At the RSA Conference (RSAC) in San Francisco this week, Google Cloud announced their new security platform, the Google Cloud Security AI Workbench, powered by a custom language model for cybersecurity, Sec-PaLM. This large language model (LLM) is designed to use Google’s proprietary threat intelligence data and the frontline intelligence from Mandiant to identify and contain malicious activity, and coordinate response actions.
Eric Doerr, Vice President of Engineering at Google Cloud, spoke to VentureBeat in an interview about the platform’s transformative potential, “Imagine a world where you know, as you’re generating your infrastructure, there’s an auto-generated security policy, security control, or security config that goes along with that.”
The Workbench is rolling out with several tools such as VirusTotal Code Insight, in preview now, to review scripts for malicious behavior, as well as Mandiant Breach Analytics for Chronicle, which notifies users automatically when a breach has occurred, and uses the Sec-PaLM model to summarize and respond to found threats.
As organizations begin to use generative AI for defensive use cases, the opportunity in security markets is proving to be lucrative. According to MarketsandMarkets, the value of this market is expected to reach $51.8 billion by 2028.
With a major competitor like Microsoft’s Security Copilot using natural language processing powered by GPT-4 to process threat signals and produce written summaries, Google is trying to gain a foothold in the defensive generative AI wars. Other notable contenders in this space include the cloud security provider Orca Security and Kubernetes security company ARMO.
Google Cloud sets itself apart from its rivals by touting its huge datasets to train the model by leveraging data from the Google product ecosystem which includes Google Chrome and its partnership with Mandiant.
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