Telemetry Interception Platform for Software Drift Detection
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Solution Overview
Problem
Existing methods lack an efficient and practical way to track changes within software packages to identify potential time frames when security vulnerabilities are introduced, especially in large and complex packages that are constantly updated during the development cycle.
Innovation Solution
A telemetry interception and analysis platform (TIAP) generates drift reports by intercepting API calls, collecting telemetry events, and analyzing them to identify changes between different builds of an application, allowing for the detection of when and where security vulnerabilities were introduced.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software packages are constantly updated during the development cycle, then the software remains current and functional, but it becomes difficult to track when security vulnerabilities are introduced
Solution Approach 1:
The system performs preliminary actions by instrumenting the software build process to automatically capture telemetry events and version information before vulnerabilities can be introduced. This proactive approach establishes a baseline of software state that enables later identification of when changes occur, resolving the contradiction by preparing tracking mechanisms in advance rather than attempting to analyze changes after they've been introduced
Solution Approach 2:
The patent introduces an intermediary telemetry collection system that sits between the software build process and vulnerability analysis. This intermediary automatically captures API calls, configuration changes, and build metadata, transforming the complex problem of tracking vulnerabilities in constantly updating software into a manageable process of analyzing pre-captured telemetry data
2Adaptability or versatility
If software packages are very large and complex, then they provide comprehensive functionality, but it becomes unclear under which configuration or usage patterns vulnerabilities exist
Solution Approach 1:
The system segments the analysis of large software packages by breaking down vulnerability detection into manageable telemetry events. Each API call, configuration change, and usage pattern is captured as a separate event, allowing the system to analyze specific segments of software behavior rather than attempting to analyze the entire complex package at once. This enables precise identification of vulnerability conditions without being overwhelmed by the overall system complexity
Solution Approach 2:
The patent employs a metaphorical 'color change' approach by using telemetry event types and metadata to highlight and differentiate various software states and configurations. Different event categories (API calls, configuration changes, errors) act as visual indicators that help researchers quickly identify and focus on specific usage patterns or configuration states where vulnerabilities may exist, making the invisible visible in complex software systems
3Measurement precision
If manual tracking of software changes is performed, then detailed information about vulnerabilities can be obtained, but the process is inefficient and time-consuming
Solution Approach 1:
The system implements self-service by automatically instrumenting the software build process to collect telemetry events without requiring manual intervention. The telemetry collection infrastructure autonomously captures version information, API calls, and configuration changes, eliminating the need for manual tracking while maintaining high precision. This resolves the contradiction by enabling the system to serve itself in the data collection process, achieving both accuracy and efficiency simultaneously
Data Source
AI summary
Systems, methods, and computer-readable media for intercepting telemetry events obtained during operation of an application and analyzing the telemetry events are provided. The analysis can generate drift reports that can inform users at which point in time a particular change to the software affected an operation thereof.