NvidiaSaša Zdjelar4 min readintermediate
AI Security Is an Engineering Problem — How to Solve It at Every Layer of the Agent Stack
Summary
Nvidia frames AI security as an engineering discipline, outlining required controls across the AI agent stack (model, harness, runtime) and advocating for enforceable boundaries, traceable identities, and evidence‑based testing. It highlights OpenShell as a sandboxed runtime, the Open Secure AI Alliance, and several vendor tools for testing and red‑team exercises.
- Security requirements for AI agents must be defined, owned, and verifiable at every stack layer (model, harness, runtime).
- Enforceable runtime policies (e.g., via OpenShell) are needed to limit file, network, and process access independent of the agent’s reasoning.
- Agents require scoped identities and credentials; permission changes must be gated by human approval.
- Testing must include attempts to exfiltrate data, elevate privileges, or tamper with monitoring, and be repeated after any material change.
As AI agents gain autonomous reasoning and tool use, they become a new attack surface that can bypass traditional perimeter controls. Treating AI security as an engineering problem forces organizations to embed identity, policy enforcement, and auditability into the core runtime, reducing the risk…
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