Plug 'n' Pray: Agentic LLM-based Detection of Potential Log File Exposures in Third-Party Content Management System Plugins
Agentic LLM analysis validates 79 log file exposures across 62 of the 300 most-installed WordPress plugins, covering 250M+ active installations.
Researchers built an agentic LLM-based framework combining static and dynamic analysis to automatically detect insecure log files created by WordPress plugins. Scanning the 300 most-installed plugins, which account for roughly 75% of all active installations in the official ecosystem, it produced 81 findings with 79 manually reproduced across 62 plugins. Insufficiently secured log files can disclose credentials and personal data and have led to website compromises. The authors derive a taxonomy of log path and protection patterns and best practices, finding multi-layered protection often absent.
- LLM agent combines static and dynamic analysis of each plugin
- 79 of 81 findings validated across 62 plugins with 250M+ active installations
- Exposed logs can leak credentials and personal data, enabling site compromise
- Proposes taxonomy and best practices for secure log file handling
From the original article
1 min read at arxiv.orgContent Management Systems (CMS), such as WordPress, power a large share of the web (~58%), and their extensibility through third-party plugins is a major source of their popularity as well as of their attack surface. One high-impact weakness that remains understudied is log file exposure by CMS plugins, which create log files for debugging or other purposes.
By Sebastian Neef · arxiv.org
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