Nvidia is extending its agent-security and open-model stack through partnerships in South Korea. Hyundai Motor Group is exploring Nvidia NemoClaw blueprints and the OpenShell runtime, while Korean security company AIM Intelligence is integrating its Starfort control platform with OpenShell for employee-productivity and enterprise-agent workflows.

Nvidia describes OpenShell as a secure runtime offering sandboxed execution and policy-based controls for sensitive data, enterprise tools and autonomous actions. AIM Intelligence’s integration is intended to combine those runtime controls with detection for malicious instructions and data leakage, and the company is considering an initial proof of concept in the public-energy sector. Separately, LG AI Research is opening API access to K-EXAONE-2.5, developed using Nvidia Nemotron datasets. Nvidia says one of those resources contains seven million fully synthetic Korean personas grounded in official statistics.


Execution Level Governance- What audit-ready agent governance actually looks like
David Girvin, founder and CEO of Assury argues that model-in-the-loop review, AI governing AI, is fundamentally unreliable for regulated environments: even the best-performing models miss a meaningful share of violations, the reviewing model is typically provided by the same vendor being reviewed, and prompt injection or context poisoning can compromise both the acting agent and its supposed overseer simultaneously. He makes the case for deterministic, architecturally enforced controls instead, walking through Assury's approach of autonomy zones, session risk accumulation, and credential starvation, which lets a compromised agent be cut off from its tools instantly rather than relying on time-boxed access. The conversation touches on why David is sceptical of just-in-time credentialing as a solution for agent security more broadly, since agent sessions don't run on predictable human timescales, along with the current gap between how identity and security vendors are pitching agent protection and what he sees happening at the execution layer in practice. He also discusses the compliance and audit implications of probabilistic decision-making, arguing that regulated industries will increasingly need tamper-evident, hash-chained audit trails that can withstand scrutiny from auditors and regulators who are only beginning to understand agentic risk, and reflects on a named frontier lab's own published framework as an example of the gap between research and practitioner reality. Elsewhere, David reflects candidly on building a bootstrapped security company in an increasingly crowded market, why he turned down aggressive VC funding to stay in control of the product, and what a credible third-party assessment of his own gateway would need to look like given that Assury sits directly in the execution path for every customer's agents.
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