We ran an experiment using Morris et. al’s Vec2Text model, to demonstrate the privacy risk of text embeddings with sensitive data. As we’ll show, a large percentage of sensitive data can be recovered from just their text embeddings, posing a significant privacy risk and demonstrating the need to use a tool like Tonic Textual to protect your data before using it to build generative AI systems.
The post Sensitive data in text embeddings is recoverable appeared first on Security Boulevard.
Key Findings Introduction Check Point Research (CPR) has been closely monitoring the ongoing exploitation of a group of Microsoft SharePoint Server vulnerabilities collectively referred to as “ToolShell.” These active attacks leverage four vulnerabilities—CVE-2025-49704, CVE-2025-49706, CVE-2025-53770, and CVE-2025-53771—and are attributed to multiple China affiliated threat actors. Among the threat groups identified by Microsoft, two are known […]
The post Before ToolShell: Exploring Storm-2603’s Previous Ransomware Operations appeared first on Check Point Research.