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Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.

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。

Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.

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 an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.

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.

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。

Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.

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。

Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.

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。

Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based 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。

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns. Use when investigating Kubernetes cluster compromise or building k8s-specific SIEM detection rules.

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。

Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.

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 abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly 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。

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.

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。

Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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。

[BETA] AEM Cloud Service expert skill — handle an explicitly-unbounded query (`p.limit=-1` predicate or JCR `setLimit(-1)`): bound it when capping is provably safe, otherwise flag it for human pagination. Use for "bound my query", "unbounded query", "query causing OOM", or a scan that flags `p.limit=-1`. Top CSO OOM cause: an unbounded result set traversed in a loop fills the heap and saturates the instance. The analyzer locates the explicit markers; the recipe triages each by how the result is consumed — single-result → 1, already-bounded list → N, iterate-all on the request path → escalate. Never silently cap a result the caller reads in full. This skill is in beta. Verify all outputs before applying them to production projects.

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。

[BETA] Implement custom AEM Workflow Java components on AEM as a Cloud Service. This skill is in beta. Verify all outputs before applying them to production projects. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.

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。

Triage AEM Workflow issues on AEM as a Cloud Service by classifying symptoms, gathering the right logs and metrics, and mapping to runbooks or Splunk searches. Use when the user asks for workflow activity/errors on a Cloud Service host, needs to classify a Jira ticket, or wants to know what to collect for workflow debugging.

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。

Debug AEM Workflow issues on AEM as a Cloud Service — stuck workflows, failed steps, missing Inbox tasks, launcher failures, stale instances, thread pool exhaustion, queue backlogs, purge failures, and permissions errors. Use when the user reports workflow problems on Cloud Service, asks why a workflow is stuck or failed, needs step-by-step troubleshooting, or provides thread dumps, configuration status output, or Sling Job console output for analysis.

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。

Publish, deactivate, and delete AEM content programmatically via the Cloud Service Replication API (com.day.cq.replication). Covers single-path and bulk activation, preview-tier targeting with AgentFilter, synchronous/async options, ReplicationStatus checks, permission validation, workflow process steps, and replication event handling. Use when the user needs to publish pages, activate or deactivate content, check replication status, build workflow steps that replicate content, listen to replication events, query batch publication state, or work with Replicator, ReplicationOptions, or ReplicationStatusProvider in AEM Cloud Service.

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。

Analyze and improve the internal link structure of an AEM Edge Delivery Services site. Builds a link graph from the query index and page content, identifies orphan pages, hub pages, and content silos, and generates specific linking recommendations with suggested anchor text and placement. Use when improving site navigation, fixing orphan pages, strengthening topical authority, or auditing link equity distribution.

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。

Orchestrate the migrate-prep cascade — extract --prep → direct --prep → prototype --prep → assets prep — with confirmation gates between phases. Builds the data structure migrate consumes.

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。

Optimize AEM Edge Delivery Services commerce product pages for search engine crawling and indexing. Audits client-side rendered product content for crawlability, validates meta tags, Product schema.org structured data, canonical URLs, and image optimization. Addresses the core challenge that EDS product pages render catalog data via JavaScript, which search crawlers may not fully execute. Use when product pages are not appearing in search results or have poor search visibility.

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。

[BETA] AEM Cloud Service expert skill — upgrade outdated Maven dependencies in pom.xml, both literal <version> and same-pom ${property} shapes. Use for "update my aem-sdk-api", "upgrade mockito", or scanning a project for stale dependency versions. Discovery can find <dependency> blocks but "outdated" needs a target version, which the user supplies. Pattern A/B locators and editing strategy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.

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。

[BETA] AEM Cloud Service expert skill — migrate javax.inject.@Inject fields in Sling Model (@Model) classes to injector-specific annotations (@ValueMapValue / @OSGiService / @SlingObject). Self-discoverable (scan for @Model classes with field-level @Inject); the replacement is chosen deterministically from each field's declared type. Use for "fix @Inject in HeroModel.java", "modernize my Sling Models", or when scanning an AEM project for @Inject misuse. Detailed decision table, companion-annotation handling, import management, and file-level skip policy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.

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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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 a full InDesign data merge from a CSV/TSV and an .indd template (or a PDF that gets converted to .indd automatically). Use this skill whenever the user wants to merge a data file with a layout template — including visiting cards, certificates, badges, catalogs, mailers, labels, invoices, or any per-row personalisation. Triggers on: "data merge", "InDesign merge", "merge my CSV with InDesign", "batch export PDF from template", "variable data InDesign", "personalise each row", or any request combining an .indd / PDF template with a data file. Use this skill even when only two of the three inputs (template, data, images) are mentioned — and even when the user never uses the phrase "data merge".

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。