Tracking GPTs Third Party Service: Automation, Analysis, and Insights

ChatGPT has quickly advanced from simple natural language processing to tackling more sophisticated and specialized tasks. Drawing inspiration from the success of mobile app ecosystems, OpenAI allows developers to create applications that interact with third-party services, known as GPTs. GPTs can choose to leverage third-party services to integrate with specialized APIs for domain-specific applications. However, the way these disclose privacy setting information limits accessibility and analysis, making it challenging to systematically evaluate the data privacy implications of third-party integrate to GPTs. In order to support academic research on the integration of third-party services in GPTs, we introduce GPTs-ThirdSpy, an automated framework designed to extract privacy settings of GPTs. GPTs-ThirdSpy provides academic researchers with real-time, reliable metadata on third-party services used by GPTs, enabling in-depth analysis of their integration, compliance, and potential security risks. By systematically collecting and structuring this data, GPTs-ThirdSpy facilitates large-scale research on the transparency and regulatory challenges associated with the GPT app ecosystem.

Publication Details

Journal
ArXiv.org
Published
2025-06-18
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Tracking GPTs Third Party Service: Automation, Analysis, and Insights

ArXiv.org
Artificial Intelligence in Healthcare and Education
article

Tracking GPTs Third Party Service: Automation, Analysis, and Insights

article en

Abstract

ChatGPT has quickly advanced from simple natural language processing to tackling more sophisticated and specialized tasks. Drawing inspiration from the success of mobile app ecosystems, OpenAI allows developers to create applications that interact with third-party services, known as GPTs. GPTs can choose to leverage third-party services to integrate with specialized APIs for domain-specific applications. However, the way these disclose privacy setting information limits accessibility and analysis, making it challenging to systematically evaluate the data privacy implications of third-party integrate to GPTs. In order to support academic research on the integration of third-party services in GPTs, we introduce GPTs-ThirdSpy, an automated framework designed to extract privacy settings of GPTs. GPTs-ThirdSpy provides academic researchers with real-time, reliable metadata on third-party services used by GPTs, enabling in-depth analysis of their integration, compliance, and potential security risks. By systematically collecting and structuring this data, GPTs-ThirdSpy facilitates large-scale research on the transparency and regulatory challenges associated with the GPT app ecosystem.

ArXiv.org
Openalex Percentile: Top 54%
Artificial Intelligence in Healthcare and Education
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Tracking GPTs Third Party Service: Automation, Analysis, and Insights · ArXiv.org (2025) | TGRS Research Map | TGRS