing web application pages to obtain key elements, deriving field matching rules, constructing semantic input samples, and executing them in a PHP interpreter environment, combined with snapshot recovery and feedback mechanisms, the problem of identifying complex vulnerabilities in PHP language applications is solved, achieving efficient vulnerability detection.

CN121000426BActive Publication Date: 2026-04-07NO 15 INST OF CHINA ELECTRONICS TECH GRP
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Patent Information

Application Number
CN202511085119.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-04
Publication Date
2026-04-07
Estimated Expiration
2045-08-04

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively identify complex server-side web vulnerabilities in PHP applications, especially those hidden in paths, permissions, template variables, or user-defined component processing. Traditional fuzzing and static analysis tools cannot meet practical needs.

Method used

By parsing web application pages to obtain key elements, deriving field matching rules, constructing semantic input samples, and executing them in a PHP interpreter environment, combined with snapshot recovery and feedback mechanisms, new paths are automatically discovered and mutation operations are performed, and execution is monitored to identify potential vulnerabilities.

Benefits of technology

It improves the credibility, reproducibility, and testing depth of vulnerability identification, effectively identifying various security vulnerabilities such as SQL injection and XSS attacks, thereby enhancing the security and reliability of web applications.

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Abstract

This application provides a method and apparatus for testing server-side vulnerabilities in web applications. It effectively uncovers potential vulnerabilities through intelligent analysis and feedback mechanisms. By parsing web application pages, extracting key elements, and deriving field matching rules based on server feedback, it generates semantic input samples that conform to the application logic. By comparing historical execution paths, it automatically discovers new paths and further explores potential deep-seated vulnerabilities through mutation operations. This method not only improves test coverage and depth but also dynamically optimizes test samples based on actual feedback, avoiding the blindness and inefficiency of traditional testing methods. This solution can effectively identify various security vulnerabilities in web applications, such as SQL injection and XSS attacks, enhancing the security and reliability of web applications and providing developers with more accurate and efficient vulnerability detection methods.
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