Real-Time Source Code Monitoring for Sensitive Data Protection
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Solution Overview
Problem
Enterprise organizations face challenges in ensuring the integrity and confidentiality of sensitive data while optimizing resource utilization and preventing unauthorized access, particularly when software developers use external source code repositories.
Innovation Solution
A computing platform monitors external code repository server infrastructure in real-time, detects sensitive information, and generates entity-specific alerts and notifications, allowing for automatic deletion or manual review of sensitive data, while updating criteria for identifying sensitive data based on detected features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If external source code repositories are used for software development, then resource utilization and operational efficiency are improved, but the risk of data leakage and unauthorized access to sensitive information increases
Solution Approach 1:
The system performs preliminary scanning and detection of sensitive information in source code before it is committed to external repositories. By proactively identifying sensitive data patterns (such as API keys, passwords, and confidential information) during the development process, the system prevents data leakage before it occurs, allowing developers to continue using external repositories efficiently while maintaining security.
Solution Approach 2:
The patent introduces an intermediary monitoring system that sits between the development environment and external source code repositories. This intermediary component analyzes code submissions in real-time, detecting sensitive information without blocking the development workflow. It acts as a mediator that enables continued use of external repositories while providing the necessary security controls.
2Reliability
If real-time monitoring of external code repositories is implemented to detect sensitive information, then data security is improved, but system complexity and computational resources increase
Solution Approach 1:
The system manages complexity by changing parameters such as scanning depth, detection sensitivity, and monitoring frequency based on the specific context. It adjusts its monitoring intensity and resource allocation dynamically, scanning only relevant code sections and adapting to different repository types and sensitivity levels, thereby maintaining high security without requiring maximum system complexity at all times.
Solution Approach 2:
The monitoring system is divided into modular components that can independently scan, detect, analyze, and respond to sensitive information. This segmentation allows the system to process different types of sensitive data through specialized modules, reducing overall system complexity while maintaining comprehensive security coverage across multiple external repositories.
3Measurement precision
If comprehensive scanning of source code for sensitive information is performed, then detection accuracy is improved, but processing time and computational overhead increase
Solution Approach 1:
The system applies partial scanning actions by focusing detection efforts on code sections most likely to contain sensitive information, such as configuration files, authentication modules, and data access layers. Rather than uniformly scanning every line of code, it prioritizes high-risk areas, achieving high detection accuracy for critical sensitive data while reducing overall processing time through selective analysis.
Solution Approach 2:
The monitoring system operates continuously in the background during normal development activities, performing incremental scans as code is written and modified. This continuous monitoring approach detects sensitive information in near-real-time without requiring lengthy batch processing interruptions, maintaining both high detection accuracy and minimal impact on development workflow timing.
Data Source
AI summary
Aspects of the disclosure relate to monitoring source code repository data in real-time to protect sensitive information and provide entity-specific alerts. A computing platform may receive configuration information defining one or more criteria for identifying sensitive data of an enterprise organization. The computing platform may monitor external code repository server infrastructure based on the configuration information. In response to detecting that first source code received by the external code repository server infrastructure contains first sensitive information associated with the enterprise organization, the computing platform may generate a notification comprising information indicating that the first sensitive information associated with the enterprise organization has been detected at the external code repository server infrastructure. Subsequently, the computing platform may send the notification to an enterprise administrator user computing device associated with the enterprise organization.