Source
AI Security Is an Engineering Problem — How to Solve It at Every Layer of the Agent Stack
AI security is framed as an engineering problem that requires enforceable boundaries, traceable identities, and evidence that protections work across the agent stack.
Why it matters
As AI agents take on more autonomous tasks, businesses need strict boundaries to prevent agents from leaking sensitive data or executing unauthorized actions.
The big picture
This article elaborates on the security standards and tools supported by the Open Secure AI Alliance, of which NVIDIA is a member.
The details
- NVIDIA OpenShell is an open source runtime providing sandboxed execution and policy enforcement. - Tools like CrowdStrike’s SafeMind and Palo Alto Networks Prisma AIRS provide security testing. - Capital One’s VulnHunter and ReversingLabs’ Spectra Assure use AI to detect vulnerabilities. - Deployment should be managed by a named owner based on evidence from repeatable tests.
What's next
The industry is called to accelerate security engineering and increase the sharing of defensive tools and research.
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In this article
Technologies
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Key connections
Cisco owns DefenseClaw
JFrog uses NVIDIA OpenShell
JFrog integrates with OpenShell to scan and verify agent skills
CrowdStrike owns SafeMind
JFrog is a member of Open Secure AI Alliance
Open Secure AI Alliance partners are building on OpenShell: ... JFrog integrates with OpenShell
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