上記に当てはまらないスキル（1.5万 件）
Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
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Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.
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 and catalog attack patterns from cyber threat intelligence reports into a structured STIX-based library mapped to MITRE ATT&CK for detection engineering and threat-informed defense.
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Detect typosquatting, homograph phishing, and brand impersonation domains using dnstwist to generate domain permutations and identify registered lookalike domains targeting your organization.
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Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.
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 and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise.
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。
Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.
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Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports
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Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.
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Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
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。
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
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Analyzes bootkit and advanced rootkit malware that infects the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware to gain persistence below the operating system. Covers boot sector analysis, UEFI module inspection, and anti-rootkit detection techniques. Activates for requests involving bootkit analysis, MBR malware investigation, UEFI persistence analysis, or pre-OS malware detection.
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。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
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Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
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。
Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr
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。
Mark an ADR as Implemented (or Superseded) and archive it, following INDEX.md conventions.
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Create or update product-update / release-notes content for a given OpenMetadata/Collate patch version across getcollate, openmetadata-site, and docs-om. Sources getcollate's changelog from openmetadata-collate + OpenMetadata + ai-platform; openmetadata-site's from OpenMetadata only; docs-om reuses openmetadata-site's already-written content, reformatted into its Mintlify snippet structure. Filters to customer-facing changes only, runs each target's own doc-review checklist, verifies every link live, and requires explicit approval before any commit.
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Full review of a PR, a file, or pasted text against the OpenMetadata Writing Style Guide checklist, plus checking every checkable claim for internal consistency against the diff/PR itself. One combined report, not separate passes. Does not fetch or verify against any external source repository. Link-checking is out of scope; a separate broken-links job covers that. Only runs on explicit /content-review invocation, never self-triggered.
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。
Diagnose and fix common AEM 6.5 LTS replication issues including blocked queues, connectivity failures, and content distribution problems
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Import a single webpage from any URL into canonical EDS block format — structured HTML that authors edit in DA. Scrapes the page, analyzes structure, maps to existing blocks, and generates HTML for immediate local preview. Also triggered by terms like "migrate", "migration", or "migrating". Use this when the goal is canonical EDS authoring; use the snowflake skill instead when the user wants to preserve the original DOM byte-for-byte (static-to-EDS overlay).
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 section boundaries and content sequences within a scraped webpage for AEM Edge Delivery Services import. Performs two-level analysis (sections, then sequences per section) and surveys available blocks.
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Analyze content sequences within a section and provide neutral descriptions for AEM Edge Delivery Services. Invoked per section during page import to identify breaking points between default content and blocks.
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。
Preview and verify imported content in local AEM Edge Delivery Services dev server. Validates rendering, compares with original page, and troubleshoots common issues.
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。
Rewrite AEM Edge Delivery Services page content for AI search discoverability (GEO — Generative Engine Optimization). Analyzes content structure, semantic clarity, and factual density, then produces optimized rewrites that rank in both traditional search and AI-powered search engines. Use when optimizing pages for search visibility, AI discoverability, or content clarity.
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。