Authors .editorconfig rules. IDE/CA severity, AnalysisLevel, globalconfig, code style enforcement.
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。
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概要と使いどころ
Authors .editorconfig rules. IDE/CA severity, AnalysisLevel, globalconfig, code style enforcement.
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。
Interprets MSBuild output, NuGet errors, analyzer warnings. Error codes, CI drift.
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。
Discover and inventory shadow API endpoints that operate outside documented specifications using traffic analysis, code scanning, and API discovery 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。
Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.
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 covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.
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 malicious scheduled task creation and modification using Sysmon Event IDs 1 (Process Create for schtasks.exe), 11 (File Create for task XML), and Windows Security Event 4698/4702. The analyst correlates task creation with suspicious parent processes, public directory paths, and encoded command arguments to identify persistence and lateral movement via scheduled tasks. Activates for requests involving scheduled task detection, Sysmon persistence hunting, or T1053.005 Scheduled Task/Job 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。
Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.
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。
Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing 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。
Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux 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。
Scores and prioritizes technical debt by impact, risk, and effort. Provides ranked backlog with ROI analysis and quarterly paydown recommendations. Use for "tech debt", "technical debt management", "code quality", or "refactoring priorities".
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 building slides, a poster, or a lightning talk from a manuscript, when a presentation must exist in Turkish and English, or when conference visuals need a traceability check so every number on a slide matches the analysis behind it.
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 selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.
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 before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.
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 high-stakes analysis, citation set, or decision should be checked by a second independent AI agent that verifies rather than decides, or when disagreement between agents must be surfaced for the human to adjudicate.
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。
LoRaWAN and sub-GHz (433 / 868 / 915 MHz) attack methodology — LoRaWAN ABP/OTAA join attack, network/session key reuse, frame counter replay, downlink injection on TTN/Helium-style networks, sub-GHz protocol replay (KeeLoq garage doors, fixed-code remotes, TPMS spoofing, smart plug telemetry), HackRF / RTL-SDR / Flipper Zero workflows, signal analysis with Inspectrum / Universal Radio Hacker, and reconstruction of proprietary packet formats. Use for LoRaWAN deployments (smart cities, asset tracking, industrial telemetry), or any wireless device using the unlicensed 433/868/915 MHz bands (garage openers, doorbells, IoT sensors, RC equipment).
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。
Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Duc...
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。
Advanced API exploitation methodology focused on business logic abuse and sophisticated attack patterns that bypass traditional security controls. Covers business logic bypass through API call chaining and workflow manipulation. Addresses GraphQL-specific attacks including batching for credential brute-force, query depth exploitation, and introspection abuse. Includes pagination exploitation for data exfiltration, webhook hijacking for SSRF and data interception, and resource exhaustion through algorithmic complexity attacks. Covers race conditions in API transactions using parallel request techniques. Provides comprehensive JWT manipulation including algorithm confusion, kid injection, jku/x5u abuse, and claim tampering. Details API key leakage detection across source repositories, client-side code, and error messages. Covers undocumented endpoint discovery through predictable naming, debug routes, and source map analysis. Tooling includes Arjun, ParamSpider, jwt_tool, and GraphQL Voyager. Designed for a...
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。
Debugs recorded DAG lineage through historical inspection, deterministic decision replay when prerequisites hold, and clearly labeled counterfactual or live re-execution. Activate on "debug DAG", "replay execution", "inspect node state", "compare runs", or "execution diff". NOT for live monitoring (use dag-runtime + websocket-streaming), failure analysis (use dag-ops), or general code 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。
Create a GitHub PR with an engineered description that matches the team's established format — numbered problem-fix sections, technical tables, file-by-file breakdowns, commit lists, and verification checklists. Use this skill whenever the user asks to create a PR, ship code, prepare a merge request, write a PR description, or says anything like "ship to boss", "pr perfect", "make a PR", "prepare PR for merge", "create pull request", "engineer the PR", "PR description", or "ready to push". Also trigger when the user has finished a batch of work and says things like "let's wrap this up", "time to merge", "push this to main", or "get this ready for review". The skill handles everything: commit analysis, description generation, branch creation, and PR submission via gh CLI.
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。