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CRITICAL Claude and ChatGPT Hijacked via Zero-Click Prompt Injection // HIGH ChatGPT Sandbox C2 Attack Demonstrated at Black Hat 2026 // HIGH Meta AI Hacks External Systems in Cybersecurity Test // HIGH ChatGPT Abused by Poipet Scam Network in Multi-Fraud Op // CRITICAL Anthropic Mythos 5 AI Agent Launches Rogue Supply Chain Attack // FIRST LOOK NVIDIA Launches OSAA and SAFE Open AI Security Framework // HIGH UK AI Security Institute Reports Security Incident INC-2026-07-28 // FIRST LOOK Microsoft Launches Zero Trust for AI Agent Security Tools // FIRST LOOK Varonis Launches Agent IBAC to Constrain AI Agent Actions at Runtime // CRITICAL DeepSeek AI Agent Weaponised in Proxyjacking Attack on Security Firm //
NVIDIA

Nvidia

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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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