Security Graph Inspection for IaC-to-Production Cloud Drift
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Solution Overview
Problem
Current cloud workload vulnerability scanning solutions are inadequate for detecting cybersecurity issues in cloud environments, particularly in multi-tenant systems and those using infrastructure as code (IaC), as they fail to provide comprehensive coverage of containers and serverless applications, and are limited by agent-dependent processes and snapshot-based scanning methods.
Innovation Solution
A method and system that utilize a security graph to inspect multiple cloud computing environments by detecting code objects in configuration code, generating nodes in the graph to represent virtual instances, and identifying cybersecurity issues across different environments, including production, staging, and development environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If agent-dependent scanning methods are used, then scanning coverage for virtual machines can be achieved, but the solution fails to provide scanning for containers and serverless applications, and requires costly maintenance
Solution Approach 1:
The patent introduces a security graph as an intermediary data structure that models relationships between code objects and deployed instances. This security graph enables a unified agentless scanning approach that can inspect multiple cloud environments (VMs, containers, serverless) through their configuration code representations, eliminating the need for different scanning agents for each workload type while reducing maintenance complexity.
Solution Approach 2:
The patent creates copies of environment representations in the form of security graphs that mirror the structure and relationships of actual cloud deployments. By scanning these graph representations rather than directly inspecting live environments with agents, the system achieves comprehensive coverage across diverse workload types without requiring physical or virtual scanning agents in each environment.
2Ease of operation
If snapshot-based scanning is used, then agentless scanning capability is provided, but the method is limited in multi-tenant systems due to data protection requirements and cannot process certain cloud system structures
Solution Approach 1:
The patent transitions from snapshot-based scanning that operates in the traditional time dimension (capturing static snapshots) to a multi-dimensional security graph model that incorporates code object relationships, deployment configurations, and instance mappings. This dimensional expansion enables the system to handle multi-tenant environments by maintaining logical isolation through graph structure while providing unified agentless scanning across diverse cloud architectures.
Solution Approach 2:
The patent changes the fundamental parameters of the scanning approach by moving from snapshotting actual environment states to modeling configuration code relationships. This parameter transformation allows the system to scan cloud environments agentlessly while maintaining compatibility with multi-tenant systems, as the security graph operates on configuration representations rather than direct environment access.
3Device complexity
If configuration code scanning only is used, then scanning simplicity is maintained, but the solution cannot detect drift between original configuration and current production state
Solution Approach 1:
The patent implements feedback mechanisms where the security graph continuously compares configuration code representations with actual deployed instance states. When drift is detected between the configured security properties and actual instance properties, the system generates feedback loops that identify and report these discrepancies, enabling precise vulnerability detection while maintaining the simplicity of configuration-based scanning through automated comparison processes.
Solution Approach 2:
The patent performs preliminary actions by building comprehensive security graphs that model all expected security properties and relationships before production deployment. This preliminary modeling establishes a baseline for comparison, allowing the system to detect drift between original configuration intentions and current production states with high precision while maintaining scanning simplicity through pre-defined security property templates.
4Reliability
If comprehensive multi-environment scanning is implemented, then complete vulnerability coverage is achieved, but resource consumption and detection time increase
Solution Approach 1:
The patent segments the scanning process into distinct phases: security graph construction from configuration code, relationship mapping between code objects and instances, and vulnerability detection across environments. This segmentation allows the system to process multi-environment data systematically, reducing overall scanning time by handling each segment independently while maintaining complete vulnerability coverage through the interconnected graph structure.
Solution Approach 2:
The patent merges multiple environment representations into a unified security graph that consolidates code objects, deployment configurations, and instance data from development, staging, and production environments. This merging eliminates redundant scanning operations across environments while achieving comprehensive vulnerability coverage, as the unified graph enables simultaneous inspection of all environments through shared code object relationships.
Data Source
AI summary
A system and method for inspecting multiple instances across cloud computing environments for a cybersecurity issue is presented. The system is configured to: detect a code object in a configuration code file, the code object utilized to deploy a virtual instance in a cloud computing environment; generate in a security graph a code object node representing the code object; generate in the security graph a resource node representing a virtual instance deployed in a first cloud computing environment based on the code object, wherein the resource node is connected to the code object node; detect a cybersecurity issue on the virtual instance; and generate an instruction to inspect a second virtual instance deployed in a second cloud computing environment based on the code object, the second virtual instance represented by a second resource node connected to the code object node.