Cloud Disk Snapshot Scanning for Data Store Discovery
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Solution Overview
Problem
Existing cybersecurity solutions for cloud environments require manual identification of data stores, which is inefficient, prone to human error, and fails to account for unknown or unlisted data stores, leading to incomplete protection.
Innovation Solution
A method and system that utilize cloud provider tools to directly access file system metadata of disk snapshots in cloud environments, analyzing a limited portion to identify data stores, and create engines to access and classify data without manual permission requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual identification of data stores is used, then data source information can be obtained, but deployment becomes slower and less efficient
Solution Approach 1:
The system performs self-service by automatically discovering data stores through cloud provider APIs without requiring manual identification. The automated discovery process scans cloud environments, identifies data store locations, and populates the data source information automatically, eliminating the manual process while maintaining accuracy through systematic scanning protocols
Solution Approach 2:
The system performs preliminary action by conducting automated data store discovery before security protection is deployed. The discovery process pre-identifies all data stores in the cloud environment, including unknown ones, and prepares the information needed for subsequent security operations, thereby accelerating deployment without sacrificing accuracy
2Reliability
If manual identification of data stores is used, then data source information can be obtained, but human error increases leading to inaccurate or incomplete information
Solution Approach 1:
The system replaces the mechanical manual process with an automated computational system. Cloud provider APIs and automated scanning tools substitute human operators, eliminating human error while systematically processing cloud environments to identify data stores. The automation maintains reliability through consistent, error-free execution of discovery protocols
Solution Approach 2:
The automated discovery system provides universal functionality by handling multiple cloud providers and various data store types through a single unified process. The system adapts to different cloud environments and data store formats, ensuring complete and accurate identification across diverse scenarios without requiring separate manual processes for each case
3Reliability
If permission is obtained for each data store manually, then access to data stores can be achieved, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system merges the permission management process by obtaining access credentials at the cloud environment level rather than individually for each data store. The automated discovery process secures permission to access the cloud environment once, then uses that permission to systematically identify and access multiple data stores, dramatically reducing the time required while ensuring proper authorization
Solution Approach 2:
The system performs preliminary action by obtaining cloud environment access permission before data store identification. This preliminary authorization enables the automated process to subsequently access and discover all data stores within the environment without requiring separate permission requests, thereby reducing time loss while maintaining security
4Reliability
If comprehensive data store listing is attempted manually, then complete data store information can be obtained, but high technical expertise is required
Solution Approach 1:
The system performs self-service by automatically conducting comprehensive data store discovery without requiring human expertise. The automated process uses cloud provider APIs and scanning algorithms to systematically identify all data stores, generating a complete inventory that would otherwise require expert manual analysis. This eliminates the technical expertise barrier while maintaining completeness
Solution Approach 2:
The system replaces the need for human expert analysis with automated computational processes. Cloud provider APIs and discovery tools substitute skilled operators, systematically scanning cloud environments to identify data stores. The automation achieves comprehensive inventory accuracy that matches or exceeds manual expert capabilities while requiring no technical expertise from users
Data Source
AI summary
A system and method for discovering data store locations. A method includes reading, for each disk of a plurality of disks deployed in a cloud environment, only a portion of a snapshot of the disk accessed via a cloud provider tool, wherein the portion of the snapshot of each disk accessed via the cloud provider tool includes file system metadata of a file system of the disk, wherein the cloud provider tool is configured to provide direct access to data from each of the plurality of disks; analyzing the portion of the snapshot of each disk of the plurality of disks to determine whether each disk contains a data store; and identifying, based on the analysis, at least one data store in the cloud environment.