API Flow Path Fingerprinting for Cloud Database Security
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Solution Overview
Problem
In cloud environments, data security threats arise from role escalation, where unauthorized users access and modify sensitive information, which is difficult to detect using existing observability tools, leading to potential unauthorized modifications of data records in databases.
Innovation Solution
Implementing multi-level security logic that analyzes API call flow paths, detects deviations from expected paths, and denies access based on predetermined thresholds, using techniques like API call path flow fingerprinting, private key derivation, and IAM/RBAC policies to ensure secure access to cloud databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Role-Based Access Control (RBAC) policies are implemented to control data access, then data security is improved, but the complexity of access control management increases
Solution Approach 1:
The patent segments access control into multiple hierarchical levels: RBAC policies at the role level, API flow path policies at the transaction level, and column-level security policies at the data level. This segmentation allows each layer to handle specific security aspects independently, improving overall security while managing complexity through modular policy enforcement points throughout the API call flow.
Solution Approach 2:
The system performs preliminary security actions by establishing expected API flow paths and security policies before actual data access occurs. Security rules, column-level access controls, and flow path expectations are predefined and stored in the database schema, enabling proactive security enforcement rather than reactive responses to breaches.
2Loss of information
If traditional observability tools are used to monitor data access, then application state visibility is improved, but detection of role escalation threats remains ineffective
Solution Approach 1:
The patent introduces security logic as an intermediary layer between the application and database that specifically monitors API flow paths. This intermediary captures and analyzes the actual execution path of API calls, comparing them against expected secure paths defined in the schema, thereby detecting role escalation attempts that traditional observability tools would miss.
Solution Approach 2:
The system adds a new dimension to observability by tracking API flow paths through multiple enforcement points rather than just monitoring application state. This dimensional shift from state monitoring to flow path analysis enables detection of unauthorized access patterns and role escalation threats that exist in the transactional flow rather than the application state.
3Reliability
If multi-level security logic with flow path analysis is implemented, then detection of unauthorized access is improved, but system complexity increases
Solution Approach 1:
The security logic is segmented into distinct enforcement points distributed throughout the API call flow: authentication/authorization at the entry point, column-level security checks at data access points, and flow path validation at transaction boundaries. This segmentation distributes complexity across multiple simple, focused security checks rather than one complex centralized security system.
Solution Approach 2:
Expected API flow paths and security policies are predefined and stored in the database schema before runtime. This preliminary configuration allows the security logic to operate through simple comparison operations during execution, reducing runtime complexity while maintaining comprehensive security monitoring capabilities.
4Reliability
If column-level security policies are enforced at multiple enforcement points, then data protection is improved, but processing overhead increases
Solution Approach 1:
Column-level security policies and access control rules are predefined and cached in the database schema before API calls are executed. This preliminary preparation allows enforcement points to perform fast lookups and comparisons rather than evaluating complex security rules in real-time, minimizing processing overhead while maintaining strong data protection.
Solution Approach 2:
The system applies column-level security checks at multiple enforcement points throughout the API flow, which may seem excessive. However, this redundancy ensures that security is enforced even if one check is bypassed, while the use of precompiled security rules keeps the performance impact minimal through efficient comparison operations.
Data Source
AI summary
A method to protect data in a database. The method includes detecting an actual flow path for an API call between a source node and a destination node, determining whether the actual flow path for the API call deviates from an expected flow path for the API call, and in response to determining that the actual flow path for the API call deviates from the expected flow path by a predetermined threshold, denying access to data sought by the API call at the destination node.