Software Deployment Risk Evaluation for Sensitive Data Exposure
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Solution Overview
Problem
Existing software development processes lack effective mechanisms to dynamically track and manage the exposure of sensitive data across different environments, leading to potential data breaches and unintentional exposure during deployment, especially in production environments.
Innovation Solution
An intelligent software deployment tool that monitors data exchanges, identifies designated types of data, evaluates the risk of exposure, and controls deployment based on this risk, using reverse proxies and fuzzy matching algorithms to detect and prevent sensitive data exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If software deployment processes are automated to improve productivity, then deployment speed increases, but the ability to detect and prevent sensitive data exposure deteriorates
Solution Approach 1:
The system performs security evaluation before deployment by monitoring data exchanges in development and testing environments. The security evaluation component analyzes requests and responses to detect sensitive data exposure patterns, generating security evaluation results that prevent harmful deployments before they occur in production environments.
Solution Approach 2:
The system implements continuous feedback loops where security evaluation results from monitoring data exchanges are fed back into the deployment control process. The deployment control component uses security evaluation results to dynamically control deployment decisions, creating a closed-loop system that adapts deployment actions based on detected security conditions.
2Object-affected harmful factors
If manual security checks are performed to reduce data exposure risk, then security evaluation improves, but deployment time and operational complexity increase
Solution Approach 1:
The system enables self-service security evaluation by automatically monitoring data exchanges and generating security evaluation results without requiring manual security checks. The security evaluation component autonomously analyzes requests and responses, detecting sensitive data exposure patterns and providing deployment control recommendations automatically.
Solution Approach 2:
The system replaces manual mechanical security checking processes with automated computer-based monitoring and analysis. The security evaluation component uses automated pattern recognition and data exchange monitoring to substitute for manual security reviews, significantly reducing time consumption while maintaining or improving detection accuracy.
3Measurement precision
If comprehensive monitoring of all data exchanges is implemented to improve detection accuracy, then security evaluation improves, but system complexity and resource consumption increase
Solution Approach 1:
The system segments the monitoring function into specialized components: a security evaluation component that specifically analyzes data exchange patterns for sensitive information, and a deployment control component that uses these results. This segmentation allows focused monitoring of security-relevant data exchanges rather than comprehensive analysis of all system traffic, reducing complexity.
Solution Approach 2:
The system changes the monitoring parameters to focus on security-relevant characteristics of data exchanges rather than monitoring all possible data attributes. The security evaluation component analyzes specific patterns and characteristics that indicate sensitive data exposure, such as data types, context, and exchange patterns, rather than performing exhaustive analysis of all data.
Data Source
AI summary
An apparatus comprises at least one processing device configured to monitor data exchanged with a given piece of software, the monitored data comprising requests and responses exchanged between clients and the given piece of software. The at least one processing device is also configured to generate a data structure characterizing whether designated types of data are included in the monitored data, the generated data structure comprising one or more entries, a given entry comprising information characterizing at least one request or response in which at least of the designated types of data is determined to be included. The at least one processing device is further configured to evaluate a risk of exposure of the designated types of data by parsing the generated data structure, and to control deployment of the given piece of software in a given operating environment based at least in part on the evaluated risk of exposure.