Cross-Tenancy Code Interrogation With Controlled Data Export
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large-scale software projects with millions of lines of code are difficult to analyze for security issues, leading to potential data breaches due to compromised code, as manual reviews are time-consuming and often miss vulnerabilities, and collaboration among companies with varying security standards increases the risk of data compromise.
Innovation Solution
Implementing test modules in a communication-controlled cloud environment that perform synchronous tests on private data, with results exported to an analytic environment for asynchronous analysis, while adhering to data export policies, and deploying investigation-bound cloud environments in restricted subnets for secure testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual code review is performed on large-scale software projects, then security issues can be detected, but the process is time-consuming and may still miss vulnerabilities
Solution Approach 1:
The patent replaces manual mechanical code review with automated computational analysis systems. Test modules automatically execute security tests on codebases, substituting human reviewers with computational agents that can analyze code at scale without time constraints, thereby maintaining high detection accuracy while eliminating time loss.
Solution Approach 2:
The patent introduces test modules as intermediary components between the codebase and security analysis. These modules act as automated mediators that systematically evaluate code for vulnerabilities, providing consistent and comprehensive security detection without the time constraints and human limitations of manual review processes.
2Adaptability or versatility
If companies collaborate on large-scale software projects with millions of lines of code, then new technologies and security safeguards can be shared, but the risk of compromised code increases
Solution Approach 1:
The patent implements preliminary security testing through test modules before code from different companies is integrated into the collaborative codebase. By performing security analysis in advance on each contributor's code, the system identifies and addresses vulnerabilities before they can propagate through the collaborative project, enabling technology sharing while mitigating data breach risks.
Solution Approach 2:
The patent introduces test modules as intermediary security verification layers between collaborating companies' code contributions. These modules automatically validate incoming code for security issues before integration, acting as a protective mediator that enables versatile collaboration while filtering out compromised code that could cause data breaches.
3Reliability
If test modules access private data in a communication-controlled cloud environment, then security testing can be performed, but data export policies must be enforced to prevent breaches
Solution Approach 1:
The patent segments the cloud environment into communication-controlled and non-communication-controlled zones. Test modules operate within the controlled zone where they can access private data for security testing, while data export policies act as segmentation boundaries that prevent unauthorized data flow to external environments, enabling effective testing while managing access control complexity.
Solution Approach 2:
The patent introduces data export policies as intermediary control mechanisms between the test modules accessing private data and the external cloud environment. These policies act as automated mediators that monitor and regulate data flow, allowing security testing to proceed effectively while preventing data breaches through enforced export restrictions.
Data Source
AI summary
Cloud computing architecture is described for implementing test modules in a communication-controlled cloud environment with access to private data. The test modules perform synchronous tests on the private data and export test results to an analytic environment subject to data export policies. An analytic application is used to asynchronously analyze the test results in the analytic environment. The cloud computing architecture alternatively or additionally includes an interface for deploying investigation-bound cloud environments in restricted subnets. A collection of software is instantiated in the investigation-bound cloud environment, and the investigation-bound cloud environment may be accessed with remote access credentials using a remote access protocol for testing the collection of software. Information about the investigation-bound cloud environment displayed in the analytic application, and the analytic application and the restricted subnet are forcibly deleted when the investigation is complete.


