Industry Leaders Unite in Open Secure AI Alliance for AI Safety and Security

NVIDIA and the Linux Foundation, joined by more than 30 industry leaders including Adobe, Cisco, CrowdStrike, Google, IBM, Microsoft, and Red Hat, launched the Open Secure AI Alliance to develop and share open technologies, techniques, and tools for safeguarding software and AI agents. The alliance aims to democratize defensive capabilities and avoid single points of failure, building on the Linux Foundation's Akrites initiative and OpenSSF community work. The effort was underscored by a recent Hugging Face security incident where open-weight GLM 5.2 model analyzed over 17,000 actions to contain an intrusion after closed AI tools blocked forensic analysis.

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. Cybersecurity is among the top three beneficiaries of open source software. The Open Secure AI Alliance — building on the leadership of the Linux Foundation’ https://www.linuxfoundation.org/blog/the-state-of-open-source-software-in-2025 s Akrites https://www.linuxfoundation.org/press/linux-foundation-and-industry-leaders-launch-akrites-to-defend-critical-open-source-software-against-ai-enabled-cyber-threats initiative and OpenSSF https://openssf.org/ community work — will work to remediate and disclose vulnerabilities using open technologies. 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. The world needs both closed and open models https://www.nvidia.com/en-us/glossary/open-models/ . 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 – with no single point of failure. Open models, like any powerful technology, can be misused — including through attempts to weaken safeguards or repurpose capabilities for cyber attacks — but those risks are not unique to open systems, and they must be managed wherever advanced AI is deployed. The recent Hugging Face security incident https://huggingface.co/blog/security-incident-july-2026 delivered a clear reminder: cyber defenders need open, frontier agentic systems for self-defense. When closed AI tools — unable to distinguish attackers from defenders — 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. 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. That is the mission of the Open Secure AI Alliance: to ensure defenders everywhere have open, frontier tools they can trust and control. Leaders across cloud computing, cybersecurity, enterprise software, open source foundations and AI research — including NVIDIA, Adobe, Cadence, Capital One, Cisco, Cloudera, Cloudflare, Cognition, CrowdStrike https://www.crowdstrike.com/en-us/blog/crowdstrike-joins-open-secure-ai-alliance , Databricks, Dell Technologies, DoorDash, Elastic, HPE https://www.hpe.com/us/en/newsroom/blog-post/2026/07/hpe-joins-open-secure-ai-alliance-to-advance-open-cybersecurity-innovation.html , Hugging Face, IBM, LangChain, the Linux Foundation, Microsoft, NAVER, NetApp, Nous Research, OpenClaw, Palantir, Palo Alto Networks, Red Hat https://www.redhat.com/en/blog/strengthening-open-source-defense-layer-red-hat-joins-nvidias-open-secure-ai-alliance , Reflection AI, Salesforce, SAP, SK Telecom, ServiceNow, Siemens, 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. 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. 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. 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. Open Research Enhances Cybersecurity and AI Safety An AI agent isn’t just a language model. It is a complex system built from models, harnesses and guardrails. Real AI safety and security depend on the full agent stack — identity, permissions, harnesses, guardrails, logs and evaluation — 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. 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. The new open source NVIDIA Labs Object-Oriented Agent NOOA https://developer.nvidia.com/blog/six-agent-harness-capabilities-for-higher-model-performance/?ncid=prsy-823400 project is now available on GitHub https://github.com/NVIDIA-NeMo/labs-OO-Agents/tree/main 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. Across the Alliance, contributors are building an open defense stack for agents — from identity and isolation to safe model formats, multi-model scanning and secure coding workflows. HPE contributes to SPIFFE/SPIRE https://spiffe.io/ , 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. Hugging Face has offered Safetensors https://github.com/safetensors/safetensors — a safe format to store AI model weights, providing transparency and guarantees of no remote code execution — to the PyTorch Foundation. IBM and Red Hat’s Lightwell https://www.redhat.com/en/about/press-releases/ibm-and-red-hat-expand-lightwell-new-offerings-build-trust-infrastructure-ai-era-open-source extends security across the open source supply chain with digitally signed patches. Microsoft’s MDASH https://www.microsoft.com/en-us/security/blog/2026/05/12/defense-at-ai-speed-microsofts-new-multi-model-agentic-security-system-tops-leading-industry-benchmark/ multi-model agentic scanning harness orchestrates specialized AI agents to discover, debate and prove exploitable bugs. SpaceXAI has open sourced the Grok Build https://x.ai/open-source terminal-based AI coding agent to promote trust, transparency and new capabilities, and plans to open source the weights of the Grok line of models to support the developer and research communities. A Call to Policymakers and Regulators As policymakers and regulators grapple with AI safety, it will be crucial to recognize open models, harnesses and security tooling as defensive assets, not liabilities, in AI and cybersecurity policy. Blanket restrictions on open frontier AI systems would weaken defensive capacity and risk concentrating power, dependence and vulnerability in a few closed providers. Companies and governments should invest in shared open infrastructure for AI defense — datasets, evaluation frameworks, attack simulators and red-teaming tools — much as past generations invested in open source software. The Future We Should Build The age of AI agents can be one of resilience and shared security. With the right choices, open secure AI systems can give defenders the tools they need, strengthen competition, extend technological leadership and ensure that the safety and security of this extraordinary technology are built in the open for everyone. That future will not be secured by assuming that secrecy alone is safety. It will be secured by building systems that are strong enough to withstand scrutiny, flexible enough to be improved and open enough to mobilize the full community of defenders. That future is worth building — and the Open Secure AI Alliance invites governments, industry and researchers to join in the work of defending the AI era together. Learn more or share interest in joining the Open Secure AI Alliance.