Network Device Risk Scoring Using Multi-Source Vulnerability Data
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Solution Overview
Problem
Current solutions for assessing device risk in network environments are inadequate, often leading to overlooked vulnerabilities due to human error, incomplete data, and a lack of consideration for factors like vulnerability age, brute force attack indicators, and device popularity.
Innovation Solution
A data-driven method for calculating risk scores for network devices, incorporating factors such as CVE data, device popularity, reachability, and dynamic operational characteristics, using APIs and NLP to gather comprehensive data for accurate risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking and analysis of vulnerabilities is used, then human error and time consumption increase, but comprehensive analysis can be performed
Solution Approach 1:
The patent introduces an automated risk assessment system that acts as an intermediary between vulnerability data sources and security analysts. This system automatically collects vulnerability data from multiple sources, calculates risk scores using predefined methodologies, and presents results in a standardized format, thereby eliminating manual tracking while maintaining comprehensive analysis capabilities
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated computational systems. The risk assessment engine automatically processes vulnerability data, applies scoring methodologies, and generates risk evaluations without human intervention, substituting the mechanical manual tracking process with an automated information processing system
2Productivity
If vulnerability scanners are used, then automated identification is achieved, but holistic risk assessment is neglected
Solution Approach 1:
The patent merges multiple data sources including vulnerability scanners, threat intelligence feeds, asset inventory systems, and security event logs into a unified risk assessment framework. This combination allows the system to maintain automated identification efficiency while achieving holistic risk assessment by integrating diverse information sources that individual scanners cannot provide alone
Solution Approach 2:
The risk assessment system is designed with multi-functionality to perform various assessment tasks including vulnerability scanning, threat analysis, risk scoring, and prioritization. This universal system can adapt to different assessment requirements and data sources, providing comprehensive risk evaluation beyond the capabilities of specialized single-function vulnerability scanners
3Speed
If SIEM systems are used, then real-time security event detection is achieved, but a priori risk assessment of individual devices is limited
Solution Approach 1:
The patent segments the risk assessment process into device-specific evaluations that can be individually customized. Each device receives a tailored risk assessment based on its unique characteristics, asset criticality, and specific vulnerability profile, rather than applying uniform real-time monitoring rules. This segmentation enables precise individual device assessment while maintaining overall system-wide security monitoring
Data Source
AI summary
Systems and methods for risk assessment of network devices are disclosed herein. In particular, embodiments may determine risk scores for devices within a network that are highly individualized to each network device by leveraging data from a number of data sources. These data sources may include search results or the determination of network device data associated with the vulnerabilities, weaknesses, configuration errors or related conditions affecting each device or device type, ensuring a rich and pertinent set of data for risk score determination.