Security Graph Visualization for Cloud Attack Path Analysis
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Solution Overview
Problem
Incident response and cybersecurity forensics in cloud computing environments face challenges due to their distributed nature and reliance on third-party providers, leading to overwhelming data volumes that are difficult to present and analyze effectively.
Innovation Solution
A system and method for detecting forensic artifacts and cybersecurity objects in a computing environment, generating representations in a security database, and visualizing potential lateral movement paths using a security graph to facilitate analysis and remediation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static analysis techniques are used to detect cybersecurity risks in cloud environments, then detection capability is improved, but data volume and analysis complexity increase tremendously
Solution Approach 1:
The patent segments the monolithic forensic data into structured components using a standardized schema that divides data into entity types (processes, files, networks, hosts) with hierarchical relationships. This segmentation organizes tremendous data volumes into manageable, queryable units that can be analyzed independently while maintaining contextual relationships through parent-child entity links.
Solution Approach 2:
The patent introduces a standardized forensic data schema as an intermediary layer between raw static analysis data and analysis tools. This schema acts as a mediator that transforms unstructured or semi-structured forensic artifacts into a consistent, organized format with defined entities, attributes, and relationships, enabling efficient querying and analysis without dealing with the raw data volume directly.
2Reliability
If comprehensive forensic data is collected from distributed cloud environments, then analysis completeness is improved, but data presentation and interpretation difficulty increases
Solution Approach 1:
The patent segments comprehensive forensic data into distinct entity types (processes, files, networks, hosts, users) with clear hierarchical relationships. Each entity type has standardized attributes and defined relationships to other entities, allowing analysts to navigate complex forensic data through structured pathways rather than overwhelming unorganized data dumps.
Solution Approach 2:
The patent adds a structural dimension to forensic data by organizing it into a hierarchical entity-relationship model. Instead of presenting data as flat tables or unstructured text, the schema introduces dimensional relationships (parent-child entities, associations, containers) that enable multi-dimensional analysis and presentation, making complex distributed cloud forensic data interpretable through structured navigation.
3Measurement precision
If detailed forensic artifacts are inspected for cybersecurity objects, then detection accuracy is improved, but processing time and resource requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-defining the forensic data structure with standardized entity types, attributes, and relationships before analysis begins. This pre-organized schema allows analysis tools to directly query specific entity attributes without parsing unstructured data, significantly reducing processing time while maintaining detection accuracy through the predefined structural framework.
Solution Approach 2:
The patent changes the parameter organization of forensic data from unstructured or semi-structured formats to a standardized schema with defined entity types, mandatory and optional attributes, and relationship parameters. This parameter transformation enables efficient database querying and indexing, reducing processing time while preserving detection accuracy through consistent data representation.
4Productivity
If a standardized forensic schema is implemented, then data organization and querying efficiency are improved, but initial system complexity increases
Solution Approach 1:
The patent segments the forensic schema into modular entity types (processes, files, networks, hosts, users) with clearly defined boundaries and relationships. This modular segmentation allows incremental implementation where organizations can adopt entities and relationships relevant to their specific needs without implementing the entire schema, reducing initial complexity while maintaining querying efficiency for implemented portions.
Data Source
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AI summary
A system and method for detecting an attack path in a computing environment is presented. The method includes: detecting a forensic artifact in a computing environment, the forensic artifact including an identifier of a resource deployed in the computing environment; inspecting the resource for a cybersecurity object, the cybersecurity object indicating a cybersecurity issue; generating a representation of: the detected forensic artifact, the resource, and the cybersecurity object, in a security database, wherein the security database includes a representation of the computing environment; generating a potential lateral movement path between the resource and another resource; and generating a visualization based on the potential lateral movement, the forensic artifact, and the cybersecurity object.