CSPM Asset Coverage Expansion Using API Metadata Prioritization
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Solution Overview
Problem
Existing cloud security posture management (CSPM) solutions struggle to maintain a comprehensive and current view of cloud assets across multiple cloud service providers (CSPs), leading to gaps in knowledge and inadequate coverage of newly offered services and technologies, which hampers effective security monitoring and compliance auditing.
Innovation Solution
A system comprising a specification crawler, classifier, prioritizer, and template generator that crawls CSP APIs to extract metadata, classifies security-related attributes, filters out covered attributes, prioritizes metadata ingestion based on usage data, and generates ingestion templates to ensure comprehensive CSPM coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CSPM solutions continuously monitor and scan cloud assets across multiple CSPs, then security coverage and compliance auditing capability are improved, but system complexity and resource consumption increase
Solution Approach 1:
The system performs preliminary actions by proactively discovering new cloud assets and services through automated crawling of CSP documentation and APIs before security issues arise. The metadata ingestion manager preemptively ingests documentation, extracts attribute information, and updates the cloud asset inventory in advance, ensuring comprehensive coverage without requiring complex real-time analysis of every possible asset state.
Solution Approach 2:
The system employs self-service mechanisms where the metadata ingestion manager autonomously crawls CSP documentation, extracts metadata, classifies attributes, and updates asset inventories without requiring manual intervention. The foundation model automatically classifies security-related attributes and the system self-updates its knowledge base, reducing the need for complex manual configuration and maintenance.
2Measurement precision
If CSPM solutions ingest and process detailed metadata from CSP APIs, then accuracy of security assessment is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential metadata and attribute information needed for security assessment from CSP API responses and documentation. The metadata ingestion manager selectively extracts critical attributes such as resource types, configuration parameters, and security-relevant metadata, while filtering out unnecessary detailed information. This extraction approach maintains assessment accuracy while significantly reducing processing time and computational resources required.
Solution Approach 2:
The system applies local quality by tailoring the level of detail processed for different cloud asset types and CSPs based on their security relevance and complexity. The foundation model classifies attributes by security importance, and the system processes detailed metadata for high-priority assets while using summarized or simplified representations for lower-priority assets, optimizing the balance between assessment accuracy and processing efficiency.
3Quantity of substance
If CSPM solutions maintain comprehensive inventory of cloud assets, then completeness of security monitoring is improved, but data management complexity increases
Solution Approach 1:
The system segments the cloud asset inventory into organized categories and structures by cloud service provider, asset type, and security relevance. The metadata ingestion manager maintains separate, modular data structures for different CSPs and asset categories, making the comprehensive inventory manageable through systematic organization. This segmentation approach enables complete tracking of all cloud assets while reducing data management complexity through structured storage and retrieval mechanisms.
Solution Approach 2:
The metadata ingestion manager acts as an intermediary layer between CSP APIs and the security assessment system. This intermediary component consolidates and normalizes metadata from multiple CSPs into a unified representation, abstracting the complexity of diverse CSP data formats and structures. The intermediary maintains comprehensive asset inventory while shielding the rest of the system from data management complexities through standardized interfaces and normalized data models.
Data Source
AI summary
A system has been created to automatically expand CSPM coverage for an organization based on CSP offerings and organization usage of cloud resources. The system crawls API specifications of each CSP used by an organization to extract cloud resource metadata including attributes and attribute descriptions. The system classifies each discovered attribute as related to security or not related to security. The system then filters out those security related attributes that already have CSPM coverage. The system collects information across different data sources corresponding to CSPM for the organization, such as audit logs and ingestion requests. The system then prioritizes resource attributes for metadata ingestion based on configurable parameters that consider newly discovered CSP offerings represented by discovered security related attributes. According to the prioritization, the system generates templates to execute for ingestion.