Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreWith cyberattacks accelerating at machine speed, open-source large language models (LLMs) have quickly become the infrastructure that enables startups and global cybersecurity leaders to develop and deploy adaptive, cost-effective defenses against threats that evolve faster than human analysts can respond.Open-source LLMs’ initial advantages of faster time-to-market, greater adaptability and lower cost have created a scalable, secure foundation for delivering infrastructure. At last week’s RSAC 2025 conference, Cisco, Meta and ProjectDiscovery announced new open-source LLMs and a community-driven attack surface innovation that together define the future of open-source in cybersecurity.One of the key takeaways from this year’s RSAC is the shift in open-source LLMs to extend and strengthen infrastructure at scale.Open-source AI is on the verge of delivering what many cybersecurity leaders have called on for years, which is the ability of the many cybersecurity providers to join forces against increasingly complex threats. The vision of being collaborators in creating a unified, open-source LLM and infrastructure is a step closer, given the announcements at RSAC.Cisco’s Chief Product Officer Jeetu Patel emphasized in his keynote, “The true enemy is not our competitor. It is actually the adversary. And we want to make sure that we can provide all kinds of tools and have the ecosystem band together so that we can actually collectively fight the adversary.”Patel explained the urgency of taking on such a complex challenge, saying, “AI is fundamentally changing everything, and cybersecurity is at the heart of it all

Robust Intelligence (now a part of Cisco) and the UK AI Security Institute partnered with the National Institute of Standards and Technology (NIST) to release the latest update to the Adversarial Machine Learning Taxonomy.