「access」の検索結果

Discovering and accessing unprotected pages, APIs, and administrative interfaces by enumerating URLs and bypassing authentication controls during authorized security assessments.

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。

Designs and implements VLAN-based network segmentation on managed switches to isolate network zones, enforce access control between segments, and reduce the attack surface by limiting lateral movement paths in enterprise network environments.

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。

Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.

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。

MITRE ATT&CK is a globally-accessible knowledge base of adversary tactics, techniques, and procedures (TTPs) based on real-world observations. This skill covers systematically mapping threat actor beh

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。

Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.

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。

Apply bottom-up and top-down role mining techniques to discover optimal RBAC roles from existing user-permission assignments, reducing role explosion and enforcing least privilege.

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。

Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.

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。

Parse and analyze Linux auditd logs to detect intrusion indicators including unauthorized file access, privilege escalation, syscall anomalies, and suspicious process execution using ausearch and Python.

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。

Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet.

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 for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

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。

Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".

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。

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".

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。

Enforce a configuration-driven design system when generating UI. Ensures consistent spacing, colors, typography, dark mode, interactions, and accessibility across all AI-generated components.

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 technical SEO — meta tags, structured data, Open Graph, sitemaps, robots.txt, performance, and accessibility signals.

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。

Signals scout that watches a PostHog project's most-viewed dashboards and insights for recent anomalies — sudden bursts, drops, flat-lines, and trend breaks at the daily or hourly level. It discovers what the team actually looks at (view counts, dashboard access), curates a durable watchlist in the scratchpad, and balances re-checking known high-value insights (exploit) against discovering new ones (explore) across runs, since no single run can cover a busy project. Anomalies are scored by robust deviation from each insight's own seasonality-matched baseline; it emits a finding only when a move clears the confidence bar, otherwise it updates the baseline memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

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。

Execute a user flow step-by-step in Cursor's built-in browser while documenting each action, then emit a Playwright test that replays the same flow using stable selectors derived from the accessibility tree.

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。

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

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。

Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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 GTK4/libadwaita app for GNOME HIG compliance across 12 categories (text, icons, layout, shortcuts, accessibility, color, dialogs, responsiveness, CSS, GSettings, i18n), then fix violations category by category. Use when asked to audit, review, polish, or "make HIG-compliant" a GNOME app, or before a release/Flathub submission.

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。

Build or improve UI test coverage for visual regression, interactions, and accessibility. Use when the user asks for a test strategy, automated tests, testing setup, or fixes to flaky UI tests. A one-time browser inspection or visual review does not require a new test suite.

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。

Design charts, metrics, and data tables that help users interpret and compare data. Use when the user asks to visualize data, choose chart types, improve dashboard analytics, or make data presentation accessible. Dashboard navigation and shell layout alone belong to add-ui or arrange.

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。

Evaluate an interface from a UX perspective, assessing hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with evidence-linked judgments and actionable feedback. Use when the user wants an overall design or UX review—not when the main need is measurable accessibility/performance diagnosis, or final micro-detail polish.

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 planning a Humans sprint — grooming the backlog into work batches and publishing the Peter-approved subset as a cloud sprint tracking issue. Runs locally with gh access to both 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。

Run multiple Reforge-guided section-refactor lanes in parallel, each in its own worktree/branch off origin/main, with a score-blind adversarial review panel gating every commit, one draft PR per section. Use when the user wants to reduce Reforge surface/internal score across several sections at once via architecturally-correct deletions (dead surface, entity-leak removal, cross-section consumers moved onto the public contract) — not by relocation, parameter bags, or accessibility-dodging. Wraps the per-lane process in .codex/skills/humans-refactor. Triggers: 'refactor swarm', 'parallel section refactors', 'run reforge refactor on Users/Tickets/...', 'burn down surface score across sections'. Has an intensity dial (light|standard|deep) and a workflow|solo execution mode to trade token burn against autonomy per unit of output.

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。