Open source software is a critical pillar of the global economy. It underpins cloud computing, financial services, manufacturing, telecommunications, government and internet services by making technology accessible and observable to communities of experts.\u00a0<\/p>\n
Cybersecurity is among the top three beneficiaries of open source software. The Open Secure AI Alliance \u2014 building on the leadership of the Linux Foundation\u2019<\/a>s Akrites <\/a>initiative and OpenSSF<\/a> community work \u2014 will work to remediate and disclose vulnerabilities using open technologies.\u00a0<\/p>\n Just as open source created a shared foundation for software, the United States and its partners now face a choice in AI security: whether the defenses that protect our infrastructure will sit inside a few opaque systems or be built on open models, harnesses and tools that any defender can study, adapt and deploy.<\/p>\n The world needs both closed and open models<\/a>. For cybersecurity, open models and open harnesses are essential because they democratize defensive capabilities, increase transparency for defenders, enable cyber defense while protecting data, and complement frontier closed models with customizable, localized controls. Open source enables massively distributed community-driven and self-controlled defense \u2013 with no single point of failure.\u00a0<\/p>\n Open models, like any powerful technology, can be misused \u2014 including through attempts to weaken safeguards or repurpose capabilities for cyber attacks \u2014 but those risks are not unique to open systems, and they must be managed wherever advanced AI is deployed.<\/p>\n The recent Hugging Face security incident<\/a> delivered a clear reminder: cyber defenders need open, frontier agentic systems for self-defense. When closed AI tools \u2014 unable to distinguish attackers from defenders \u2014 blocked essential forensic analysis, Hugging Face ran the open-weight GLM 5.2 model on its own infrastructure to analyze more than 17,000 actions and contain the intrusion.\u00a0\u00a0<\/p>\n That incident showed a practical truth: when defenders cannot inspect, adapt and run advanced AI on their own infrastructure, their ability to respond is constrained at exactly the moment speed matters most. Companies and countries need open frontier defensive tools and techniques so critical industries can build security systems across a multi-vendor ecosystem and avoid single points of failure.<\/p>\n That is the mission of the Open Secure AI Alliance: to ensure defenders everywhere have open, frontier tools they can trust and control.<\/p>\n Leaders across cloud computing, cybersecurity, enterprise software, open source foundations and AI research \u2014 including NVIDIA, Adobe, Cadence, Capital One, Cisco, Cloudera, Cloudflare, Cognition, CrowdStrike<\/a>, Databricks, Dell Technologies, DoorDash, Elastic<\/a>, HPE<\/a>, Hugging Face, IBM, LangChain, the Linux Foundation, Microsoft, NAVER, NetApp, Nous Research, OpenClaw, Palantir, Palo Alto Networks, Red Hat<\/a>, Reflection AI,\u00a0Salesforce, SAP, ServiceNow, Siemens, SK Telecom, Snowflake, SpacexAI, Synopsys, Thinking Machines Lab and TrendAI are inaugural partners in the Open Secure AI Alliance, a movement to develop and share open technologies, techniques and tools to safeguard software and agents in the age of AI.<\/p>\n Some argue that open models are inherently less safe because they can be misused for cyberattacks or modified to remove guardrails. Those risks are real, but they do not disappear in closed systems, and simply keeping weights closed does not prevent determined attackers from seeking or exploiting powerful AI.<\/p>\n The right response is not to deny defenders access to capable open systems. It is to pair openness with strong safeguards, clear rules against malicious misuse, rigorous evaluation and rapid remediation. In cybersecurity, the safer path is the one that gives more defenders the ability to test, verify and strengthen the systems on which society relies.\u00a0<\/p>\n Defenders need both frontier closed models and frontier open models, working together, so they can choose the right system for the job and ensure that transparency, adaptation and sovereign control are available wherever security demands them.<\/p>\n Open Research Enhances Cybersecurity and AI Safety<\/p>\n An AI agent isn\u2019t just a language model. It is a complex system built from models, harnesses and guardrails.\u00a0<\/p>\n Real AI safety and security depend on the full agent stack \u2014 identity, permissions, harnesses, guardrails, logs and evaluation \u2014 not just on whether model weights are open or closed. Open harnesses and tools make those controls easier for many defenders to inspect, test and improve.<\/p>\n NVIDIA is contributing open models, model weights, data and new agent harness research to the Open Secure AI Alliance to speed the development of new cybersecurity tools and techniques.<\/p>\n The new open source NVIDIA Labs Object-Oriented Agent (NOOA)<\/a> project is now available on GitHub<\/a> to make advanced AI safety capabilities more accessible for agent harnesses. The NOOA research framework enables harnesses to better integrate with models to make agent behavior easier to test, trace, audit and govern.<\/p>\n Across the Alliance, contributors are building an open defense stack for agents \u2014 from identity and isolation to safe model formats, multi-model scanning and secure coding workflows.\u00a0<\/p>\n HPE contributes to SPIFFE\/SPIRE<\/a>, which creates zero-trust identity framework standards and methods that can cryptographically verify AI agents and services to ensure only authorized workloads communicate and access enterprise resources.\u00a0<\/p>\n Hugging Face has offered Safetensors<\/a> \u2014 a safe format to store AI model weights, providing transparency and guarantees of no remote code execution \u2014 to the PyTorch Foundation.\u00a0<\/p>\n IBM and Red Hat\u2019s Lightwell<\/a> extends security across the open source supply chain with digitally signed patches.\u00a0<\/p>\n Microsoft\u2019s MDASH<\/a> multi-model agentic scanning harness orchestrates specialized AI agents to discover, debate and prove exploitable bugs.\u00a0<\/p>\n