Presently, the introduction of Sec-Gemini v1 signifies a cutting-edge AI model designed to drive the boundaries of cybersecurity AI.
As mentioned a year ago, defenders are confronted with the formidable challenge of safeguarding against all digital threats, while attackers seek to pinpoint and exploit just one vulnerability. This inherent imbalance has rendered system protection incredibly arduous, time-intensive, and prone to errors. AI-infused cybersecurity procedures hold promise in potentially rebalancing the scale in favor of defenders like never before.
Enabling top-notch SecOps procedures demands cutting-edge reasoning capacities and extensive contemporary cybersecurity insights. Sec-Gemini v1 accomplishes this by merging Gemini’s sophisticated functionalities with almost real-time cybersecurity expertise and tools. This fusion empowers it to excel in critical cybersecurity workflows such as root cause analysis of incidents, threat assessment, and comprehension of vulnerability impacts.
We firmly advocate that pushing the cybersecurity AI boundaries effectively to shift the equilibrium decisively in favor of defenders necessitates a robust partnership within the cybersecurity sector. That’s why we are granting access to Sec-Gemini v1 at no cost to select entities, organizations, professionals, and non-governmental organizations for research objectives.
Sec-Gemini v1 surpasses alternative models in prominent cybersecurity metrics due to its advanced integration of Google Threat Intelligence (GTI), OSV, and various vital data sources. Sec-Gemini v1 surpasses rival models by a minimum of 11% on CTI-MCQ, a primary threat intelligence benchmark (Refer to Figure 1). Moreover, it outperforms other models by at least 10.5% on the CTI-Root Cause Mapping benchmark (See Figure 2):
Figure 1: The CTI-MCQ Cybersecurity Threat Intelligence benchmark demonstrates the superiority of Sec-Gemini v1 over other models.
Figure 2: Sec-Gemini v1 excels in the CTI-RCM benchmark, which evaluates various cybersecurity models.
The following demonstrates Sec-Gemini v1’s in-depth responses to crucial cybersecurity inquiries. Initially, the model correctly identifies Salt Typhoon as a threat actor and provides a detailed account, facilitated by its integration with Mandiant Threat intelligence data.
Subsequently, when asked about vulnerabilities related to Salt Typhoon, Sec-Gemini v1 not only delivers vulnerability specifics (leveraging its OSV data integration) but also places the vulnerabilities in context with threat actors (utilizing Mandiant data). This efficient approach enables analysts to quickly grasp the risk and threat aspects associated with specific vulnerabilities.
If you wish to collaborate in advancing AI cybersecurity, feel free to request early access to Sec-Gemini v1 via this form.
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