NVIDIA has demonstrated how its generative AI technologies can help to quickly identify and mitigate common vulnerabilities and exposures (CVEs) and other software security risks.
The NVIDIA NIM and NeMo Retriever microservices – along with the Morpheus accelerated AI framework – enable security analysts to detect and mitigate risks in a matter of seconds, a task that previously took hours or even days using traditional methods.
Traditional cybersecurity methods often involve laborious manual efforts to pinpoint solutions for identified vulnerabilities. However, NVIDIA’s generative AI technologies automate this process, providing quick and actionable CVE risk analysis through large language models (LLMs) and retrieval-augmented generation (RAG). This empowers analysts to make informed decisions swiftly, resembling the role of CEO-like decision-makers in the enterprises of the future.
The significance of generative AI in cybersecurity is highlighted by recent trends. Last year witnessed a record-high number of reported software security flaws in the CVE public database, underlining the critical need for innovative solutions in this space.
Gartner predicts that generative AI will play a pivotal role in reducing false-positive rates for application security testing and threat detection by 30 percent by 2027. NVIDIA’s AI Enterprise software platform incorporates these generative AI microservices and Morpheus, delivering unparalleled accuracy comparable to human experts.
The process of generative AI in cybersecurity involves the use of LLMs and event-driven RAG triggered by the creation of new software packages or the detection of CVEs.
In a demonstration by NVIDIA, an LLM generates a checklist of tasks to assess software vulnerabilities—followed by AI-powered searches across internal and external data sources to identify necessary safety actions:
NVIDIA is leveraging these cutting-edge technologies to secure its internal software development workflows, demonstrating their efficacy by performing over 400 internet searches and making more than 500 queries on enterprise data sources within seconds. This level of efficiency is unprecedented, with NVIDIA scanning over 1,000 containers per day.
Partnering with cybersecurity leader CrowdStrike, NVIDIA aims to further advance the adoption of generative AI and RAG in the industry.
Sven Krasser, SVP and Chief Scientist at CrowdStrike, said:
“Our industry has reached a crucial pivot point as AI becomes an equaliser for security teams and adversaries. Today, threat actors are leveraging the latest AI advancements to compromise organisations with increased velocity.
To stay one step ahead, security and operations teams need advanced threat detection and response capabilities that force-multiply their efforts by coupling together the power of data with targeted AI to accelerate investigations, identify potential vulnerabilities, and prevent breaches in their environments.”
NIM, NeMo Retriever, and Morpheus are available through NVIDIA AI Enterprise, providing a cloud-native software platform for accelerated and efficient runtime for generative AI foundation models. Developers can explore NVIDIA microservices for free, while enterprises can deploy production-grade NIM microservices through NVIDIA AI Enterprise 5.0 on certified systems and leading cloud marketplaces.
This week, NVIDIA also unveiled its Blackwell GPU architecture, designed to usher in a new era of accelerated computing and enable organisations to build and run real-time generative AI on trillion-parameter large language models.
(Photo by Agence Olloweb)
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