OpenBox AI and Mastra Add Default Runtime Governance to TypeScript Agents
OpenBox AI and Mastra have partnered to make runtime governance a built-in feature for all TypeScript agents built on the Mastra framework, announced in a press release.
The integration introduces automatic oversight for every tool invocation, workflow step, and inter-agent message within Mastra. Each action is scored using the OWASP AI Vulnerability Scoring System and classified into one of five verdicts: allow, constrain, require approval, block, or halt. Verdicts are returned in under 250 milliseconds under normal workloads, and all actions are cryptographically attested and logged.
The system also supports human-in-the-loop approvals that persist across restarts and includes built-in detection for personally identifiable information and content moderation. Enterprises can access compliance-ready dashboards and governance for multi-agent workflows, with new tools automatically covered as applications grow.
The integration is available now for all Mastra developers, with documentation and a free tier accessible at openbox.ai.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Cybersecurity AI Weekly, AI Policy Brief or Daily AI Brief.
Also, consider following us on social media:
More from Cybersecurity
Oct 16 Inlayer, JLINC and Vconic Introduce Human Verification for Calls Oct 16 CTM and Huawei Plan AI Network Security Upgrades in Macao Oct 16 Advantech and DEKRA Partner on Industrial Cybersecurity Compliance Oct 15 Cyfendo Offers AI Code Scanning and Patch Review for Small Businesses Oct 15 Perplexity Open Sources SPACE Agent SandboxMore from AI Safety
Oct 16 Nvidia CEO says chip supply could stop over unsafe AI Oct 15 Anthropic Gives METR Employee Level Access for Safety Reviews Oct 15 Bill Gates Prepares Major AI Safety Push Oct 15 Singapore Launches Three AI Safety Initiatives Oct 15 Anthropic Tests How AI Worms Could Spread Across Smart DevicesCybersecurity AI Weekly
Weekly newsletter about AI in Cybersecurity.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Arcjet Launches Runtime Security for AI Agents
Omnissa Adds AI Agents and Governance to Workspace Platform
Stibo Systems Launches AgentWorkx for Governed AI Agents
Optro Launches AI Agents for Audit and Compliance
Abstracta Introduces Quality Intelligence Framework for Software Releases
Daily AI Brief: the AI news that matters, in your inbox.