At the moment, we’re asserting Sec-Gemini v1, a brand new experimental AI mannequin targeted on advancing cybersecurity AI frontiers.
As outlined a yr in the past, defenders face the daunting job of securing in opposition to all cyber threats, whereas attackers have to efficiently discover and exploit solely a single vulnerability. This elementary asymmetry has made securing programs extraordinarily tough, time consuming and error inclined. AI-powered cybersecurity workflows have the potential to assist shift the steadiness again to the defenders by pressure 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, risk evaluation, and vulnerability impression understanding.
We firmly consider that efficiently pushing AI cybersecurity frontiers to decisively tilt the steadiness in favor of the defenders requires a robust collaboration throughout the cybersecurity group. For this reason we’re making Sec-Gemini v1 freely accessible to pick 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 risk intelligence benchmark, by not less than 11% (See Determine 1). It additionally outperforms different fashions by not less than 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 potential to know the nuances of vulnerability descriptions, establish vulnerabilities underlying root causes, and precisely classify them in keeping 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 Hurricane is a risk actor (not all fashions do) and supplies a complete description of that risk actor, due to its deep integration with Mandiant Risk intelligence knowledge.
Subsequent, in response to a query in regards to the vulnerabilities within the Salt Hurricane description, Sec-Gemini v1 outputs not solely vulnerability particulars (due to its integration with OSV knowledge, the open-source vulnerabilities database operated by Google), but in addition contextualizes the vulnerabilities with respect to risk actors (utilizing Mandiant knowledge). With Sec-Gemini v1, analysts can perceive the danger and risk profile related to particular vulnerabilities sooner.
If you’re concerned about collaborating with us on advancing the AI cybersecurity frontier, please request early entry to Sec-Gemini v1 through this kind.
