メニュー
754 cybersecurity skills cho AI agent — 26 domains, map sang 5 frameworks (MITRE ATT&CK v19.1, NIST CSF 2.0, ATLAS v5.4, D3FEND v1.3, AI RMF 1.0). Real practitioner workflows.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
SOC 職業分類に基づく
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/yanacuti1121/Yana-AI --skill analyzing-network-traffic-of-malwareコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
Sovereign-grade safety OS for AI coding agents. 62 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.
Use when the user wants to generate or keep repository documentation up to date via OpenWiki (langchain-ai/openwiki) — an LLM-driven CLI that writes a wiki for a codebase (or a personal knowledge base from Notion/Gmail/Slack/X/web search) and keeps it fresh via a scheduled CI pull request. Examples: "set up OpenWiki for this repo", "keep the docs updated automatically", "generate an agent wiki".
Use when implementing the core AR pipeline (camera pose estimation, marker tracking, projection overlay) from first principles — not when just using ARKit/ARCore/Unity's AR framework as a black box. Triggers on: 'build augmented reality from scratch', 'marker-based AR tracking', 'camera pose estimation', 'implement fiducial marker detection', 'AR projection matrix math', 'markerless AR tracking'. Covers marker-based vs markerless tracking, pose estimation, and the projection math to overlay 3D content on a camera feed.
| name | mukul975--cybersecurity-skills |
| description | 754 cybersecurity skills cho AI agent — 26 domains, map sang 5 frameworks (MITRE ATT&CK v19.1, NIST CSF 2.0, ATLAS v5.4, D3FEND v1.3, AI RMF 1.0). Real practitioner workflows. |
| allowed-tools | Read, Bash |
| user-invocable | true |
754 structured cybersecurity skills: không phải script collection — là domain knowledge có cấu trúc để AI agent ra quyết định WHEN và HOW dùng technique.
npx skills add mukul975/Anthropic-Cybersecurity-Skills
# hoặc
git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills
Detection & Response:
threat-hunting (55) security-operations (36) incident-response (25)
Infrastructure:
cloud-security (60) network-security (40) container-security (30)
OT/ICS security (28)
Attack & Defense:
web-app-security (42) malware-analysis (39) red-teaming (24)
penetration-testing (23) digital-forensics (37)
Identity & API:
IAM (35) api-security (28) ransomware-defense (7)
MITRE ATT&CK v19.1 — 286 techniques, 15 tactics (adversary TTPs)
NIST CSF 2.0 — 6 functions, 22 categories (org posture)
MITRE ATLAS v5.4 — 16 tactics, 84 techniques (AI/ML threats) ← unique
MITRE D3FEND v1.3 — 267 defensive techniques
NIST AI RMF 1.0 — 72 subcategories (AI risk management)
# Frontmatter (~30 tokens) — rapid scan
name: analyzing-network-traffic-of-malware
domain: malware-analysis
tags: [network, pcap, wireshark]
mitre_attack: T1071
nist_csf: DE.CM
atlas: AML.T0047
d3fend: D3-NTA
ai_rmf: MEASURE-2.6
# Body (500–2000 tokens) — full execution
## When to Use
## Prerequisites
## Workflow (step-by-step với commands)
## Verification
1. Scan 754 frontmatters → identify relevant (bằng tags + domain)
2. Load top 3–5 matches full body
3. Execute Workflow section step-by-step
4. Validate với Verification section
Load skills:
performing-memory-forensics-with-volatility3
hunting-for-credential-dumping-lsass
analyzing-windows-event-logs-for-credential-access
→ Execute sequentially = DFIR analyst workflow
Claude Code, Cursor, Copilot, LangChain, CrewAI, AutoGen, MCP systems, Gemini CLI
https://github.com/mukul975/Anthropic-Cybersecurity-Skills · MIT · +2192⭐/week