OpenClaw Launches Free Open-source Enterprise Agent Platform for AI Agents
OpenClaw launched OpenClaw Enterprise, a free open-source control plane for governed AI agents.
OpenClaw announced OpenClaw Enterprise on September 29, 2026, a free MIT-licensed platform for running persistent AI agents with multi-tenancy, sandboxing, fine-grained permissions, and audit records. The project began at OpenAI, was donated to the OpenClaw Foundation, and remains pre-1.0, so OpenClaw recommends internal pilots rather than broad production use. Red Hat and NVIDIA are collaborating on development, and OpenAI and Red Hat are piloting it internally. The announcement cites earlier OpenClaw indirect prompt-injection leaks and log poisoning, which are not newly disclosed OCE vulnerabilities.
- OpenClaw Enterprise is a free MIT-licensed control plane for persistent AI agents.
- It is still pre-1.0 and recommended for internal pilots, not broad production.
- Controls include sandboxing, fine-grained permissions, LLM reviews, and audit logs.
- It began at OpenAI and is now developed with Red Hat and NVIDIA.
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OpenClaw has launched OpenClaw Enterprise (OCE), a free, open-source platform that helps organizations run persistent AI agents with stronger security and central oversight.
Announced on September 29, 2026, the project targets businesses that want agents to handle ongoing work without giving them unchecked access to sensitive systems.
The platform remains under development ahead of its planned 1.0 release later this year. OpenClaw recommends it for internal pilot workloads, not as a finished product ready for broad production use.
OpenClaw Free Enterprise Platform
OCE adds an enterprise control plane, a central layer for deploying agents, setting rules, and tracking their activity. It supports multiple teams through multi-tenancy, with security boundaries intended to separate trusted services from untrusted workloads.
According to the platform announcement from OpenClaw, its security design combines sandboxing, fine-grained permissions, and reviews performed by large language models.
These controls aim to limit what agents can access and do while preserving their ability to complete useful tasks. Governance and audit records extend across the agent lifecycle, helping operators trace activity and review decisions.
The approach addresses a concern raised in OpenClaw’s announcement: many organizations still block agent platforms because shared security, safety, and governance standards remain weak. Agents that can read internal data, run code, or use plugins need controls beyond instructions telling them to behave safely.
That concern has practical roots. Cybersecurity News previously reported on OpenClaw data leaks through indirect prompt injection, where malicious instructions hidden in external content could trigger the release of sensitive information.
Separate coverage of log poisoning showed how attacker-controlled log entries could influence an agent’s troubleshooting context. Those reports concern earlier OpenClaw issues, not newly disclosed OCE vulnerabilities.
The project began at OpenAI before being donated to the OpenClaw Foundation, where it now operates independently. Red Hat and NVIDIA are collaborating on development. The public repository uses the MIT license, and the foundation says OCE will remain free for organizations to use.
Vendor neutrality is central to the design. Organizations can replace the model, sandbox, and agent harness- the software that connects the model to tools and tasks- with third-party or internal options. This lets teams keep their existing infrastructure rather than depend on one provider.
Organizations can self-host OCE using its GitHub repository and getting started documentation. Kubernetes supports internal deployment.
The current repository also notes that its default Compose preview runs the control plane but cannot deploy agents; the local agent walkthrough uses a Kubernetes profile. Free software does not remove infrastructure or model-service costs.
OpenClaw says OpenAI and Red Hat are piloting the platform internally. OpenAI staff member RJ Marsan described Androidclaw, an internal enterprise agent, helping investigate broken builds, locate incident records, and prepare fixes with supporting evidence.
These examples show why access control matters: an agent connected to code, logs, and collaboration tools can act across several sensitive systems.
The repository separates identity and role management from audit processing, including tools for removing sensitive values from audit events, offering another area for teams to inspect.
The foundation plans to publish a security reference architecture in the coming weeks. For security teams, the immediate value is an open platform they can inspect and test. Its early status also means organizations should verify isolation, permissions, audit coverage, and plugin behavior before expanding access to critical workloads.
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Guru Baranhttps://cybersecuritynews.com
Gurubaran KS is a cybersecurity analyst, and Journalist with a strong focus on emerging threats and digital defense strategies. He is the Co-Founder and Editor-in-Chief of Cyber Security News, where he leads editorial coverage on global cybersecurity developments.