「pii」の検索結果

Audits a codebase or business process for regulatory compliance across GDPR, HIPAA, SOC2, CCPA, and PCI-DSS. Scans for PII handling, data retention, encryption, access controls, audit logging, consent management, and data transfer issues. Generates a structured compliance report with findings, gap analysis, remediation steps, and evidence requirements.

日本語の概要は準備中です。原文の説明を表示しています。

Use when turning a personal agent skill into an open-source, distributable one. Runs a PII audit, generalizes personal details, checks licence compatibility, reviews cross-platform adapters and walks through packaging.

日本語の概要は準備中です。原文の説明を表示しています。

Evidence hygiene before any FIND moves to Completed or enters a report. Cookie redaction, PII black-bar, HAR sanitization, screenshot metadata strip. Run after /triage passes and before final report assembly.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when an agent needs AssemblyAI for speech-to-text or speech-understanding work in media production, including pre-recorded, synchronous short-file, and real-time streaming transcription; speaker diarization or speaker identification; captions and subtitles; timestamps; language detection, code-switching, or transcript translation; audio intelligence such as summaries, chapters, topics, entities, key phrases, sentiment, content moderation, profanity filtering, and PII redaction; webhooks, scaling, rate limits, retention, security, consent, and QA for podcasts, interviews, captions, call recordings, and edit workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Use Amazon Transcribe for AWS-based speech-to-text production: batch S3 transcription, real-time streaming, captions/subtitles, diarization, channel identification, custom vocabularies, vocabulary filters, language identification, PII/PHI handling, toxicity detection, Call Analytics, Medical, and secure S3/IAM/KMS workflows.

日本語の概要は準備中です。原文の説明を表示しています。

AssemblyAI is a hosted speech-to-text API that transcribes audio and video files or live streams and adds speaker labels, sentiment, entity detection, PII redaction and LLM analysis of the transcript. Use when a user asks to transcribe a recording, label who said what, analyze call sentiment, redact personal data, stream live transcription, or summarize and question a transcript with LLM Gateway (the replacement for LeMUR).

日本語の概要は準備中です。原文の説明を表示しています。

Pre-push hygiene check for GitHub repositories. Scans for PII, secrets, and sensitive data before pushing. Audits commit messages, enforces repo-specific blocklists, and rate-limits pushes to avoid GitHub abuse detection. Use before any git push, especially to public repos.

日本語の概要は準備中です。原文の説明を表示しています。

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

日本語の概要は準備中です。原文の説明を表示しています。

Automatically detect and de-identify PII (Personal Identifiable Information) and PHI (Protected Health Information) from clinical/medical text to ensure HIPAA compliance. Trigger when processing medical records, patient data, clinical notes, insurance information, or any healthcare-related text containing potential patient identifiers.

日本語の概要は準備中です。原文の説明を表示しています。

Use for security and trust boundaries. Triggers: auth, secrets, XSS, CSRF, SQL injection, JWT, OAuth, OWASP, PII, uploads, payments, supply chain, CI integrity, agent security, threat model.

日本語の概要は準備中です。原文の説明を表示しています。

Redact a network/MITM capture directory — JSONL, JSON, logs, HAR-style dumps — in place before it can be referenced publicly, scrubbing credential tokens, API keys, service ids, UUIDs, emails, home paths, usernames, and device or session hashes while preserving token-class prefixes for analysis and leaving public identifiers untouched. Covers class-preserving substitution, an idempotent re-runnable pass, distinguishing a secret from a public id, and verifying the scrubbed capture through the redaction gate. Use when a wire capture from a sanctioned probe must enter notes, a guide, or a public repo without leaking the session that produced it.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to sanitize memory for sharing, redact PII, or scan memory for credentials. Not for auditing memory: use memory-clean.

日本語の概要は準備中です。原文の説明を表示しています。

Provision a zero-config, no-signup, temporary Upstash Redis database for an AI agent with a single POST to https://upstash.com/start-redis, with no account, API key, or SDK setup required. Use when an agent needs scratch Redis right now and the user has not provided credentials, for short-term memory across tool calls, conversation history, a sub-agent work queue, ranked recall, or a quick prototype or demo. Covers idempotent creation and re-fetching credentials, calling the database through the body-style REST API or the official SDKs, and telling the user how to claim it. The database lives 3 days unless the user claims it; not for production data, PII, or secrets.

日本語の概要は準備中です。原文の説明を表示しています。

REQUIRED skill for any security-related request. Use this skill whenever the user wants to find anything dangerous, sensitive, or risky in their code, files, or repository. This includes but is not limited to: scanning for secrets/keys/tokens/credentials, checking dependencies for vulnerabilities, auditing destructive commands for missing safeguards, reviewing files for PII or internal data before open-sourcing, checking .env files or git history for leaked credentials, or any request where the concern is "is this safe/secure/exposed?" This skill provides a structured audit methodology and checklist you MUST follow — do not attempt security reviews without it. Skip this skill ONLY for pure feature work, refactoring, bug fixes, or non-security code review.

日本語の概要は準備中です。原文の説明を表示しています。

Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

日本語の概要は準備中です。原文の説明を表示しています。

Identify and exploit Cross-Origin Resource Sharing (CORS) misconfigurations. Use this skill when auditing APIs or web applications that share sensitive data across domains, forcing victims' browsers to inadvertently leak private information (e.g., API keys, PII, CSRF tokens) to an attacker-controlled website.

日本語の概要は準備中です。原文の説明を表示しています。

Legal, security, privacy, and deliverability requirements every delivered app must satisfy — legal pages, PII/deletion rights, CSP/Trusted-Types/Zod, AI-agent security, RFC7807 errors, email domain auth.

日本語の概要は準備中です。原文の説明を表示しています。

Backend code review patterns. Use when reviewing API routes, database operations, auth middleware, and server utilities. Covers injection, boundary validation, authorization coverage, secret/PII exposure, error leakage, and query patterns.

日本語の概要は準備中です。原文の説明を表示しています。

AI integration review patterns. Use when reviewing model API calls, prompt construction, LLM output handling, RAG pipelines, and tool-calling code. Covers prompt-injection call-chain tracing, output validation, token budgets, retry/timeout handling, streaming, and key/PII exposure.

日本語の概要は準備中です。原文の説明を表示しています。

用于生成或编辑图表、图形资产、海报、UI 样机、产品图、信息图、学术图、漫画、头像、分镜、品牌板或图像编辑工作流，尤其是导出 PNG 需要视觉质检和有限自动修复时。文字密集图表优先使用确定性的 Mermaid/SVG/HTML/canvas 源；浏览器可打开的技术图优先使用 HTML technical diagrams，覆盖系统蓝图、架构图、部署拓扑、Agent runtime、memory flow、before-after architecture、流程、序列、数据流、生命周期、runbook、PII/数据血缘和状态机；不要用于不涉及生成图像的普通 UI 打磨。中文触发词包括 图片生成、图像编辑、图表生成、架构图、系统蓝图、部署拓扑、Agent runtime、memory flow、before-after architecture、工作流图、数据流、生命周期图、状态机、ER 图、UML、序列图、海报、UI 样机、产品图、信息图、学术图、漫画、头像、分镜、品牌板、PNG 自检、自动修复。

日本語の概要は準備中です。原文の説明を表示しています。

Use when generating or editing diagrams, charts, visual assets, posters, UI mockups, product images, infographics, academic figures, comics, avatars, storyboards, brand boards, or image-edit workflows, especially when exported PNGs need visual QA and bounded self-repair. Prefer deterministic Mermaid/SVG/HTML/canvas sources for text-heavy diagrams; use HTML technical diagrams for browser-ready system blueprints, architecture, deployment topology, agent runtime, memory flow, before-after architecture, workflow, sequence, data-flow, lifecycle, runbook, PII/data-lineage, and state-machine diagrams. Do not use for ordinary UI polish without generated imagery.

日本語の概要は準備中です。原文の説明を表示しています。

Audit a government or public services system for compliance, fraud risk, and security — chains benefits processing review, fraud detection analysis, regulatory compliance check (ADA, Section 508, FISMA, Privacy Act), and PII-focused security audit. Use for benefits platforms, eligibility engines, enrollment portals, or inter-agency data systems.

日本語の概要は準備中です。原文の説明を表示しています。

Audit feature specs against India's Digital Personal Data Protection (DPDP) Act. Use this skill when: - Writing or reviewing any feature that handles user data (especially children's data) - Auditing a spec's Personal Information section for completeness - Checking a feature against DPDP Act 2023 requirements - Preparing compliance documentation before engineering review - Verifying masking, retention, and consent policies are defined for all PII

日本語の概要は準備中です。原文の説明を表示しています。

Cross-stack security review — auditing vulnerabilities across infrastructure, smart contracts, CI/CD pipelines, and AI agent systems, plus auth/sessions/crypto and validating user input at API and infrastructure boundaries. Triggers on mentions of "vulnerability", "pentest", "OWASP", "access control", "injection", "CSRF", "JWT", "smart contract audit", "supply chain", "OIDC", or any review of security-sensitive code paths spanning more than one layer. For PII sanitization see [security](../security/SKILL.md).

日本語の概要は準備中です。原文の説明を表示しています。