Evolution but Still Exposed: An Empirical Study of Residual APIs in the ChatGPT Plugin Ecosystem
Abstract
As large language model (LLM) platforms evolve rapidly, third-party plugin systems extend model capabilities but also introduce challenges for infrastructure governance and security. When a platform replaces an older third-party plugin ecosystem, backend services from the old ecosystem may remain reachable even after the platform no longer exposes those integrations. In this work, we focus on the early ChatGPT plugin ecosystem, which is in the original plugin store before the transition to the GPT Store. We probe domain reachability, residual configuration files, and API endpoint responses. We also use historical API records to identify backend services that standard probes miss.
Publication details
- Journal / source
- Proceedings of the 34th ACM International Conference on the Foundations of Software Engineering
- Publisher
- ACM
- Pages
- 1593–1598
- Publication date
- 5 July 2026
- Language
- EN