「rdp」の検索結果

Produces WordPress draft posts from research findings — converts Paper Store research records or raw research data into publishable blog posts, buying guides, brand spotlights, and how-to articles. Use when the task asks to "turn research into a post", "create a blog post from findings", "publish my research", "research to content", or "write up the findings". Covers the full research-to-post pipeline with Paper Store integration.

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Publish and schedule content to social media platforms (Twitter/X, Facebook, Instagram, LinkedIn) via the MCP bridge schedule_social_post tool as primary. The Design Stack media worker API is the fallback for advanced platform management. Covers platform-specific formatting, media attachment, scheduling, and WordPress-to-social publishing workflows. Use when posting to social platforms, scheduling future posts, attaching media to posts, checking optimal timing, or debugging API delivery failures.

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Design and implement typography systems for web and brand projects. Covers font pairing, type scales, variable fonts, web font loading strategies (font-display, subsetting), CSS typography best practices, and WordPress theme typography integration. Use when selecting fonts, building type scales, loading web fonts, configuring theme.json typography, or fixing font performance issues.

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End-to-end media pipeline automation — from AI generation through optimization to social publishing. Covers workflow design, WordPress integration, Redis job queuing, batch processing, multi-site pipelines, and orchestration. MCP bridge tools are the primary interface for individual operations; the Design Stack media worker handles batch and advanced processing. Use when you need to automate image generation→optimization→publishing chains, set up cross-site media sync, design batch processing pipelines, or orchestrate multi-step media workflows triggered by post publish or cron.

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Implement iOS authentication patterns including Sign in with Apple (ASAuthorizationAppleIDProvider, ASAuthorizationController, ASAuthorizationAppleIDCredential), credential state checking, identity token validation, ASWebAuthenticationSession for OAuth and third-party auth flows, ASAuthorizationPasswordProvider for AutoFill credential suggestions, and biometric authentication with LAContext. Use when implementing Sign in with Apple, handling Apple ID credentials, building OAuth login flows, integrating Password AutoFill, checking credential revocation state, or validating identity tokens server-side.

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Fast BPE/WordPiece tokenization and custom vocab training.

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Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.

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Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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Deploy Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points. This skill covers Duo integration methods, adaptive authentication policies, device trust

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Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.

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Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.

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Use this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

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Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between 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。

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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 Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points. This skill covers Duo integration methods, adaptive authentication policies, device trust

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Hunting skill for business logic vulnerabilities. Built from 12 public bug bounty reports. Covers coupon-race-stacking (Instacart, Stripe, Reverb), negative-quantity-in-cart price tampering (Upserve, Eternal/Zomato), decimal/fraction price-field overflow (Shipt), client-side checkout amount trust on PayPal redirect (WordPress.org), price-per-unit mass-assignment (Krisp), and archived-price swap / cart-TOCTOU (Stripe). Use when hunting business logic — heavy emphasis on financial-impact-demonstrated cases.

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Initial access techniques checklist: phishing (spear/smishing), credential stuffing, exposed service exploitation, supply chain attacks, watering hole, VPN/RDP brute force, public-facing application exploitation. Maps to MITRE ATT&CK TA0001. Use when planning initial access phases of red team engagements.

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Hunting skill for auth bypass vulnerabilities. Built from 12 public bug bounty reports across SAML XSW / parser-differential (GitHub Enterprise CVE-2025-25291/25292), SAML signature stripping (Uber, Rocket.Chat, samlify CVE-2025-47949), SAML domain enforcement bypass via control characters (HackerOne 2024), partner-portal cross-IdP assertion reuse (Slack), WordPress XMLRPC bypassing SSO (Uber), JWT alg-confusion HS256/RS256 (Jitsi), JWT signature-validation skip (Linktree, Newspack), and token-audience confusion (Argo CD CVE-2023-22482). For standalone JWT signature/crypto forging (alg:none, key confusion, kid/jku) see hunt-jwt-crypto; this skill covers JWT only inside SSO/SAML/token-trust bypass chains. SAML assertion-layer attacks (XSW, comment injection, signature stripping, XXE-in-assertion) are owned by hunt-saml; this skill owns the broader cross-protocol auth-bypass taxonomy. Use when hunting auth bypass — see the Legacy-Protocol Matrix for branded-UI vs legacy-endpoint patterns.

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Comprehensive lateral movement tradecraft for authorized red team engagements covering credential-based movement (pass-the-hash, pass-the-ticket, overpass-the-hash), NTLM relay attacks (ntlmrelayx with PetitPotam, DFSCoerce, PrinterBug coercion), remote execution protocols (WMI, WinRM, DCOM, PsExec and alternatives), RDP session hijacking, and network pivoting through tunneling tools (chisel, ligolo-ng, SSH tunnels, SOCKS proxies). Provides operator-ready command sequences for mimikatz, crackmapexec/netexec, impacket suite, and evil-winrm with emphasis on OPSEC considerations, SMB signing bypass, and detection evasion. Maps to MITRE ATT&CK T1021 (Remote Services), T1550 (Use Alternate Authentication Material), and sub-techniques. Includes defender-perspective detection guidance for blue team awareness and a rapid engagement cheatsheet for common lateral movement scenarios encountered during internal penetration tests and assumed-breach exercises.

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。