Offline Instance Security Testing for Web Applications
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Solution Overview
Problem
Traditional security testing of web products often disrupts the operation of released applications and fails to comprehensively cover all potential vulnerabilities, as it is challenging to test online products without affecting their stability and cannot easily detect new security threats post-release.
Innovation Solution
A method and system that generate malicious requests based on real-time user requests, which are sent to an offline instance of the target application to simulate malicious actions, allowing for security testing without affecting the online application, and determining the security level based on the offline instance's response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If security testing is directly performed on the online web product, then security vulnerabilities can be detected, but the operation stability of the web product is affected
Solution Approach 1:
The system segments the web product into an online instance (for normal operation) and an offline instance (for security testing). By dividing the testing target from the operational target, security vulnerabilities can be detected on the offline instance without affecting the stability of the online instance.
Solution Approach 2:
The system creates an offline instance that copies the structure and functionality of the online web product. This copy is used for security testing, allowing comprehensive vulnerability detection while the original online product continues to operate normally without disruption.
2Measurement precision
If traditional security testing methods are used, then some vulnerabilities can be detected, but comprehensive coverage of all potential vulnerabilities cannot be achieved
Solution Approach 1:
The system dynamically generates malicious requests based on real user requests and behavioral patterns. Instead of using static, pre-defined test cases, the testing mechanism adapts to actual usage scenarios, enabling comprehensive coverage of potential vulnerabilities across different attack vectors.
Solution Approach 2:
The system incorporates feedback mechanisms where responses from the offline instance are analyzed to generate improved malicious requests. This iterative feedback loop allows the testing system to learn from each interaction and progressively detect more sophisticated vulnerabilities.
Data Source
AI summary
Implementations of the present disclosure relate to security testing based on user request. According to the method, a first request for a target application is received from a first user. A first malicious request is generated by modifying the first request, wherein the first malicious is associated with a malicious action on the target application. The first malicious request is sent to an offline instance of the target application. A first security level of the target application against the malicious action is determined based on a first response generated by the offline instance in response to the first malicious request. In other implementations, a system and a computer program product for process tracking are disclosed.