Usage-Based Fuzz Testing for User Input Fields
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Solution Overview
Problem
Fuzz testing is time-consuming and difficult to automate due to the large number of possibilities that need to be explored and the need for human intelligence to determine a valid starting point, especially when identifying vulnerabilities in user input fields of running applications in a production environment.
Innovation Solution
A computer-implemented method that monitors and ranks user input fields based on actual usage data, selectively performs fuzz testing on high-priority fields, and dynamically adapts to changes in usage patterns, using spare resources to generate fuzzed inputs that mimic real user interactions and environmental contexts to identify and mitigate vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fuzz testing is performed on all user input fields, then security vulnerability detection coverage is improved, but resource consumption and testing time increase significantly
Solution Approach 1:
The patent segments the set of all user input fields into different priority groups based on actual usage data. High-priority fields that are frequently used are selected for fuzz testing, while low-priority fields are excluded. This segmentation allows the system to focus testing resources on the most critical fields, maintaining security coverage while reducing overall testing time and resource consumption.
2Reliability
If fuzz testing is performed on all user input fields, then security vulnerability detection coverage is improved, but resource consumption increases
Solution Approach 1:
The system segments user input fields into priority groups using usage data analysis. By selecting only high-priority fields for fuzz testing, the patent reduces the computational resources, processor cycles, and memory required for testing while maintaining adequate security coverage on the most critical fields.
Solution Approach 2:
The patent applies local quality by allocating testing resources differently based on the specific characteristics of each user input field. High-priority fields receive intensive fuzz testing resources, while low-priority fields receive minimal or no testing resources. This non-uniform resource allocation optimizes the balance between security coverage and resource consumption.
3Reliability
If traditional fuzz testing is used, then vulnerability detection capability is maintained, but automation difficulty increases due to need for human intelligence
Solution Approach 1:
The patent implements feedback by using actual usage data from production environments to automatically determine which user input fields should be tested. The system continuously monitors usage patterns and uses this feedback to dynamically select test fields, eliminating the need for manual human analysis while maintaining effective vulnerability detection capability.
Solution Approach 2:
The system performs self-service by automatically analyzing its own usage data to identify high-priority user input fields that require fuzz testing. This self-directed approach enables full automation of the test selection process, removing the dependency on human intelligence to determine valid starting points for testing.
4Productivity
If usage-based field selection is implemented, then resource utilization is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing usage statistics for each user input field before fuzz testing begins. The system analyzes usage data in advance to determine field priorities, creating a ready-to-use selection criteria that simplifies the actual testing process and reduces real-time computational complexity.
Data Source
AI summary
Improved utilization of spare resources for fuzz testing is provided. A production environment that includes a plurality of running applications having a plurality of user input fields is monitored over a period of time for consumer use. Actual usage data for the plurality of user input fields are determined during the period of time. Each user input field in the plurality of user input fields is ranked for fuzz testing based on, at least in part, the actual usage data corresponding to each respective user input field during the period of time. The fuzz testing is selectively performed on a portion of the plurality of user input fields based on user input field rankings.