At present, we’re asserting Sec-Gemini v1, a brand new experimental AI mannequin centered 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 must efficiently discover and exploit solely a single vulnerability. This basic asymmetry has made securing techniques extraordinarily troublesome, time consuming and error susceptible. AI-powered cybersecurity workflows have the potential to assist shift the steadiness again to the defenders by drive multiplying cybersecurity professionals like by no means earlier than.
Successfully powering SecOps workflows requires state-of-the-art reasoning capabilities and intensive 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 attain 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 robust collaboration throughout the cybersecurity neighborhood. Because of this we’re making Sec-Gemini v1 freely obtainable 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 Menace Intelligence (GTI), OSV, and different key information sources. Sec-Gemini v1 outperforms different fashions on CTI-MCQ, a number one menace 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 Menace Intelligence benchmark.
Determine 2: Sec-Gemini v1 has outperformed different fashions in a Cybersecurity Menace Intelligence-Root Trigger Mapping (CTI-RCM) benchmark that evaluates an LLM’s potential to know the nuances of vulnerability descriptions, determine vulnerabilities underlying root causes, and precisely classify them in response to the CWE taxonomy.
Beneath 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 menace actor (not all fashions do) and offers a complete description of that menace actor, because of its deep integration with Mandiant Menace intelligence information.
Subsequent, in response to a query in regards to the vulnerabilities within the Salt Hurricane description, Sec-Gemini v1 outputs not solely vulnerability particulars (because of its integration with OSV information, the open-source vulnerabilities database operated by Google), but in addition contextualizes the vulnerabilities with respect to menace actors (utilizing Mandiant information). With Sec-Gemini v1, analysts can perceive the danger and menace profile related to particular vulnerabilities sooner.
If you’re keen on collaborating with us on advancing the AI cybersecurity frontier, please request early entry to Sec-Gemini v1 through this type.
