Dynamic Scan Adaptation for Web Application Security
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Solution Overview
Problem
Web applications are vulnerable to security threats due to the lack of effective real-time adaptation during security scans, leading to inefficiencies and resource consumption issues.
Innovation Solution
A scan system with a scan execution engine and a scan adaptation engine that dynamically adapts scan parameters and requests during execution based on real-time metrics, allowing for adjustments to configuration, attack surface detections, and resource usage to enhance efficiency and effectiveness without stopping the scan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional security scans are executed without real-time adaptation, then comprehensive security coverage is achieved, but resource consumption increases and scan efficiency decreases
Solution Approach 1:
The patent implements dynamic scan adaptation by continuously monitoring scan metrics during execution and adjusting scan parameters in real-time. The scan adaptation engine modifies scan requests, configuration settings, and execution speed dynamically based on observed application behavior and resource consumption patterns, transforming a static scan process into a dynamic one that optimizes efficiency while maintaining security coverage.
Solution Approach 2:
The system employs feedback mechanisms by monitoring scan metrics (response times, error rates, resource usage) during scan execution and using this information to adapt subsequent scan requests. The scan adaptation engine receives feedback from the monitored web application and adjusts scan parameters accordingly, creating a closed-loop control system that improves scan efficiency while managing resource consumption.
2Loss of energy
If scan parameters are adjusted during execution to improve efficiency, then resource consumption is reduced, but scan completeness may be compromised
Solution Approach 1:
The system dynamically adjusts scan parameters based on real-time conditions rather than using fixed configurations. The scan adaptation engine modifies scan intensity, request frequency, and test depth dynamically, increasing scan completeness when resources are available and reducing it when resource consumption becomes excessive, thereby maintaining reliability while managing resource usage.
Solution Approach 2:
The patent changes scan parameters (such as request rate, concurrency level, test depth) based on monitored metrics. When the application shows signs of stress or resource consumption exceeds thresholds, the system adjusts parameters to reduce load while maintaining essential security testing, thus preserving scan completeness within acceptable resource constraints.
3Productivity
If real-time monitoring and adaptation mechanisms are implemented, then scan efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments the scan functionality into distinct modules: a scan execution engine for performing scans, a scan adaptation engine for real-time adjustments, and a monitoring component for collecting metrics. This segmentation allows each component to have a specific responsibility, reducing overall system complexity while enabling efficient real-time adaptation through coordinated operation of specialized subsystems.
Solution Approach 2:
The scan adaptation engine acts as an intermediary between the scan execution engine and the monitored web application. It receives scan metrics from the application, processes this information, and generates adapted scan requests that are then sent back to the execution engine. This intermediary layer simplifies the control logic by centralizing the adaptation decisions and reducing direct complexity in the execution engine.
4Loss of time
If scan requests are sent at high speed to improve productivity, then scan completion time is reduced, but resource consumption and risk of application overload increase
Solution Approach 1:
The system dynamically adjusts the rate at which scan requests are sent based on real-time monitoring of application response times and resource usage. When the application handles requests efficiently, the system increases request speed to reduce scan completion time. When signs of overload appear, the system automatically reduces the request rate, preventing application overload while maintaining optimal scan speed.
Solution Approach 2:
The scan system uses feedback from application performance metrics to control request sending speed. Monitored metrics such as response time, error rates, and resource consumption feed back to the scan adaptation engine, which adjusts the scan request rate accordingly. This feedback control prevents application overload by reducing request speed when the application shows signs of stress, while maximizing scan speed when the application can handle the load.
Data Source
AI summary
In some examples, a system includes a scan execution engine and a scan adaptation engine. The scan execution engine may execute a scan of a web application hosted on a web host. During scan execution, the scan adaptation engine may adapt a subsequent scan portion for later execution based on a scan metric received from a monitoring agent that monitors the web application, the web host, or both.