「eal」の検索結果

Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them. Activates for requests involving ransomware canary deployment, honeyfile setup, deception-based ransomware detection, or file integrity monitoring for encryption.

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。

Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification 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。

Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.

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。

Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.

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。

Deploys and configures CrowdStrike Falcon EDR agents across enterprise endpoints to enable real-time threat detection, behavioral analysis, and automated response. Use when onboarding endpoints to EDR coverage, configuring detection policies, or integrating Falcon telemetry with SIEM platforms. Activates for requests involving CrowdStrike deployment, Falcon sensor installation, EDR policy configuration, or endpoint detection and response.

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。

Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.

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。

Deobfuscates malicious JavaScript code used in web-based attacks, phishing pages, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control flow obfuscation to reveal the original malicious logic. Activates for requests involving JavaScript malware analysis, script deobfuscation, web skimmer analysis, or obfuscated dropper investigation.

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。

Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for real-time network traffic inspection, threat detection, and integration with SIEM platforms for centralized security 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。

Builds automated threat intelligence feed integration pipelines connecting STIX/TAXII feeds, open-source threat intel, and commercial TI platforms into SIEM and security tools for real-time IOC matching and alerting. Use when SOC teams need to operationalize threat intelligence by automating feed ingestion, normalization, scoring, and distribution to detection 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。

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.

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。

Crawl and validate all internal and external links across an AEM Edge Delivery Services site. Uses the query index or sitemap to discover pages, extracts links from .plain.html renditions, checks HTTP status codes, and produces a prioritized report of broken, redirecting, and insecure links. Use when auditing link health before launch, after a migration, or as a periodic maintenance check.

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。

Validate an AEM Edge Delivery Services sitemap.xml against actual site content. Cross-references the sitemap with the query index, checks URL reachability, validates lastmod dates, and identifies missing or orphaned pages. Use when auditing SEO health, preparing for launch, or investigating indexing 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。

Analyzes a multi-step conversion funnel to find where users drop off and which steps have the worst leakage. Use this skill when someone describes a journey or funnel and asks about conversion rates, drop-off, fallout, or step completion. Trigger for phrases like "analyze our onboarding funnel," "where are users dropping off," "what's our checkout conversion rate," "funnel analysis," "show me fallout between these steps," or "which step loses the most users."

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。

Comprehensive dimension analysis and reporting for CJA. Use this skill whenever the user wants to analyze one or more dimensions — including cardinality, distribution/skew, trends, anomalies, data quality errors, comparisons, and forecasting. Also trigger when someone asks "what are the top values for...", "dimension health", "explore this dimension", "dimension dashboard", "dimension statistics", "data quality check on a dimension", "dimension cardinality", "dimension trends", "dimension skew", "dimension anomalies", "compare dimensions", or any similar request to understand what's inside a CJA dimension. Produces an interactive HTML dashboard or a markdown report. Works with the CJA MCP server.

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 asked to run, read, or interpret react-doctor output on the Namias portfolio. Covers the npm scripts, the doctor.config.json schema, the score model, the 12-rule catalog, and which findings are real vs false-positive by design.

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。

Creates factories and builders for generating consistent, composable test data with realistic values and relationship handling. Use for "test factories", "test data builders", "fixture factories", or "test data generation".

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。

Deep competitive intelligence for any market. Analyzes competitors' products, pricing, customer sentiment, GTM strategy, and growth signals using real web data. Produces battle cards, pricing landscape, and feature matrix. Use when the user wants to understand their competitive landscape, analyze competitors, compare products in a market, or research who they're competing against. Triggers for "who are my competitors", "competitive analysis", "competitor research", "battle cards", "pricing comparison", "competitor pricing", "market players", "competitive intelligence", "competitive landscape", "who else is in this space", "competitive moat", or any request to profile, compare, or map competitors in a category. Works standalone — no prior startup-design session 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。

Creates comprehensive load test plans with realistic scenarios, traffic models, k6 scripts, and success criteria. Use for "load testing", "performance testing", "capacity validation", or "stress 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。

Make a web app feel native on a phone — the small CSS and meta-tag fixes that separate "a website in a browser" from something that feels installed. Covers sticky hover states, tap highlight flashes, the 100vh bug, inputs that zoom the page, laggy taps, pull-to-refresh hijacking scroll, content under the notch, long-press selecting button text, carousels that scroll the wrong way, mismatched status bars, and the rule that you test on real hardware. Use when a web app is being built for or reviewed on mobile, when something "works in Chrome but feels wrong on my phone", when building a PWA, a bottom sheet, a carousel, a full-screen layout, or any touch interaction. For motion itself use animate; for React Native use animate-expo.

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。

Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.

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。

Generates deterministic seed data for development and testing with factory functions, realistic fixtures, and database reset scripts. Use for "data seeding", "test fixtures", "database seeding", or "mock data generation".

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 a running Spark or DSH web service needs real-browser verification — page load, client-plugin boot errors, console errors, failed requests, or onboarding/dialog rendering — with the repository's own Playwright chromium.

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 a reference list needs APA 7 cleanup, when DOIs must be confirmed real against Crossref or PubMed, when the user asks whether AI-suggested citations actually exist, or when a manuscript needs a citation hygiene pass before submission or 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。