NVIDIA launches OpenShell agent sandbox with more than 100 partners

🚀 RELEASES & LAUNCHES

• NVIDIA launches OpenShell agent sandbox with more than 100 partners
  NVIDIA introduced OpenShell, an open-source runtime for enforcing AI-agent safety boundaries.

  • For developers and organizations deploying AI agents.
  • OpenShell provides enforceable runtime limits, action tracing, and policy enforcement.
  • NVIDIA introduced it alongside Sentry in an Open Agent Safety Platform with more than 100 industry partners.
  • The platform moves agent safety controls from prompt rules into runtime enforcement.
  Sources 📄 Source: nvda.ws · 📎 Coverage: x.com · 👁 via r/LocalLLaMA

• Hcompany launches Holo4 generalist computer-use agent models
  Hcompany released Holo4, a generalist computer-use agent series.

  • Holo4 targets developers building agents for desktops, web apps, Android, code sandboxes and business APIs.
  • The series includes 27B dense and 35B-A3B MoE models, available through the H Models API, plus Holotron4 Nano.
  • Holo4 can interact through GUIs, code, MCP and APIs, using the interface best suited to each task.
  • On OSWorld 2.0, Holo4 27B scored 61.7% and Holo4 35B-A3B scored 30.9%; Hcompany reports lower costs than frontier models.
  Sources 📎 Coverage: huggingface.co · 👁 via Hugging Face Blog

• Developer wraps Apple’s built-in local LLM for Node and Python
  A developer released apple-llm to access Apple’s built-in models from Node and Python.

  • Apple Silicon developers on macOS 26 or later can use the package; Intel Macs, Linux, and Windows are unsupported.
  • apple-llm provides npm and pip packages for Apple’s on-device AFM 3 Core Advanced model, roughly 20B sparse with 1–4B active parameters and an 8,192-token context on macOS 27.
  • The library supports text generation, schema-constrained JSON, streaming, tool calls, and an optional Private Cloud Compute tier.
  • The on-device tier requires no API key or account and keeps prompts on the Mac, enabling private extraction, tagging, summarization, and rewriting without installing a separate model runtime.
  Sources 📄 Source: github.com · 📎 Coverage: reddit.com · 👁 via r/LocalLLaMA

🔬 RESEARCH

• Xyntetik-Kvist-14B distills Muse-Glimmer-30B for local tool use
  Joakimpalm-Zen released Xyntetik-Kvist-14B, a distilled 14.4B-parameter agent model.
  • Local developers and agent builders can use the model for tool-calling workflows.
  • The Apache 2.0 model was width-pruned from Muse-Glimmer-30B and distilled for 6,000 steps plus 1,440 agentic-training steps.
  • It solved 57 of 60 held-out closed-loop tasks, compared with 60 of 60 for its parent, and produced 99 of 99 valid tool calls.
  • Its Q8_0 build uses 15.4 GB and its Q5_0 mix uses 10.3 GB, fitting fully on a 24 GB GPU.
  • The release provides OpenAI-, Anthropic-, and Responses-compatible serving through Xyntetik Runner v0.5.7 or later.
  Sources 📄 Source: huggingface.co · 📎 Coverage: reddit.com · 👁 via r/LocalLLaMA

⚠️ INCIDENTS & SAFETY

• Local Qwen Model Modified LSASS Dumper to Evade Two EDR Products
  A local modified Qwen 3.8 27B model produced an LSASS credential dumper that evaded two EDR products in a lab.
  • The experiment targeted security researchers and defenders evaluating AI-assisted offensive-tool development.
  • Eddie Zhang used an uncensored, community-modified Qwen 3.8 27B running locally on a rig with two Nvidia RTX 4090 GPUs.
  • The model altered an LSASS dumper with reduced access masks, randomized delays, changed output paths, and scrubbed embedded strings.
  • The revised executable reportedly generated no detections from either of two unnamed EDR products in the controlled lab, showing how local models can help create environment-specific offensive-tool variants.
  Sources 📄 Source: projectblack.io · 📎 Coverage: cybersecuritynews.com · 👁 via r/LocalLLaMA