At present, we’re asserting Sec-Gemini v1, a brand new experimental AI mannequin centered on advancing cybersecurity AI frontiers.
As outlined a 12 months in the past, defenders face the daunting job of securing towards all cyber threats, whereas attackers have to efficiently discover and exploit solely a single vulnerability. This elementary asymmetry has made securing methods extraordinarily troublesome, time consuming and error susceptible. AI-powered cybersecurity workflows have the potential to assist shift the steadiness again to the defenders by power multiplying cybersecurity professionals like by no means earlier than.
Successfully powering SecOps workflows requires state-of-the-art reasoning capabilities and in depth present cybersecurity information. Sec-Gemini v1 achieves this by combining Gemini’s superior capabilities with close to real-time cybersecurity information and tooling. This mix permits it to realize superior efficiency on key cybersecurity workflows, together with incident root trigger evaluation, menace evaluation, and vulnerability influence understanding.
We firmly consider that efficiently pushing AI cybersecurity frontiers to decisively tilt the steadiness in favor of the defenders requires a powerful collaboration throughout the cybersecurity neighborhood. This is the reason we’re making Sec-Gemini v1 freely obtainable to pick out organizations, establishments, professionals, and NGOs for analysis functions.
Sec-Gemini v1 outperforms different fashions on key cybersecurity benchmarks because of its superior integration of Google Risk Intelligence (GTI), OSV, and different key knowledge sources. Sec-Gemini v1 outperforms different fashions on CTI-MCQ, a number one menace intelligence benchmark, by at the least 11% (See Determine 1). It additionally outperforms different fashions by at the least 10.5% on the CTI-Root Trigger Mapping benchmark (See Determine 2):
Determine 1: Sec-Gemini v1 outperforms different fashions on the CTI-MCQ Cybersecurity Risk Intelligence benchmark.
Determine 2: Sec-Gemini v1 has outperformed different fashions in a Cybersecurity Risk Intelligence-Root Trigger Mapping (CTI-RCM) benchmark that evaluates an LLM’s capability to grasp the nuances of vulnerability descriptions, determine vulnerabilities underlying root causes, and precisely classify them in line with the CWE taxonomy.
Under is an instance of the comprehensiveness of Sec-Gemini v1’s solutions in response to key cybersecurity questions. First, Sec-Gemini v1 is ready to decide that Salt Storm is a menace actor (not all fashions do) and supplies a complete description of that menace actor, because of its deep integration with Mandiant Risk intelligence knowledge.
Subsequent, in response to a query in regards to the vulnerabilities within the Salt Storm description, Sec-Gemini v1 outputs not solely vulnerability particulars (because of its integration with OSV knowledge, the open-source vulnerabilities database operated by Google), but additionally contextualizes the vulnerabilities with respect to menace actors (utilizing Mandiant knowledge). With Sec-Gemini v1, analysts can perceive the chance and menace profile related to particular vulnerabilities quicker.
If you’re fascinated about collaborating with us on advancing the AI cybersecurity frontier, please request early entry to Sec-Gemini v1 by way of this manner.
