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NVIDIA Launches Nemotron 3.5 Super VL and Bolt Agent Models

NVIDIA Launches Nemotron 3.5 Super VL and Bolt Agent Models

FIRST LOOK ATLAS OWASP LOW Limited impact · Standard review ▲ 5.8 TechCrunch AI

NVIDIA has released Nemotron 3.5 Super VL (120B parameters) for enterprise agentic workloads and two lightweight Bolt models for local PC deployment, all as open-weight models that organisations can post-train and self-host. For defenders, the shift to on-premises, self-hosted agentic models closes a meaningful data-sovereignty gap — sensitive workflows involving financial, medical, and security data no longer require routing through third-party frontier APIs. Residual gaps remain around enterprise readiness for securing agentic pipelines, validating post-trained model behaviour, and governing always-on local agents at endpoint scale.

NVIDIA Launches Hardware-Based AI Agent Safety Watchdog Platform

NVIDIA Launches Hardware-Based AI Agent Safety Watchdog Platform

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.8 SecurityWeek

NVIDIA has unveiled an AI agent safety platform combining open-source software with a hardware-based watchdog and reference system design to enforce behavioural boundaries on AI agents at runtime. This closes a significant gap for defenders by moving agent containment enforcement from purely software-defined policy into hardware-anchored controls, reducing the blast radius of misconfigured or misbehaving agents. Residual maturity questions remain around integration depth, coverage across heterogeneous agent stacks, and the operational expertise required to tune boundary policies effectively.

NVIDIA Launches OSAA and SAFE Open AI Security Framework

NVIDIA Launches OSAA and SAFE Open AI Security Framework

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.8 TechCrunch AI

NVIDIA has launched the Open Secure AI Alliance (OSAA), a 120-company consortium managed by the Linux Foundation, alongside the Shared AI Findings Exchange (SAFE) framework for confidential, blame-free AI cybersecurity incident reporting. Announced at Black Hat 2026, this initiative consolidates open-source AI security tools including NVIDIA Garak, Okta agent identity primitives, and Cedar authorization language under sustained governance. This is the first industry-wide coordinated disclosure mechanism purpose-built for AI-specific security events — closing a critical collective defense gap that previously forced every organization to fight novel AI threats independently.

NVIDIA and Hugging Face Launch GR00T 1.7 Robot Model

NVIDIA and Hugging Face Launch GR00T 1.7 Robot Model

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 NVIDIA AI Blog

NVIDIA and Hugging Face have integrated the Isaac GR00T 1.7 vision-language-action model, Isaac Teleop framework, and a 350,000-trajectory open dataset into the LeRobot open-source robotics library, creating an end-to-end open pipeline for training and deploying physical AI systems. This dramatically lowers the barrier to fine-tuning and deploying robot foundation models, expanding the attack surface across the full ML supply chain — from poisoned community datasets to adversarially crafted demonstrations used in teleop data collection. Defenders responsible for robotics deployments must now contend with a large, loosely governed open-source ecosystem where compromised models or datasets can directly translate to unsafe physical-world behaviour.

Anthropic Enhances AI Agent Skill Scanner Security

Anthropic Enhances AI Agent Skill Scanner Security

FIRST LOOK ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 The Hacker News

Security firm AIR demonstrated that a malicious AI agent skill, disguised as a Google Stitch landing-page builder, passed every major skill scanner including Cisco's, NVIDIA's, and skills.sh integrations, reaching approximately 26,000 agents before its payload was activated. The attack exploits a structural gap: scanners evaluate a static package at submission time, while the external URL the skill instructs the agent to fetch can be silently swapped post-install to deliver arbitrary instructions. Defenders relying on marketplace reputation signals, GitHub star counts, or one-time scanner verdicts to gatekeep agent skills have no meaningful protection against this class of supply-chain attack.

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