「wind」の検索結果

Create safe, deterministic git worktrees for large or risky workstreams using the repository-owned runtime helper and Windows-safe defaults.

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 WMI event subscription persistence by analyzing Sysmon Event IDs 19, 20, and 21 for malicious EventFilter, EventConsumer, and FilterToConsumerBinding creation.

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。

Identifies and exploits SMB protocol vulnerabilities using Metasploit Framework during authorized penetration tests to demonstrate risks from unpatched Windows systems, misconfigured shares, and weak authentication in enterprise networks.

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 abuse of elevation control mechanisms including UAC bypass, sudo exploitation, and setuid/setgid manipulation by monitoring registry modifications, process elevation flags, and unusual parent-child process relationships.

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 OS credential dumping techniques targeting LSASS memory, SAM database, NTDS.dit, and cached credentials using EDR telemetry, Sysmon process access monitoring, and Windows security event 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。

Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log 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。

Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.

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 privilege escalation attempts including token manipulation, UAC bypass, unquoted service paths, kernel exploits, and sudo/doas abuse across Windows and 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 abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution patterns.

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 deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use when implementing AD deception defenses for detecting lateral movement, credential theft, and reconnaissance.

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。

Establish a structured operational process to triage, test, and deploy Microsoft Patch Tuesday security updates within risk-based remediation SLAs.

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 USB device connection history from Windows registry, event logs, and setupapi logs to track removable media usage and potential data exfiltration.

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 PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

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。

Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident 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。

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。

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware 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。

Fetch up-to-date, version-specific documentation for any major library (Next.js 16, Sanity, LangGraph, React, Tailwind CSS, Vitest, Framer Motion) via the Context7 MCP server. Use when writing code against unfamiliar or recently-changed framework APIs, when training data may be stale, when resolving deprecations or version-specific syntax, or when the repo warns about framework drift (e.g. the nextjs-agent-rules block in portfolio-v1/AGENTS.md). Invokes the resolve-library-id and get-library-docs MCP tools.

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 beautiful, responsive, accessible UIs using React, Tailwind CSS, Framer Motion, and the Vercel Web Interface Guidelines.

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。

Implements rate limiting and abuse prevention with per-route policies, IP/user-based limits, sliding windows, safe error responses, and observability. Use when adding "rate limiting", "API protection", "abuse prevention", or "DDoS protection".

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。

Implements responsive design systems with mobile-first breakpoints, container queries, fluid typography, and adaptive layouts using Tailwind CSS. Use when users request "responsive design", "mobile-first", "breakpoints", "fluid typography", or "adaptive layout".

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。

Converts Figma/design specifications into production-ready UI components with accurate spacing, typography, color tokens, responsive rules, and interaction states (hover, focus, disabled, active). Generates Tailwind/shadcn code with design system tokens mapping. Use when translating "Figma to code", "design specs to components", or "implement design system".

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。

Implements complete dark/light mode theming systems using CSS variables, Tailwind dark mode, React context, and system preference detection. Use when users request "add dark mode", "theme toggle", "dark theme", "light mode switch", or "color scheme".

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。

Guide to Sonner, the React toast library — install and wire up the Toaster, pick the right toast() call, promise and loading toasts, updating, dismissing and persisting toasts, styling, theming and icons, positioning and multiple toasters. Use when working with Sonner or troubleshooting it — toasts that don't appear, appear twice, lose their styles, ignore Tailwind classes, sit behind a modal, or don't follow dark mode.

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 adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.

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。