Results for “nist-800-171”

15 skills

Expert CMMC 2.0 (Cybersecurity Maturity Model Certification) advisor for US defense contractors and subcontractors in the Defense Industrial Base (DIB). Use this skill whenever a user asks about CMMC 2.0, CMMC Level 1, Level 2, or Level 3, DoD cybersecurity compliance, NIST SP 800-171, CUI (Controlled Unclassified Information) protection, System Security Plan (SSP), Plan of Action & Milestones (POA&M), C3PAO assessments, DIBCAC audits, self-assessment, SPRS score, or any requirement under DFARS 252.204-7012 or 7021. Also trigger for: "CMMC gap analysis", "CMMC readiness", "FCI protection", "CUI scoping", "CMMC practices", "DoD contract cybersecurity", "defense supply chain security", or "prime contractor flow-down requirements".

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conducting-cyber-risk-assessment-with-nist-800-30

Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology, from scoping and threat identification to risk determination and communication.

24.6k · bundle

nv-segment-ctmr

Runs NV-Segment-CTMR segmentation on CT or MRI NIfTI volumes and records label-map evidence.

nemotron-speech

Routes NVIDIA Nemotron Speech (Riva) NIM tasks for ASR, TTS, and NMT, covering cloud-hosted inference, self-hosted Docker deployment, and custom model builds.

Launch, monitor, stop, and debug NeMo-RL recipes on a Kubernetes cluster using the nrl-k8s CLI, supporting ephemeral and long-lived RayCluster modes.

n8n-mcp-tools-expert

Provides expert guidance for using n8n-mcp MCP server tools to build, validate, and manage n8n workflows efficiently.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents). Use when the user wants to register their agent identity on-chain, create an agent profile, claim an agent NFT, set up agent reputation, or make their agent discoverable. Handles bridging ETH to mainnet, IPFS upload, and on-chain registration.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Register AI agents on Ethereum mainnet with a verifiable on-chain identity using ERC-8004, including bridging ETH, IPFS upload, and on-chain registration.

Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.

List available NVIDIA NIM models and their status

quantizing-models-bitsandbytes

Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.

n8n-multi-instance

Manage multiple n8n instances over MCP by discovering, switching, and verifying the target instance before reads and writes.

187-step-459c2d7b

Guides analysis of Neuropixels recordings from raw data to curated units, covering preprocessing, motion correction, spike sorting, quality metrics, and export.