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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.

arXiv cs.CRSep 15, 13:29 UTC · 22h agoResearch

WordPress Adds Automated Plugin Reviews to Block High-Risk Updates Before Distribution

WordPress will automatically scan every plugin release and block high-risk updates from distribution using AI analysis plus Jetpack Scan.

WordPress announced automated security reviews for every plugin release during its cooldown period before distribution through the WordPress.org update API, combining AI models with Jetpack Scan into a security score. The system already caught a backdoor committed to a plugin with about 20,000 active installations on July 28, 2026, blocking it within 26 minutes of a Wordfence alert. Flagged patterns include missing capability checks, unsafe $wpdb queries, unserialize() on request data, and obfuscated code.

The Hacker NewsSep 14, 16:00 UTC · 1d agoTools