Cloud Data Risk Scoring for Cybersecurity Remediation Prioritization
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Solution Overview
Problem
Organizations face challenges in prioritizing cybersecurity remediation actions due to balancing risk, urgency, and resource constraints, distinguishing real threats from theoretical risks, and managing disruptions to business operations, leading to decision paralysis and misallocation of resources.
Innovation Solution
A system and method for detecting data objects in a cloud computing environment, determining cybersecurity contexts, generating risk scores, and prioritizing remediation actions based on these scores to efficiently address critical cybersecurity issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security teams assess and address all vulnerabilities, then comprehensive security coverage is improved, but resource constraints and time limitations cause delays in remediation
Solution Approach 1:
The patent segments vulnerabilities into different risk tiers based on data sensitivity and exploitability factors. High-risk vulnerabilities involving sensitive data are prioritized for immediate remediation, while lower-risk issues are scheduled for later addressing. This segmentation enables security teams to focus resources on critical issues without being overwhelmed by the complete vulnerability set.
Solution Approach 2:
The system dynamically changes the prioritization parameters based on multiple factors including data sensitivity classifications, exploitability assessments, and business context. By adjusting these parameters, the system generates context-aware risk scores that reflect the actual threat level of each vulnerability, enabling time-sensitive remediation decisions.
2Reliability
If organizations address all theoretical risks, then security thoroughness is improved, but real business operations are disrupted
Solution Approach 1:
The patent applies different remediation urgency levels to different vulnerabilities based on their local context. Vulnerabilities affecting sensitive data or high-value targets receive immediate attention, while those with minimal business impact are deferred. This local quality approach ensures security thoroughness is applied where needed without uniformly disrupting all operations.
Solution Approach 2:
The system performs partial remediation by addressing only the most critical vulnerabilities first rather than attempting to fix all issues simultaneously. This allows business operations to continue with acceptable risk levels while security remediation progresses systematically, balancing thoroughness with operational continuity.
3Speed
If security teams prioritize high-risk vulnerabilities, then critical security issues are addressed faster, but resource allocation to other important areas may be reduced
Solution Approach 1:
The vulnerability prioritization system is dynamic and adaptable, adjusting resource allocation recommendations based on changing threat landscapes, data sensitivity assessments, and business context. As new information becomes available, the system re-evaluates and re-prioritizes vulnerabilities, ensuring resource allocation remains versatile and responsive to emerging security needs while maintaining fast remediation of critical issues.
Data Source
AI summary
A system and method for prioritizing remediation actions for cybersecurity issues in a cloud computing environment based on a data risk score is presented. The method includes detecting a plurality of data objects in the computing environment, the computing environment including a plurality of resources and principals; determining a cybersecurity context for each detected data object; generating a representation of each data object, each resource, and each principal in a security database; detecting in the security database a resource representation connected to a data object representation, wherein a cybersecurity context is determined for the resource; generating a cybersecurity risk score based on the cybersecurity context of the data object and the cybersecurity context of the resource; prioritizing a plurality of remediation actions based on the generated cybersecurity risk score; and executing a remediation action based on the prioritization.