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Anthropic-Cybersecurity-Skills

by @mukul975v
4.5(576)

754の構造化されたサイバーセキュリティスキルを提供し、AIエージェントを強化します。これらのスキルは26のセキュリティ領域をカバーし、MITRE ATT&CKやNIST CSF 2.0などの5つの主要な業界フレームワークにマッピングされており、AIエージェントがシニアアナリストレベルのセキュリティ知識とガイダンスを獲得できるようにし、セキュリティ調査と対応を加速させます。

cybersecurityai-agentssecurity-frameworksopen-sourceskill-libraryGitHub
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git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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SKILL.md

Anthropic Cybersecurity Skills

The largest open-source cybersecurity skills library for AI agents

GARS-2026 Survey License Skills Frameworks Domains Platforms GitHub stars GitHub forks Last Commit agentskills.io PRs Welcome Playground Hermes Agent

754 production-grade cybersecurity skills · 26 security domains · 5 framework mappings · 26+ AI platforms

Get Started · What's Inside · Frameworks · Platforms · Contributing


⚠️ Community Project — This is an independent, community-created project. Not affiliated with Anthropic PBC.

Give any AI agent the security skills of a senior analyst

A junior analyst knows which Volatility3 plugin to run on a suspicious memory dump, which Sigma rules catch Kerberoasting, and how to scope a cloud breach across three providers. Your AI agent doesn't — unless you give it these skills.

This repo contains 754 structured cybersecurity skills spanning 26 security domains, each following the agentskills.io open standard. Every skill is mapped to five industry frameworks — MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, and NIST AI RMF — making this the only open-source skills library with unified cross-framework coverage. Clone it, point your agent at it, and your next security investigation gets expert-level guidance in seconds.

Five frameworks, one skill library

No other open-source skills library maps every skill to all five frameworks. One skill, five compliance checkboxes.

FrameworkVersionScope in this repoWhat it maps
MITRE ATT&CKv19.115 tactics · 286 techniquesAdversary behaviors and TTPs
NIST CSF 2.02.06 functions · 22 categoriesOrganizational security posture
MITRE ATLASv5.416 tactics · 84 techniquesAI/ML adversarial threats
MITRE D3FENDv1.37 categories · 267 techniquesDefensive countermeasures
NIST AI RMF1.04 functions · 72 subcategoriesAI risk management

Example — a single skill maps across all five:

SkillATT&CKNIST CSFATLASD3FENDAI RMF
analyzing-network-traffic-of-malwareT1071DE.CMAML.T0047D3-NTAMEASURE-2.6

MITRE ATT&CK v19.1 — 754/754 skills mapped

Every skill carries a mitre_attack frontmatter list validated against MITRE ATT&CK v19.1 (the latest release) using the official mitreattack-python library — 286 distinct techniques across all 15 Enterprise tactics, plus ICS and Mobile techniques where relevant. Zero revoked or deprecated IDs. v19.1's restructured Defense Evasion (now split into Stealth and Defense Impairment) is reflected below.

TacticIDSkills
ReconnaissanceTA0043103
Resource DevelopmentTA004222
Initial AccessTA0001467
ExecutionTA0002350
PersistenceTA0003444
Privilege EscalationTA0004464
StealthTA0005442
Defense ImpairmentTA011292
Credential AccessTA0006202
DiscoveryTA0007237
Lateral MovementTA000868
CollectionTA0009172
Command and ControlTA0011123
ExfiltrationTA001082
ImpactTA004050

Quick start

# Option 1: npx (recommended)
npx skills add mukul975/Anthropic-Cybersecurity-Skills

# Option 2: Git clone
git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
cd Anthropic-Cybersecurity-Skills

Works immediately with Claude Code, GitHub Copilot, OpenAI Codex CLI, Cursor, Gemini CLI, and any agentskills.io-compatible platform.

🌍 GARS-2026 — Global Agentic AI Readiness Survey

I'm running a global academic study measuring how ready security professionals, developers, and enterprise teams actually are for agentic AI — MCP servers, tool calling, governance, and human-in-the-loop workflows.

If you use this repo, your response would be a genuinely valuable data point.

📋 Take the survey (10 min): Survey Link

  • 60 questions · Anonymous · Supervised by SRH Berlin
  • You get 50 Casky Tokens for early access to casky.ai
  • Results published open access under CC-BY 4.0

🚀 Try it on the Playground

Experience Casky.ai hands-on — no setup required.

→ Launch Playground on Casky.ai

The playground lets you:

  • Run live cybersecurity skill exercises against real targets
  • See AI agents execute structured skills in real time
  • Explore MITRE ATT&CK mapped workflows interactively
  • Test threat hunting, DFIR, and penetration testing scenarios

No installation. No configuration. Just open and start.

Why this exists

The cybersecurity workforce gap hit 4.8 million unfilled roles globally in 2024 (ISC2). AI agents can help close that gap — but only if they have structured domain knowledge to work from. Today's agents can write code and search the web, but they lack the practitioner playbooks that turn a generic LLM into a capable security analyst.

Existing security tool repos give you wordlists, payloads, or exploit code. None of them give an AI agent the structured decision-making workflow a senior analyst follows: when to use each technique, what prerequisites to check, how to execute step-by-step, and how to verify results. That is the gap this project fills.

Anthropic Cybersecurity Skills is not a collection of scripts or checklists. It is an AI-native knowledge base built from the ground up for the agentskills.io standard — YAML frontmatter for sub-second discovery, structured Markdown for step-by-step execution, and reference files for deep technical context. Every skill encodes real practitioner workflows, not generated summaries.

What's inside — 26 security domains

DomainSkillsKey capabilities
Cloud Security60AWS, Azure, GCP hardening · CSPM · cloud forensics
Threat Hunting55Hypothesis-driven hunts · LOTL detection · behavioral analytics
Threat Intelligence50STIX/TAXII · MISP · feed integration · actor profiling
Web Application Security42OWASP Top 10 · SQLi · XSS · SSRF · deserialization
Network Security40IDS/IPS · firewall rules · VLAN segmentation · traffic analysis
Malware Analysis39Static/dynamic analysis · reverse engineering · sandboxing
Digital Forensics37Disk imaging · memory forensics · timeline reconstruction
Security Operations36SIEM correlation · log analysis · alert triage
Identity & Access Management35IAM policies · PAM · zero trust identity · Okta · SailPoint
SOC Operations33Playbooks · escalation workflows · metrics · tabletop exercises
Container Security30K8s RBAC · image scanning · Falco · container forensics
OT/ICS Security28Modbus · DNP3 · IEC 62443 · historian defense · SCADA
API Security28GraphQL · REST · OWASP API Top 10 · WAF bypass
Vulnerability Management25Nessus · scanning workflows · patch prioritization · CVSS
Incident Response25Breach containment · ransomware response · IR playbooks
Red Teaming24Full-scope engagements · AD attacks · phishing simulation
Penetration Testing23Network · web · cloud · mobile · wireless pentesting
Endpoint Security17EDR · LOTL detection · fileless malware · persistence hunting
DevSecOps17CI/CD security · code signing · Terraform auditing
Phishing Defense16Email authentication · BEC detection · phishing IR
Cryptography14TLS · Ed25519 · certificate transparency · key management
Zero Trust Architecture13BeyondCorp · CISA maturity model · microsegmentation
Mobile Security12Android/iOS analysis · mobile pentesting · MDM forensics
Ransomware Defense7Precursor detection · response · recovery · encryption analysis
Compliance & Governance5CIS benchmarks · SOC 2 · regulatory frameworks
Deception Technology2Honeytokens · breach detection canaries

How AI agents use these skills

Each skill costs ~30 tokens to scan (frontmatter only) and 500–2,000 tokens to fully load (complete workflow). This progressive disclosure architecture lets agents search all 754 skills in a single pass without blowing context windows.

User prompt: "Analyze this memory dump for signs of credential theft"

Agent's internal process:

  1. Scans 754 skill frontmatters (~30 tokens each)
     → identifies 12 relevant skills by matching tags, description, domain

  2. Loads top 3 matches:
     • performing-memory-forensics-with-volatility3
     • hunting-for-credential-dumping-lsass
     • analyzing-windows-event-logs-for-credential-access

  3. Executes the structured Workflow section step-by-step
     → runs Volatility3 plugins, checks LSASS access patterns,
        correlates with event log evidence

  4. Validates results using the Verification section
     → confirms IOCs, maps findings to ATT&CK T1003 (Credential Dumping)

Without these skills, the agent guesses at tool commands and misses critical steps. With them, it follows the same playbook a senior DFIR analyst would use.

Skill anatomy

Every skill follows a consistent directory structure:

skills/performing-memory-forensics-with-volatility3/
├── SKILL.md              ← Skill definition (YAML frontmatter + Markdown body)
├── references/
│   ├── standards.md      ← MITRE ATT&CK, ATLAS, D3FEND, NIST mappings
│   └── workflows.md      ← Deep technical procedure reference
├── scripts/
│   └── process.py        ← Working helper scripts
└── assets/
    └── template.md       ← Filled-in checklists and report templates

YAML frontmatter (real example)

---
name: performing-memory-forensics-with-volatility3
description: >-
  Analyze memory dumps to extract running processes, network connections,
  injected code, and malware artifacts using the Volatility3 framework.
domain: cybersecurity
subdomain: digital-forensics
tags: [forensics, memory-analysis, volatility3, incident-response, dfir]
atlas_techniques: [AML.T0047]
d3fend_techniques: [D3-MA, D3-PSMD]
nist_ai_rmf: [MEASURE-2.6]
nist_csf: [DE.CM-01, RS.AN-03]
version: "1.2"
author: mukul975
license: Apache-2.0
---

Markdown body sections

## When to Use
Trigger conditions — when should an AI agent activate this skill?

## Prerequisites
Required tools, access levels, and environment setup.

## Workflow
Step-by-step execution guide with specific commands and decision points.

## Verification
How to confirm the skill was executed successfully.

Frontmatter fields: name (kebab-case, 1–64 chars), description (keyword-rich for agent discovery), domain, subdomain, tags, atlas_techniques (MITRE ATLAS IDs), d3fend_techniques (MITRE D3FEND IDs), nist_ai_rmf (NIST AI RMF references), nist_csf (NIST CSF 2.0 categories). MITRE ATT&CK technique mappings are documented in each skill's references/standards.md file and in the ATT&CK Navigator layer included with releases.

 

TacticIDCoverageKey skills
ReconnaissanceTA0043StrongOSINT, subdomain enumeration, DNS recon
Resource DevelopmentTA0042ModeratePhishing infrastructure, C2 setup detection
Initial AccessTA0001StrongPhishing simulation, exploit detection, forced browsing
ExecutionTA0002StrongPowerShell analysis, fileless malware, script block logging
PersistenceTA0003StrongScheduled tasks, registry, service accounts, LOTL
Privilege EscalationTA0004StrongKerberoasting, AD attacks, cloud privilege escalation
Defense EvasionTA0005StrongObfuscation, rootkit analysis, evasion detection
Credential AccessTA0006StrongMimikatz detection, pass-the-hash, credential dumping
DiscoveryTA0007ModerateBloodHound, AD enumeration, network scanning
Lateral MovementTA0008StrongSMB exploits, lateral movement detection with Splunk
CollectionTA0009ModerateEmail forensics, data staging detection
Command and ControlTA0011StrongC2 beaconing, DNS tunneling, Cobalt Strike analysis
ExfiltrationTA0010StrongDNS exfiltration, DLP controls, data loss detection
ImpactTA0040StrongRansomware defense, encryption analysis, recovery

An ATT&CK Navigator layer file is included in the [v1.0.0 release assets](https://github.com/mukul975/Anthropic-Cybersecurity-Sk

...

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インストール数14.4K
評価4.5 / 5.0
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更新日2026年6月10日
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作成2026年6月6日
最終更新2026年6月10日
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