Vulnerability Remediation Complexity Scoring for Patch Prioritization
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Solution Overview
Problem
Existing patch management strategies fail to efficiently prioritize and apply patches due to the complexity of remediation, leading to unpatched systems and increased security risks, as they do not account for the variability in vulnerability remediation costs and potential disruptions.
Innovation Solution
An automated system that assigns a vulnerability remediation complexity (VRC) score to prioritize patches based on remediation cost, focusing on high-severity vulnerabilities with lower remediation costs first, considering factors like registry modifications, system configuration changes, and historical data to ensure successful patch application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patches are applied to fix security vulnerabilities, then security risk is reduced, but system availability and operational continuity are disrupted
Solution Approach 1:
The system performs preliminary assessment of patch complexity and remediation cost before applying patches. By evaluating factors such as reboot requirements, configuration changes, and historical success rates in advance, the system can prioritize and schedule patches during maintenance windows or low-activity periods, thereby reducing disruption to system availability while still achieving security risk reduction
Solution Approach 2:
The system changes the parameter of patch prioritization from simple vulnerability severity to a composite metric that includes remediation cost and complexity. This allows the system to select patches that achieve security improvements with minimal operational impact, effectively balancing security risk reduction with system availability
2Reliability
If comprehensive patch management is implemented across numerous systems, then security coverage is improved, but management complexity increases
Solution Approach 1:
The system enables automated self-service patch management by using agents deployed on each system to automatically report vulnerability status, receive appropriate patches, and apply them according to prioritization algorithms. This automation reduces manual management complexity while maintaining comprehensive security coverage across numerous systems
Solution Approach 2:
The system transforms the management approach by introducing a complexity score parameter that automatically evaluates and ranks patches. This parameter-driven approach simplifies decision-making for managing numerous systems by providing an objective metric for prioritization, thereby reducing management complexity while maintaining comprehensive coverage
3Reliability
If high-severity vulnerabilities are prioritized for patching, then security risk reduction is improved, but remediation cost and operational impact increase
Solution Approach 1:
The system changes the prioritization parameter from vulnerability severity alone to a composite metric that balances severity with remediation cost and complexity. This allows the system to identify and prioritize patches that provide the best security return on investment, reducing overall remediation cost while maintaining effective security risk reduction
Solution Approach 2:
The system incorporates historical feedback data about patch application success rates and operational impact to refine prioritization decisions. By learning from past patching experiences, the system can predict and avoid high-cost remediation scenarios while still addressing critical security risks efficiently
4Reliability
If frequent patching is performed to address new vulnerabilities, then security posture is improved, but system stability and operational continuity are disrupted
Solution Approach 1:
The system performs preliminary stability assessment before applying patches by evaluating system state, recent changes, and criticality of affected services. This preliminary action allows the system to defer non-critical patches until more stable periods, maintaining system stability while still improving security posture through targeted patching
Solution Approach 2:
The system introduces a stability risk parameter that evaluates the potential impact of patching on system stability. By incorporating this parameter into prioritization, the system can balance security improvements with operational stability, scheduling patches during periods of lower system activity or when stability risk is minimized
Data Source
AI summary
The subject matter herein provides an automated system and method for software patch management that ranks patches at least in part according to a score indicative of a complexity (e.g., cost) of remediating a vulnerability. This score is sometimes referred to herein as a vulnerability remediation complexity (VRC) score. A VRC score provides an objective measure by which an organization can determine which patches are most likely to be successfully applied, thus enabling implementation of a patching strategy that preferentially applies most critical, but less impact (in terms of remediation cost) patches first to remediate as must risk as possible as quickly as possible. Thus, for example, the approach herein enables the patching to focus on vulnerabilities of highest severity and small remediation cost over those, for example, representing lower severity and higher remediation cost.