Google Cloud responds to AI-accelerated cyberattacks with a platform that aims to close security gaps in minutes
Quick Answer
Google Cloud has launched 'AI Threat Defense', a platform that automatically identifies, evaluates, and fixes security vulnerabilities in enterprise systems.
Quick Take
Google Cloud has launched 'AI Threat Defense', a platform that automatically identifies, evaluates, and fixes security vulnerabilities in enterprise systems. This initiative leverages technologies acquired through acquisitions to address the rising threat of AI-accelerated cyberattacks, aiming to close security gaps within minutes.
Key Points
- AI Threat Defense automates vulnerability detection and remediation in enterprise systems.
- The platform aims to close security gaps in minutes, enhancing response times.
- Technologies used in the platform were partly acquired through strategic acquisitions.
- This launch addresses the increasing threat posed by AI-driven cyberattacks.
- Google Cloud targets enterprise customers looking to bolster their cybersecurity posture.
Article Excerpt
From source RSS / original summaryGoogle Cloud has unveiled "AI Threat Defense," a platform designed to automatically find, assess, and patch security flaws in enterprise systems. The company bundles technologies it partly acquired through acquisitions. The article Google Cloud responds to AI-accelerated cyberattacks with a platform that aims to close security gaps in minutes appeared first on The Decoder.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.
