Vulnerability Relevance Profiling to Cut Security False Alarms
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Solution Overview
Problem
Existing vulnerability checks in security-relevant products generate numerous false alarms due to the lack of information about specific conditions required for vulnerability exploitation, leading to inefficient manual effort in identifying relevant vulnerabilities.
Innovation Solution
A method utilizing a terms specification, product profile, and vulnerability profile to automatically ascertain the relevance of vulnerabilities by natural language processing, comparing product and vulnerability descriptions, and calculating similarity metrics to filter out false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a vulnerability database is compared with a software bill of materials to check for known vulnerabilities, then security coverage is improved, but the number of false alarms increases
Solution Approach 1:
The vulnerability assessment process is segmented into multiple stages: initial vulnerability identification from the database, followed by relevance filtering using product-specific information (product profile, software configuration, attack possibility assessment). This segmentation allows comprehensive security coverage while systematically eliminating false alarms through progressive filtering criteria.
Solution Approach 2:
A relevance assessment mechanism acts as an intermediary between the vulnerability database and the final security evaluation. This intermediary evaluates each vulnerability against product-specific criteria (product profile, software configuration, attack possibility) to determine actual relevance, thereby reducing false alarms while maintaining security coverage.
2Measurement precision
If all reported vulnerabilities are analyzed manually to determine relevance, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The system performs self-service by automatically assessing vulnerability relevance using predefined criteria (product profile, software configuration, attack possibility evaluation). The system autonomously filters and prioritizes vulnerabilities without requiring manual analysis of each item, thereby maintaining high accuracy while significantly improving checking efficiency.
Solution Approach 2:
The assessment process uses parameter changes by evaluating multiple dimensions (product profile matching, software configuration alignment, attack possibility conditions) to dynamically determine vulnerability relevance. This multi-parameter approach enables automated accurate assessment without manual intervention.
3Measurement precision
If detailed product information is collected to assess vulnerability relevance, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The product profile serves as a universal data structure that consolidates multiple product-specific information elements (software components, configurations, versions). This multi-functional profile enables comprehensive relevance assessment across different vulnerability types without requiring separate complex systems for each information type.
Data Source
AI summary
A method for ascertaining a relevance of security-relevant vulnerabilities of a product. The method includes the following steps which are carried out automatically: providing a terms specification which includes terms for specifying the vulnerabilities; providing a product profile of the product, which specifies the product on the basis of the terms in the terms specification; providing at least one vulnerability profile for the particular vulnerability, which specifies the vulnerability on the basis of the terms in the terms specification; ascertaining the relevance of the particular vulnerability for the product on the basis of a processing of the product profile and of the vulnerability profile.