2,529 件 ・ 関連度順
概要と使いどころ
Execute an IPv6 DNS Spoofing attack using `mitm6` on an IPv4-only corporate network. Exploit default Windows behavior (preferring IPv6 DHCP/DNS) to intercept NTLMv2 hashes, force WPAD rogue proxy settings, and relay credentials to Active Directory services.
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。
Execute and analyze malware samples within a highly controlled, instrumented sandbox environment to observe their true behavior, network communications, file system modifications, and registry changes in real-time.
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。
CSRF testing playbook. Use when reviewing state-changing web flows, anti-CSRF defenses, SameSite behavior, JSON CSRF, login CSRF, and OAuth state handling.
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。
Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.
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 NeMo Guardrails Colang (.co) files and YAML config blocks from a plain-language description of a chatbot's purpose, allowed behaviors, and constraints. Use this skill whenever a user wants to build guardrails for a chatbot, define allowed intents for an LLM, create an AI firewall with NeMo Guardrails, generate Colang flow definitions, or configure a semantic allow-list for a bot. Trigger this skill even when the user just describes what their bot should and shouldn't do — generating the Colang and YAML is almost always what they need next.
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。
Execute a DCSync attack mimicking the behavior of a legitimate Active Directory Domain Controller (DC). Leverage Directory Replication Service Remote Protocol (DRSR) permissions to silently request and extract the password hashes (NTLM/Kerberos) of any or all users in the domain without executing code on the target Domain Controller.
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。
Add or update Flutter widget tests in this repository using the existing test layout, Riverpod provider overrides, generated localization, shared theme setup, and FVM test commands. Use when a task asks for widget tests, UI regression coverage, test coverage for a screen/component, or when implementation work changes visible Flutter 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。
Diagnose and fix Flutter layout, overflow, unbounded constraint, scroll, and responsive rendering issues in this repository while preserving the template's existing feature, theme, localization, and shared widget patterns. Use when UI overflows, text clips, widgets disappear, layouts fail on mobile/tablet/desktop, or a feature needs responsive 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。
Design or revise Interpreter UI for non-developers with an ultra-minimal, utilitarian style inspired by the OpenAI website and ChatGPT, not the developer platform. Use when simplifying settings, onboarding, chat, forms, empty states, or helper copy; when removing extra containers, labels, or visual noise; when replacing technical wording with plain language; when clarifying hierarchy and making the main user action obvious; when making every visible label and status understandable to an average HR admin or other non-technical user; when hiding implementation details such as logs, IDs, endpoints, paths, or protocol names; or when a screen must respect the app's existing CSS variables and light/dark theme 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。
Supreme policy layer governing all agent behavior. Autonomy, one-line prompt interpretation, speed standards, emphasis signal processing, cross-skill coordination, done definitions, conflict resolution. Loaded every prompt.
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。
ERPNext-aware reasoning for accounting, selling, buying, stock, manufacturing, projects, HR, support, education, CRM, and other ERPNext module work. Use when a task affects ERPNext module behavior, configuration, reports, dashboards, workflows, or customizations.
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。
Frappe backend guidance for Python and backend-adjacent JavaScript surfaces such as client interaction patterns, hooks, APIs, patches, scheduler logic, reports, and server-side review. Use when implementing or reviewing Frappe backend 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。
PostHog event tracking, user identification, group analytics for B2B, GDPR consent patterns. Use when implementing product analytics, tracking user behavior, setting up funnels, or configuring privacy-compliant tracking.
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。
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
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。
This skill provides systematic bug detection and discovery capabilities for VS Code extensions. Use when searching for hidden bugs, analyzing code for potential issues, investigating suspicious behavior, performing code audits, or proactively finding bugs before they manifest. Covers static analysis patterns, dynamic analysis techniques, code smell detection, and systematic codebase 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。
Analyzes position-independent shellcode: disassembling raw bytes at the right architecture, recognizing PEB-walk API resolution and egg hunters, and emulating execution to recover behavior and payloads. Activates for requests to analyze shellcode, disassemble raw position-independent code, or emulate a shellcode blob.
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 capa to identify malware capabilities from a binary: running rule-based detection over disassembly, mapping matched capabilities to MITRE ATT&CK and MBC, and interpreting results to focus deeper analysis. Activates for requests to run capa, generate a capability report, or map a sample's behaviors to ATT&CK automatically.
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。
Establishes behavioral baselines from historical telemetry (process, network, or logon events) so hunts can flag rare and first-seen activity instead of relying on static signatures. Activates for requests to build a telemetry baseline, find rare or first-seen activity, or compute frequency baselines for anomaly hunting.
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 VBScript, WSF, and HTA scripts: parsing WSF/HTA containers, decoding VBScript.Encode (#@~^) and string obfuscation, and identifying WScript.Shell/ActiveX abuse to recover dropper behavior. Activates for requests to analyze VBScript, decode a WSF/HTA, or investigate a Windows Script Host dropper.
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。
Captures and analyzes malware network traffic from a detonation: extracting C2 endpoints, HTTP/DNS patterns, TLS metadata (JA3/SNI), and beaconing from a PCAP to build network IOCs and detection. Activates for requests to analyze malware PCAP, extract C2 from traffic, or study network 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。
Analyzes a PE file's import and export tables to infer capability: mapping imported APIs to behaviors (networking, crypto, injection, persistence), spotting dynamic-resolution stubs, and reading exports of malicious DLLs. Activates for requests to analyze PE imports, inspect the IAT/exports, or infer capability from API usage.
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。
Frames a structured, testable threat-hunting hypothesis: grounding it in adversary behavior and available telemetry, defining the data sources and detection logic, and setting success criteria and outcomes. Activates for requests to start a threat hunt, write a hunt hypothesis, or plan a hypothesis-driven hunt.
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 sandbox and analysis evasion techniques in a sample by scanning static strings, imports, and API traces for VM artifact checks, timing/sleep stalls, anti-debug calls, and environment fingerprinting. Activates for requests to detect sandbox evasion, find anti-VM or anti-debug checks, or explain why a sample did not detonate.
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。