Results for “nist-sp-800-161”

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.

Implement the NIST Privacy Framework PROTECT function covering PR.AC access control, PR.DS data security, and PR.PO protective policies. Provides technical control implementation guidance, encryption standards, access management architectures, and security-privacy integration patterns.

Implement the NIST Privacy Framework CONTROL function covering CT.DM data management, CT.DP data processing policies and procedures, and CT.PO disassociated processing. Provides technical control architectures, data management workflows, and de-identification implementation guidance.

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

Develop and implement OT-specific incident response playbooks aligned with SANS PICERL framework, IEC 62443, and NIST SP 800-82 that address unique ICS challenges including safety-critical systems, limited downtime tolerance, and coordination between IT SOC, OT engineering, and plant operations teams.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Guide federal systems through the NIST Risk Management Framework (SP 800-37 Rev 2) to achieve an Authorization to Operate (ATO), covering categorization, control selection, assessment, and continuous monitoring.

Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors (Sycamore/Weber), designing noise-aware NISQ circuits, or running characterization experiments (randomized benchmarking, XEB). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.

Designs and documents structured incident response playbooks aligned with NIST SP 800-61r3 and SANS PICERL frameworks, covering playbook structure, decision trees, escalation criteria, RACI matrices, and SOAR integration.

Assess security of SCADA HMI systems by evaluating authentication, communication, web interfaces, and hardening against IEC 62443 and NIST SP 800-82 guidelines.

Implement the NIST Privacy Framework COMMUNICATE function covering CM.AW awareness raising and CM.PO communication policies. Provides transparency mechanisms, stakeholder engagement frameworks, privacy notice templates, and communication workflow guidance.

Security vulnerability scanner and OWASP compliance auditor for codebases. Dependency scanning (npm audit, pip-audit), secret detection (high-entropy strings, API keys), SAST for injection/XSS vulnerabilities, and security posture reports. Activate on 'security audit', 'vulnerability scan', 'OWASP', 'secret detection', 'dependency check', 'CVE', 'security review', 'penetration testing prep'. NOT for runtime WAF configuration (use infrastructure tools), network security/firewalls, or compliance certifications like SOC2/HIPAA (legal/organizational).

Triages security incidents by classifying type, assigning severity based on business impact, enriching with threat intelligence, and routing to appropriate response teams using NIST SP 800-61r3 and SANS PICERL frameworks.

Deploy CyberArk Privileged Access Management to discover, vault, rotate, and monitor privileged credentials across enterprise infrastructure, covering vault architecture, session isolation, credential rotation policies, and NIST 800-53 integration.

VIPER v2.1 — Range-bound liquidity sniper. Enters at support/resistance when Bollinger Bands are tight, ATR is low, RSI is at extremes within the range, and volume is declining. Works when nothing is trending — the chop predator. USD-weighted OI filtering (min $5M). DSL High Water Mode (mandatory). 5-minute scan interval. Second-best performer in the Senpi zoo at +6.2% ROI.

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

Run the standard single-cell RNA-seq analysis pipeline with Scanpy on AnnData — QC filtering, normalization, dimensionality reduction (PCA, UMAP, t-SNE), Leiden/Louvain clustering, marker/differential expression, PAGA trajectories, and plotting. Use when analyzing scRNA-seq data through clustering, cell-type annotation, DE, or pseudotime workflows; for building or reading the .h5ad data structure itself (layers, obs/var, concatenation, backed mode) prefer alterlab-anndata instead, and for RNA velocity from spliced/unspliced counts prefer alterlab-scvelo instead. Part of the AlterLab Academic Skills suite.

Runs standard single-cell RNA-seq analysis with Scanpy, covering QC, normalization, dimensionality reduction, clustering, marker identification, visualization, and conversion of R single-cell formats to h5ad.

Programs ESP32 microcontrollers in C/C++ or MicroPython. Use for IoT projects with WiFi/Bluetooth.

Simulates ARP spoofing attacks in authorized lab or pentest environments using arpspoof, Ettercap, and Scapy to demonstrate man-in-the-middle risks, test network detection capabilities, and validate ARP inspection countermeasures.

Consume and produce STIX/TAXII 2.1 cyber threat intelligence feeds using Python, including server discovery, collection polling, object parsing, and SIEM/TIP integration.

Set up and verify a connection to an NI USRP radio (USRP E320, N300, N310, N320, N321, X300, X310, or X410) using Wireless Testbench. Use when connecting a USRP for the first time, configuring radio hardware, troubleshooting connection failures, or verifying a radio setup. Covers host inspection (OS, NIC type/speed/MTU), device discovery (findsdru, probesdru), UHD version checking, programmatic radio configuration, and basebandTransceiver verification. Also use when the user mentions USRP setup, radio not found, connection errors, dropped samples, or network configuration for SDR hardware.

Enforces identity-based network access with 802.1X, RADIUS authentication, dynamic VLAN assignment, and endpoint posture assessment using PacketFence.

Expert NIST Cybersecurity Framework (CSF) advisor covering CSF 2.0 and CSF 1.1. Use this skill whenever a user asks about NIST CSF, cybersecurity risk management, the six CSF functions (Govern, Identify, Protect, Detect, Respond, Recover), CSF profiles, implementation tiers, gap assessments, organizational profiles, community profiles, CSF core subcategories, informative references, or mapping to other frameworks (NIST SP 800-53, ISO 27001, CIS Controls, COBIT). Also trigger for questions like "how do I implement NIST CSF?", "what does CSF 2.0 change?", "help me build a CSF profile", "how do I assess my cybersecurity posture?", or any request involving organizational cybersecurity risk strategy or framework alignment.

Security Practices — Cryptographic Safety, Memory Zeroization & Hardened I/O

NER with Spacy. named entity recognition.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identific...

Scales reinforcement learning with PufferLib — high-throughput parallel training (PuffeRL), vectorized environments, and native multi-agent systems achieving 2-10x speedups over standard implementations. Use when scaling RL to millions of steps per second, running vectorized or multi-agent setups, building custom PufferEnv tasks, or integrating game environments (Atari, Procgen, NetHack, PettingZoo). For standard single-agent algorithm implementations (PPO/SAC/DQN) or quick prototyping prefer alterlab-stable-baselines3. Part of the AlterLab Academic Skills suite.

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

SVIT: Scaling up Visual Instruction Tuning

>- Run automatic SPICE simulations on subcircuits detected from KiCad schematic analysis — validates filter frequencies, divider ratios, opamp gains, LC resonance, and crystal load capacitance. Supports ngspice, LTspice, and Xyce (auto-detected). Generates testbenches, runs batch mode, produces structured pass/warn/fail report. Use when the user asks to simulate, verify, or validate any analog subcircuit — RC filters, LC filters, voltage dividers, opamp circuits, crystal oscillators. Also for "simulate my circuit", "run spice", "verify with simulation", "check my filter cutoff", "does this divider give the right voltage", "what's the bandwidth of this opamp stage". Consider suggesting simulation during design reviews when the schematic analyzer reports simulatable subcircuits and a SPICE simulator is available.

Controls IP cameras via RTSP for snapshots and recording, and ONVIF for PTZ movement, presets, and network discovery, with support for common camera brands.

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

Implement the NIST Privacy Framework IDENTIFY function including ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Provides control mapping, gap analysis templates, and implementation workflows for privacy risk identification.