927 件 ・ 関連度順
概要と使いどころ
Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build 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。
Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authenticat...
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。
Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
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 fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.
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 process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR telemetry.
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 defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.
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 cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.
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。
Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si
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。
Wire Promptfoo and DeepTeam into CI/CD for automated regression red-teaming of LLM apps against OWASP LLM Top 10 and OWASP Agentic presets, failing the build when jailbreak or injection vulnerabilities regress.
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。
Deploy Llama Guard, NeMo Guardrails, and LLM Guard input/output scanners as runtime defenses.
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。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat 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。
Use when a concept is too abstract for the learner's current level and needs analogy-first teaching before complexity re-injection.
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。
Reviews one SKILL.md against the format rules and returns a findings table: strict YAML front matter with exactly name and description, name equal to the folder, description as the trigger, the eight-heading skeleton, capability-neutral wording, safety boundaries. Each finding carries severity, rule identifier, location, quoted evidence and replacement text; the verdict READY, REVISE or BLOCKED is an apparent state and the owner decides. Use when the user asks to "review this SKILL.md", "check my skill file before upload", "lint this skill description", "validate the front matter of this skill" or "score this skill folder". Do not use to write an agent's instructions field, use agent-instructions-drafter instead; for injection or leakage exposures use agent-instructions-red-team; for launch tests use agent-evaluation-plan. Drafts for human review; never approves, authorises or signs off.
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。
Designs a pre-launch evaluation plan for a declarative agent from its instructions text, skills, capabilities, knowledge sources and sample requests: a behaviour contract of testable statements quoted from the text, test prompts by scenario family and tier with setup, expected behaviour, pass and fail criteria and red flags, a red-flag catalogue, a blank scoring sheet, a coverage table and a go or no-go checklist the owner completes and decides. Use when the user asks to "write test cases for my agent", "how do I evaluate this agent before launch", "build a test plan for the agent", "what should I check before publishing this agent" or "give me a go no-go checklist". Do not use for finding injection or leakage exposures in the instructions, use agent-instructions-red-team instead; do not use for reviewing one SKILL.md, use skill-file-reviewer instead. Drafts for human review; never approves, authorises or signs off.
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。
当用户说"内容质量好但没人分享""产品很棒但传播不动"时激活此 skill。 典型触发信号：用户已有高质量内容但分享率低于预期，或在问"怎么让内容更容易被转发"。 不适用于：纯粹的情绪设计理论探讨（应使用 emotion-arousal-model）、与传播无关的内容创作。 核心判断：用户是否在寻求"如何让已有内容获得更多分享"的实操方法。
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。
Operational guide for the ArtCraft MCP integration — the community Python rebuild (C:\Users\rasta\artcraft-mcp-py\artcraft_mcp_server.py) that replaces the broken upstream artcraft-mcp.exe, the live api.storyteller.ai/v1 API map (required headers, cookie auth, endpoint schemas), the upstream bug/PR trail (issues #1/#3, PR #2), the reverse-engineering playbook (browser capture, cookie injection, schema fishing via validation errors, handshake replay, Windows MITM kit), and the generic MCP-protocol debugging playbook (snake_case servers, the shim pattern, 'missing field protocolVersion' diagnosis). Use when working on ArtCraft MCP tools, debugging an artcraft server connection, extending the Python rebuild, or diagnosing any third-party MCP handshake failure.
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。
Autonomous AI security pen testing. Executes real exploits against web applications to find SQL injection, XSS, SSRF, authentication flaws, and IDOR vulnerabilities. Reports only confirmed, reproducible findings — no false positives.
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。
Master AngularJS to Angular migration, including hybrid apps, component conversion, dependency injection changes, and routing migration.
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。
Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.
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。
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.
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 an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
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。
差分に追加されたソースコードへ混入した不可視・危険な Unicode 文字（タグ文字・異体字セレクター・ゼロ幅文字・双方向制御/マーク・変則空白）を検出する。GlassWorm 型サプライチェーン攻撃・ASCII smuggling・Trojan Source（CVE-2021-42574）でコードを不可視化する手口を、決定論的な静的解析（列挙した code point 集合に限定）として捕捉し、canary テストで誤検出の再発を防ぐ
Reviews GitHub Actions workflow diffs for script injection of untrusted input, pull_request_target with untrusted checkout, over-broad GITHUB_TOKEN permissions, and unpinned third-party actions.
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。