Anthropic Cybersecurity Skills

Anthropic Cybersecurity Skills

The largest open-source cybersecurity skills library for AI agents

[](https://mahipal.engineer/survey?utmsource=githubbadge&utmmedium=readme&utmcampaign=gars2026) [](LICENSE) [](#whats-inside--29-security-domains) [](#six-frameworks-one-skill-library) [](https://ctid.mitre.org/fraud/) [](#whats-inside--29-security-domains) [](#compatible-platforms) [](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/stargazers) [](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/network/members) [](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/commits/main) [](https://agentskills.io) [](CONTRIBUTING.md) [](https://casky.ai/?utmsource=github&utmmedium=readme&utmcampaign=cohortlaunch#waitlist) [](https://github.com/NousResearch/hermes-agent)

817 production-grade cybersecurity skills · 29 security domains · 6 framework mappings · 26+ AI platforms

[Get Started](#quick-start) · [What's Inside](#whats-inside--29-security-domains) · [Frameworks](#five-frameworks-one-skill-library) · [Platforms](#compatible-platforms) · [Contributing](#contributing)

---

> ⚠️ Community Project — This is an independent, community-created project. Not affiliated with Anthropic PBC. > > 🔐 Authorized & lawful use only. This library includes offensive and dual-use techniques (e.g. red-team C2, phishing simulation, exploitation) intended for authorized penetration testing, security research, defense, and education. Only use them against systems you own or have explicit written permission to test, and comply with all applicable laws and rules of engagement. You are solely responsible for how you use these skills. See [SECURITY.md](SECURITY.md) and [CODEOFCONDUCT.md](CODEOFCONDUCT.md).

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 817 structured cybersecurity skills spanning 29 security domains, each following the agentskills.io open standard. Every skill is mapped to six industry frameworks — MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, NIST AI RMF, and the MITRE Fight Fraud Framework (F3) — 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.

Six frameworks, one skill library

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

| Framework | Version | Scope in this repo | What it maps | |---|---|---|---| | MITRE ATT&CK | v19.1 | 15 tactics · 286 techniques | Adversary behaviors and TTPs | | NIST CSF 2.0 | 2.0 | 6 functions · 22 categories | Organizational security posture | | MITRE ATLAS | v5.4 | 16 tactics · 84 techniques | AI/ML adversarial threats | | MITRE D3FEND | v1.3 | 7 categories · 267 techniques | Defensive countermeasures | | NIST AI RMF | 1.0 | 4 functions · 72 subcategories | AI risk management | | MITRE F3 (Fight Fraud Framework) | v1.1 (2026-04-09) | 8 tactics · 123 techniques · 94 fraud-relevant skills | Cyber-enabled financial fraud TTPs |

Example — a single skill maps across all six:

| Skill | ATT&CK | NIST CSF | ATLAS | D3FEND | AI RMF | F3 | |---|---|---|---|---|---|---| | analyzing-network-traffic-of-malware | T1071 | DE.CM | AML.T0047 | D3-NTA | MEASURE-2.6 | — | | detecting-business-email-compromise | T1566 | DE.AE | — | — | — | F1005.006 · monetization |

🆕 MITRE Fight Fraud Framework (F3) — 94 fraud-relevant skills

[](https://ctid.mitre.org/fraud/)

The MITRE Fight Fraud Framework (F3) was released April 9, 2026 by MITRE's Center for Threat-Informed Defense (CTID), co-developed with JPMorganChase, Citigroup, Lloyds Banking Group, Standard Chartered, CrowdStrike, Verizon Business, FS-ISAC, and others. It is an ATT&CK-compatible TTP catalog for cyber-enabled financial fraud — filling the gap ATT&CK leaves after initial compromise.

F3 v1.1 adds two fraud-specific tactics that ATT&CK does not enumerate:

• Positioning (FA0001) — actions taken after access to collect/manipulate data and prepare the fraud (synthetic-identity seeding, account warming, beneficiary setup, SIM-swap pre-positioning, banking-session hijack).
• Monetization (FA0002) — converting stolen assets into usable funds (money-mule layering, APP fraud, crypto off-ramping, card cash-out, refund/chargeback abuse).

Fraud-specific techniques use F1XXX IDs (e.g. F1005.003 Add Beneficiary, F1025.003 Wire Transfer, F1007 Adversary-in-the-Browser); reused ATT&CK techniques keep their T1XXX IDs. Mappings live in each skill's mitre_f3: frontmatter block — all 123 F3 v1.1 technique IDs were verified against the upstream STIX bundle. See [docs/mitre-f3-mapping.md](docs/mitre-f3-mapping.md) for the schema.

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.

| Tactic | ID | Skills | |--------|----|--------| | Reconnaissance | TA0043 | 103 | | Resource Development | TA0042 | 22 | | Initial Access | TA0001 | 467 | | Execution | TA0002 | 350 | | Persistence | TA0003 | 444 | | Privilege Escalation | TA0004 | 464 | | Stealth | TA0005 | 442 | | Defense Impairment | TA0112 | 92 | | Credential Access | TA0006 | 202 | | Discovery | TA0007 | 237 | | Lateral Movement | TA0008 | 68 | | Collection | TA0009 | 172 | | Command and Control | TA0011 | 123 | | Exfiltration | TA0010 | 82 | | Impact | TA0040 | 50 |

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 — 29 security domains

| Domain | Skills | Key capabilities | |---|---|---| | Cloud Security | 66 | AWS, Azure, GCP hardening · CSPM · cloud attack emulation · cloud forensics | | Threat Hunting | 58 | Hypothesis-driven hunts · LOTL detection · EVTX hunting · fleet hunting | | Threat Intelligence | 52 | STIX/TAXII · MISP · OpenCTI · feed integration · actor profiling | | Network Security | 43 | IDS/IPS · firewall rules · VLAN segmentation · traffic analysis | | Web Application Security | 42 | OWASP Top 10 · SQLi · XSS · SSRF · deserialization | | Digital Forensics | 41 | Disk imaging · memory forensics · Hayabusa/KAPE/Plaso timelines | | Malware Analysis | 39 | Static/dynamic analysis · reverse engineering · sandboxing | | Identity & Access Management | 37 | Entra ID/ROADtools · device-code phishing · PAM · zero trust identity | | SOC Operations | 35 | Playbooks · escalation workflows · Graph-log detection · tabletop exercises | | Red Teaming | 33 | ADCS/Certipy · BloodHound CE · Sliver/Havoc C2 · NTLM relay | | Container Security | 33 | K8s RBAC · image scanning · Falco · container escape | | Security Operations | 28 | SIEM correlation · log analysis · alert triage | | OT/ICS Security | 28 | Modbus · DNP3 · IEC 62443 · historian defense · SCADA | | API Security | 28 | GraphQL · REST · OWASP API Top 10 · WAF bypass | | Incident Response | 26 | Breach containment · ransomware response · IR playbooks | | Vulnerability Management | 25 | Nessus · scanning workflows · patch prioritization · CVSS | | Penetration Testing | 21 | Network · web · cloud · mobile · NetExec lateral movement | | DevSecOps | 18 | CI/CD security · Trivy IaC/image scanning · code signing | | Zero Trust Architecture | 17 | BeyondCorp · CISA maturity model · microsegmentation | | Endpoint Security | 17 | EDR · LOTL detection · fileless malware · persistence hunting | | Cryptography | 16 | TLS · Ed25519 · post-quantum migration · key management | | Phishing Defense | 15 | Email authentication · BEC detection · phishing IR | | AI Security | 14 | LLM red-teaming (garak/PyRIT) · prompt injection · MCP/agentic security · guardrails | | Mobile Security | 13 | Android/iOS analysis · mobile pentesting · MDM forensics | | Ransomware Defense | 13 | Precursor detection · response · recovery · encryption analysis | | Compliance & Governance | 9 | NIST 800-30/RMF · CMMC · HIPAA · TPRM · CIS benchmarks | | Supply Chain Security | 8 | SBOMs · dependency confusion · malicious-package triage · SLSA/Sigstore | | Deception Technology | 6 | Honeytokens · canarytokens · breach detection | | Hardware & Firmware Security | 4 | CHIPSEC/UEFI audit · Secure Boot bypass · TPM attestation · bootkit hunting |

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 817 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 817 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.

📊 MITRE ATT&CK Enterprise coverage — all 14 tactics

 

| Tactic | ID | Coverage | Key skills | |---|---|---|---| | Reconnaissance | TA0043 | Strong | OSINT, subdomain enumeration, DNS recon | | Resource Development | TA0042 | Moderate | Phishing infrastructure, C2 setup detection | | Initial Access | TA0001 | Strong | Phishing simulation, exploit detection, forced browsing | | Execution | TA0002 | Strong | PowerShell analysis, fileless malware, script block logging | | Persistence | TA0003 | Strong | Scheduled tasks, registry, service accounts, LOTL | | Privilege Escalation | TA0004 | Strong | Kerberoasting, AD attacks, cloud privilege escalation | | Defense Evasion | TA0005 | Strong | Obfuscation, rootkit analysis, evasion detection | | Credential Access | TA0006 | Strong | Mimikatz detection, pass-the-hash, credential dumping | | Discovery | TA0007 | Moderate | BloodHound, AD enumeration, network scanning | | Lateral Movement | TA0008 | Strong | SMB exploits, lateral movement detection with Splunk | | Collection | TA0009 | Moderate | Email forensics, data staging detection | | Command and Control | TA0011 | Strong | C2 beaconing, DNS tunneling, Cobalt Strike analysis |

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mukul975
• Source: mukul975/Anthropic-Cybersecurity-Skills
• License: Apache-2.0
• Homepage: https://mahipal.engineer/Anthropic-Cybersecurity-Skills/

Install and usage instructions live in the source repository linked above.