Security news aggregator

Latest coverage for Google

Stay updated on Google's info security advances, threats, and solutions. Protect your data with the latest insights from our dedicated Google security tag.

10 headlines in this view

Refine the feed

Search across headline titles and summaries.

Tag briefing

Background for this topic.

Google is a technology company whose ecosystem includes internet services, cloud infrastructure, mobile software, browsers, and productivity platforms. In information security, the tag commonly covers vulnerabilities and security changes across these services, as well as Google’s role as an identity and data-processing provider for organizations.

Material risks include compromised Google accounts, overly permissive cloud identities or APIs, exposed stored data, and unpatched flaws in software such as Android or Chrome. Security teams should track relevant advisories, prioritize patches based on affected assets and exposure, enforce strong authentication and least-privilege access, and review logging for suspicious account or service activity. Google’s collection and processing of user, device, and organizational data also makes privacy controls, retention settings, contractual obligations, and regulatory compliance important. Its vulnerability-disclosure and threat-intelligence work can inform defensive monitoring, but does not replace asset inventory, configuration review, or tested recovery procedures.

Showing 10 most recent headlines Filtered view

Chinese-Made AI App Faces European Privacy PushbackA German data regulator on Friday ordered Apple and Google to remove the Chinese artificial intelligence DeepSeek app from online stores over non-compliance with privacy and digital service rules. Commercial transfers of data outside of trading bloc members are governed by a complex legal system

Google's Anton Chuvakin Calls for Layered Defenses When Deploying AI ToolsAccording to Anton Chuvakin, security advisor at Google Cloud's Office of the CISO, relying solely on artificial intelligence model training or adversarial testing is not enough. Effective AI defense demands a "defense-in-depth" approach and proven best practices for autonomous actions.