Results for “nist-privacy-framework”

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.

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.

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.

Builds AWS Nitro Enclave-based confidential computing environments with cryptographic attestation, KMS policy integration, and secure vsock communication for processing sensitive data.

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.

Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

Finetunes the NV-Generate-CTMR MR-brain diffusion UNet from user-supplied NIfTI training volumes using a wrapper that stages configs and delegates to upstream scripts.

Analyze git repositories to build a security ownership topology mapping people to files, compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization.

GDPR and CCPA/CPRA privacy compliance audit for codebases. Inventories PII fields (email, phone, SSN, IP, device ID, geolocation, biometrics, behavioral data), maps data collection points (forms, APIs, cookies, analytics, error tracking), audits consent mechanisms (cookie banners, opt-in, pre-checked boxes, consent withdrawal), verifies data subject rights implementation (right to access, erasure, rectification, portability, opt-out, Do Not Sell), traces third-party data sharing (Google Analytics, Facebook Pixel, Stripe, SendGrid, Sentry), and checks data retention policies and automated purging. Use when auditing privacy compliance, building data export or deletion endpoints, reviewing cookie consent, or assessing DSAR readiness.

Nigeria Data Protection Regulation (NDPR) and Nigeria Data Protection Act (NDPA) 2023 compliance. Covers lawful basis for processing, data subject rights, cross-border transfer mechanisms, Data Protection Compliance Organisation (DPCO) registration, mandatory DPIA filing, and breach notification. Keywords: NDPR, NDPA, Nigeria, NITDA, DPCO, Africa data protection, cross-border transfer.

NestJS 架构模式，涵盖模块、控制器、提供者、DTO 验证、守卫、拦截器、配置以及生产级 TypeScript 后端。

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Implements AI transparency requirements under EU AI Act Arts. 13-14 and GDPR Arts. 13-14. Covers user notification of AI interaction, system capability disclosure, limitation documentation, and meaningful information about automated logic. Keywords: AI transparency, EU AI Act, GDPR notification, explainability, automated decision.

Applies the PCI-DSS framework to identify, assess, and mitigate security risks in systems, processes, and data handling.

Conduct a maturity assessment against the NIST Cybersecurity Framework (CSF) 2.0, using Implementation Tiers to measure organizational cybersecurity posture and create improvement roadmaps.

Implement JWT authentication, RBAC guards, Helmet hardening, and Argon2 hashing in NestJS. Use when adding auth strategies, role-based access control, CSRF protection, or security headers.

防止 JavaScript 和 TypeScript 中的以太坊哈希错误。Node 的 sha3-256 是 NIST SHA3，而非以太坊 Keccak-256，会静默破坏选择器、签名、存储槽和地址推导。

Automates GDPR Data Subject Access Request (DSAR) workflows including identity verification, PII discovery across databases and files using regex and NER, data mapping, response templating per Article 15 requirements, deadline tracking, and audit logging.

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.

Prevent Ethereum hashing bugs in JavaScript and TypeScript. Node's sha3-256 is NIST SHA3, not Ethereum Keccak-256, and silently breaks selectors, signatures, storage slots, and address derivation.

Provides production-grade NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and testing.

Provides production-grade NestJS architecture patterns covering modules, controllers, providers, DTO validation, guards, interceptors, exception filters, configuration, and testing for TypeScript backends.

Detect and prevent public-over-private name resolution in npm, PyPI, and Maven dependency manifests.

NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and production-grade TypeScript backends.

List available NVIDIA NIM models and their status

Identify sensitive data exposure vulnerabilities including API key leakage, PII in responses, insecure storage, and unprotected data transmission during security assessments.

Performance Profiler

AI safety and responsible AI practices

Performs advanced network reconnaissance using Nmap's scripting engine, timing controls, evasion techniques, and output parsing to discover hosts, enumerate services, detect vulnerabilities, and fingerprint operating systems across authorized target networks.

Use before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.

Provides comprehensive NestJS framework patterns with Drizzle ORM integration. Use when building NestJS applications, setting up APIs, implementing authentication, working with databases, or integrating Drizzle ORM. Covers controllers, providers, modules, middleware, guards, interceptors, testing, microservices, GraphQL, and database patterns.

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.