Black Kite:2025大语言模型在网络威胁情报中的应用研究报告:AI赋能第三方风险管理(英文版)(15页).pdf

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Black Kite:2025大语言模型在网络威胁情报中的应用研究报告:AI赋能第三方风险管理(英文版)(15页).pdf

1、Large Language Model Use Cases in Cyber Threat IntelligenceEnhancing Third-Party Risk Management Through AIAuthors:Mzeyyen Gken Tapkan,Gizem ToprakLLMs in CTI:A New Era for Third-Party Risk ManagementThe security of your organization is only as strong as its weakest link 3 and increasingly,those lin

2、ks are external.While internal cybersecurity measures are essential,they offer limited visibility into the security postures of third-party vendors and partners.This report is specifically designed to bridge that gap,empowering Third-Party Risk Management(TPRM)professionals to harness the vast poten

3、tial of open-source intelligence(OSINT).Todays challenge is that while Cyber Threat Intelligence(CTI)is crucial for identifying potential risks,traditional methods struggle to efficiently process the vast amounts of unstructured data relevant to third-party security4before adversaries can exploit vu

4、lnerabilities.This is where Large Language Models(LLMs)emerge as a game-changer.This report will demystify the application of LLMs in CTI,demonstrating how these powerful tools can be practically applied to strengthen your third-party risk management program.We will show how LLMs can enable you to:S

5、treamline OSINT AnalysisEnhance Supply Chain VisibilityImprove Risk PrioritizationFacilitate Informed Decision-MakingUltimately,by transforming the often overwhelming volume of publicly available data into clear,actionable intelligence,LLMs empower you to move from reactive threat response to proact

6、ive risk mitigation.What are LLM and CTI?LLMs are trained on extensive datasets that allow them to understand,generate,and summarize human-like text with remarkable accuracy.By leveraging advanced deep learning techniques,LLMs can sift through vast amounts of information to extract meaningful insigh

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