Web Application Security Scanner Integrating Human Expertise
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Solution Overview
Problem
Existing methods struggle to effectively and automatically assess security vulnerabilities in complex web applications, as they require manual evaluation and lack a systematic way to incorporate human insights into automated testing processes.
Innovation Solution
A system that allows for gathering human insights on potential security vulnerabilities and structures data storage to support these insights, enabling later analysis by both humans and computers, including the ability to run scripted tests, record results, and accept custom test parameters for automated scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated testing is used to scan web applications for security vulnerabilities, then productivity increases, but measurement precision deteriorates because automated systems cannot effectively assess complex vulnerabilities without human insight
Solution Approach 1:
Human experts perform preliminary vulnerability assessments and document their findings, methodologies, and insights in a structured knowledge base before automated scanning. This preliminary human analysis creates a foundation of accurate vulnerability patterns that the automated system can then replicate and execute at scale, maintaining both speed and accuracy
Solution Approach 2:
A knowledge base acts as an intermediary between human expert insights and automated scanning systems. It captures, structures, and stores human expertise in a format that automated tools can query and apply, serving as a bridge that transfers human intelligence to machine execution without requiring continuous human involvement in each scan
2Measurement precision
If manual evaluation is used to assess security vulnerabilities, then measurement precision improves, but productivity deteriorates due to the time-consuming nature of manual analysis
Solution Approach 1:
Human experts perform preliminary vulnerability assessments and document their findings, methodologies, and insights in a structured knowledge base before automated scanning. This preliminary human analysis creates a foundation of accurate vulnerability patterns that the automated system can then replicate and execute at scale, maintaining both speed and accuracy
Solution Approach 2:
The system copies human expert vulnerability assessment methodologies and insights into the knowledge base, then replicates these proven effective analysis patterns through automated scanning. Instead of requiring experts to manually evaluate each vulnerability instance, the system copies and applies their established assessment frameworks automatically across multiple targets
3Reliability
If comprehensive code review and file permission verification are performed, then reliability improves, but device complexity increases making it impractical for complex web applications
Solution Approach 1:
The system extracts specific vulnerability assessment patterns from comprehensive code reviews and isolates them into discrete, manageable knowledge base entries. Rather than attempting to review entire codebases manually, it extracts and stores specific vulnerability indicators, attack patterns, and assessment criteria that can be applied automatically to relevant sections of complex applications
Solution Approach 2:
The security assessment process is segmented into discrete vulnerability types and patterns, each captured as separate knowledge base entries. This segmentation allows the automated system to target specific vulnerability classes independently, making the overall assessment of complex applications manageable by breaking down the monolithic review process into modular, reusable components
Data Source
AI summary
An apparatus and method of managing vulnerability testing of a web application is provided for running a set of one or more scripted tests against a web application, recording results of the one or more scripted tests, providing an interface for a human evaluator to review the recorded results, and accepting from the human evaluator custom test parameters based on observations of the recorded results, wherein custom test parameters include at least one context usable by a future tester in deciding whether to run the custom test, and also includes at least one instruction for automatically running custom test steps of the custom test.