anthropic-cybersecurity-skills
reason-machines/security-skills
754 structured cybersecurity skills mapped to MITRE ATT&CK, NIST CSF, ATLAS, D3FEND, and NIST AI RMF frameworks.
What is anthropic-cybersecurity-skills?
A production-grade library of 754 cybersecurity skills organized across 26 security domains and mapped to five industry-standard frameworks. Use this to enable AI agents to perform incident response, threat hunting, malware analysis, forensics, and security posture assessment with expert-level guidance.
- Access 754 production-grade cybersecurity skills spanning 26 security domains
- Map security operations to MITRE ATT&CK techniques, NIST CSF 2.0, MITRE ATLAS, D3FEND, and NIST AI RMF frameworks
- Discover skills by domain, framework mapping, or tags using provided Python utilities
- Load skills progressively to minimize token cost (frontmatter ~30 tokens, full skill ~500-2000 tokens)
- Access structured references including standards mappings, technical workflows, helper scripts, and templates
How to install anthropic-cybersecurity-skills
npx skills add https://github.com/reason-machines/security-skills --skill anthropic-cybersecurity-skills- Python 3.6+ for skill discovery and loading utilities
- Access to the skill repository (GitHub or local clone)
- Basic familiarity with MITRE ATT&CK, NIST CSF, or other referenced frameworks (optional but helpful)
How to use anthropic-cybersecurity-skills
- 1.Install the skill library using npx, git clone, or git submodule
- 2.Use the SkillLoader class to scan all skill frontmatter and build an index of available skills
- 3.Search for relevant skills by domain, ATT&CK technique ID, or tags using the provided Python functions
- 4.Load the full skill content (metadata, references, scripts) when you need to execute a specific skill
- 5.Reference the skill's standards.md for framework mappings and workflows.md for technical procedures
Use cases
- Investigate security incidents by mapping attack patterns to relevant skills and frameworks
- Perform malware analysis and reverse engineering with guided procedures and checklists
- Conduct threat hunting across cloud and on-premises environments using domain-organized skills
- Execute memory forensics and incident response workflows with step-by-step technical guidance
- Assess and improve security posture by discovering skills relevant to NIST CSF or ATT&CK techniques
- Security operations center (SOC) analysts and incident responders
- Threat hunters and malware analysts
- Security architects designing defense strategies
- AI agents performing autonomous security operations
- Organizations mapping their security practices to industry frameworks
anthropic-cybersecurity-skills FAQ
754 skills organized into 26 security domains. Each skill includes metadata, framework mappings, technical workflows, helper scripts, and templates.
MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, and NIST AI RMF. This enables alignment with multiple industry standards and compliance requirements.
Use the find_by_attack_technique() function provided in the SKILL.md, which searches skill references for a specific technique ID (e.g., T1003 for Credential Dumping).
Yes. The skills follow the agentskills.io standard and are designed for AI-driven security operations. Use the SkillLoader to integrate skills into your agent workflow.
Use the progressive loading pattern: scan all frontmatter first (~30 tokens each) to build an index, then load only the full skill content (~500-2000 tokens) when needed.
Full instructions (SKILL.md)
Source of truth, from reason-machines/security-skills.
name: anthropic-cybersecurity-skills description: Use 754 structured cybersecurity skills mapped to MITRE ATT&CK, NIST CSF, ATLAS, D3FEND, and NIST AI RMF for AI-driven security operations triggers:
- "help me investigate this security incident"
- "analyze this malware sample"
- "perform memory forensics on this dump"
- "hunt for threats in our environment"
- "check cloud security posture"
- "map this attack to MITRE ATT&CK"
- "what security skills are available"
- "guide me through incident response"
anthropic-cybersecurity-skills
Skill by ara.so — Security Skills collection.
Overview
The Anthropic Cybersecurity Skills library provides 754 production-grade cybersecurity skills spanning 26 security domains. Each skill is structured following the agentskills.io standard and mapped to five industry frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, and NIST AI RMF. This enables AI agents to perform security operations with expert-level guidance.
Installation
# Option 1: Using 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
# Option 3: Add as submodule
git submodule add https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills/cybersecurity
Directory Structure
skills/
├── {skill-name}/
│ ├── SKILL.md # Skill definition with YAML frontmatter
│ ├── references/
│ │ ├── standards.md # Framework mappings
│ │ └── workflows.md # Technical procedures
│ ├── scripts/
│ │ └── *.py # Helper scripts
│ └── assets/
│ └── *.md # Templates and checklists
Discovering Skills
By Domain
Skills are organized into 26 domains. List all domains:
import os
import yaml
def list_domains():
domains = {}
for skill_dir in os.listdir('skills'):
skill_path = f'skills/{skill_dir}/SKILL.md'
if os.path.exists(skill_path):
with open(skill_path, 'r') as f:
content = f.read()
# Extract YAML frontmatter
if content.startswith('---'):
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
domain = frontmatter.get('domain', 'unknown')
subdomain = frontmatter.get('subdomain', 'general')
if domain not in domains:
domains[domain] = {}
if subdomain not in domains[domain]:
domains[domain][subdomain] = []
domains[domain][subdomain].append(frontmatter['name'])
return domains
# Usage
domains = list_domains()
for domain, subdomains in domains.items():
print(f"\n{domain.upper()}")
for subdomain, skills in subdomains.items():
print(f" {subdomain}: {len(skills)} skills")
By Framework Mapping
Find skills mapped to specific ATT&CK techniques:
def find_by_attack_technique(technique_id):
"""Find skills mapped to a specific ATT&CK technique"""
matching_skills = []
for skill_dir in os.listdir('skills'):
skill_path = f'skills/{skill_dir}/SKILL.md'
if os.path.exists(skill_path):
with open(skill_path, 'r') as f:
content = f.read()
if content.startswith('---'):
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
# Check ATT&CK mappings in references
refs_path = f'skills/{skill_dir}/references/standards.md'
if os.path.exists(refs_path):
with open(refs_path, 'r') as ref_file:
if technique_id in ref_file.read():
matching_skills.append({
'name': frontmatter['name'],
'description': frontmatter['description'],
'path': skill_path
})
return matching_skills
# Usage
skills = find_by_attack_technique('T1003') # Credential Dumping
for skill in skills:
print(f"{skill['name']}: {skill['description']}")
By Tags
Search skills by tags:
def search_by_tags(search_tags):
"""Find skills matching any of the provided tags"""
results = []
for skill_dir in os.listdir('skills'):
skill_path = f'skills/{skill_dir}/SKILL.md'
if os.path.exists(skill_path):
with open(skill_path, 'r') as f:
content = f.read()
if content.startswith('---'):
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
skill_tags = frontmatter.get('tags', [])
if any(tag in skill_tags for tag in search_tags):
results.append(frontmatter)
return results
# Usage
malware_skills = search_by_tags(['malware-analysis', 'reverse-engineering'])
for skill in malware_skills:
print(f"{skill['name']}: {', '.join(skill['tags'])}")
Loading and Executing Skills
Progressive Loading Pattern
Load only frontmatter first (low token cost), then full content when needed:
class SkillLoader:
def __init__(self, skills_dir='skills'):
self.skills_dir = skills_dir
def scan_all_frontmatter(self):
"""Scan all skill frontmatter (~30 tokens each)"""
skills_index = []
for skill_dir in os.listdir(self.skills_dir):
skill_path = f'{self.skills_dir}/{skill_dir}/SKILL.md'
if os.path.exists(skill_path):
with open(skill_path, 'r') as f:
content = f.read()
if content.startswith('---'):
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
frontmatter['path'] = skill_path
skills_index.append(frontmatter)
return skills_index
def load_full_skill(self, skill_name):
"""Load complete skill content (~500-2000 tokens)"""
skill_path = f'{self.skills_dir}/{skill_name}/SKILL.md'
with open(skill_path, 'r') as f:
content = f.read()
# Parse frontmatter and body
if content.startswith('---'):
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
body = content[yaml_end + 3:].strip()
return {
'metadata': frontmatter,
'content': body,
'references': self._load_references(skill_name),
'scripts': self._load_scripts(skill_name)
}
def _load_references(self, skill_name):
"""Load framework mappings and workflows"""
refs = {}
refs_dir = f'{self.skills_dir}/{skill_name}/references'
if os.path.exists(refs_dir):
for ref_file in os.listdir(refs_dir):
with open(f'{refs_dir}/{ref_file}', 'r') as f:
refs[ref_file.replace('.md', '')] = f.read()
return refs
def _load_scripts(self, skill_name):
"""Load helper scripts"""
scripts = {}
scripts_dir = f'{self.skills_dir}/{skill_name}/scripts'
if os.path.exists(scripts_dir):
for script_file in os.listdir(scripts_dir):
with open(f'{scripts_dir}/{script_file}', 'r') as f:
scripts[script_file] = f.read()
return scripts
# Usage
loader = SkillLoader()
# Step 1: Scan all skills (lightweight)
all_skills = loader.scan_all_frontmatter()
print(f"Found {len(all_skills)} skills")
# Step 2: Find relevant skills
memory_forensics = [s for s in all_skills if 'memory-analysis' in s.get('tags', [])]
# Step 3: Load top matches fully
for skill in memory_forensics[:3]:
full_skill = loader.load_full_skill(skill['name'])
print(f"\n{skill['name']}")
print(f"Content length: {len(full_skill['content'])} chars")
Common Usage Patterns
Incident Response Workflow
def incident_response_guide(incident_type):
"""Get relevant IR skills for incident type"""
loader = SkillLoader()
all_skills = loader.scan_all_frontmatter()
# Map incident types to skill domains
incident_mappings = {
'ransomware': ['malware-analysis', 'incident-response', 'forensics'],
'data_breach': ['threat-hunting', 'forensics', 'cloud-security'],
'phishing': ['email-security', 'threat-intelligence', 'endpoint-security'],
'insider_threat': ['behavior-analytics', 'iam', 'forensics']
}
relevant_tags = incident_mappings.get(incident_type, [])
relevant_skills = [
s for s in all_skills
if any(tag in s.get('tags', []) for tag in relevant_tags)
]
# Prioritize by subdomain
prioritized = sorted(
relevant_skills,
key=lambda s: (
s.get('subdomain') == 'incident-response',
len(set(s.get('tags', [])) & set(relevant_tags))
),
reverse=True
)
return prioritized[:5]
# Usage
ransomware_skills = incident_response_guide('ransomware')
for skill in ransomware_skills:
print(f"- {skill['name']}: {skill['description']}")
ATT&CK Technique Coverage
def check_attack_coverage(technique_id):
"""Check which skills cover a specific ATT&CK technique"""
loader = SkillLoader()
coverage = []
for skill_dir in os.listdir('skills'):
refs_path = f'skills/{skill_dir}/references/standards.md'
if os.path.exists(refs_path):
with open(refs_path, 'r') as f:
content = f.read()
if technique_id in content:
skill = loader.load_full_skill(skill_dir)
coverage.append({
'name': skill['metadata']['name'],
'description': skill['metadata']['description'],
'domain': skill['metadata']['subdomain']
})
return coverage
# Usage
t1003_coverage = check_attack_coverage('T1003') # Credential Dumping
print(f"Skills covering T1003: {len(t1003_coverage)}")
for skill in t1003_coverage:
print(f" {skill['domain']}: {skill['name']}")
Multi-Framework Compliance Check
def compliance_mapper(skill_name):
"""Show all framework mappings for a skill"""
loader = SkillLoader()
skill = loader.load_full_skill(skill_name)
frameworks = {
'MITRE ATT&CK': skill['metadata'].get('attack_techniques', []),
'NIST CSF 2.0': skill['metadata'].get('nist_csf', []),
'MITRE ATLAS': skill['metadata'].get('atlas_techniques', []),
'MITRE D3FEND': skill['metadata'].get('d3fend_techniques', []),
'NIST AI RMF': skill['metadata'].get('nist_ai_rmf', [])
}
print(f"\nFramework mappings for: {skill_name}\n")
for framework, mappings in frameworks.items():
if mappings:
print(f"{framework}:")
for mapping in mappings:
print(f" - {mapping}")
# Usage
compliance_mapper('performing-memory-forensics-with-volatility3')
Working with Skill Scripts
Many skills include helper scripts in scripts/ directories:
import subprocess
import json
def execute_skill_script(skill_name, script_name, **kwargs):
"""Execute a skill's helper script with arguments"""
script_path = f'skills/{skill_name}/scripts/{script_name}'
if not os.path.exists(script_path):
raise FileNotFoundError(f"Script not found: {script_path}")
# Build command with arguments
cmd = ['python', script_path]
for key, value in kwargs.items():
cmd.extend([f'--{key}', str(value)])
# Execute
result = subprocess.run(cmd, capture_output=True, text=True)
return {
'stdout': result.stdout,
'stderr': result.stderr,
'returncode': result.returncode
}
# Usage example with memory forensics skill
result = execute_skill_script(
'performing-memory-forensics-with-volatility3',
'process.py',
dump_file='/path/to/memory.dmp',
plugin='windows.pslist'
)
if result['returncode'] == 0:
print(result['stdout'])
else:
print(f"Error: {result['stderr']}")
Environment Configuration
Skills that require API keys or credentials reference environment variables:
# .env file for skills requiring external services
export VIRUSTOTAL_API_KEY=your_vt_key_here
export SHODAN_API_KEY=your_shodan_key_here
export MISP_URL=https://your-misp-instance.com
export MISP_API_KEY=your_misp_key_here
export SPLUNK_HOST=your-splunk-host
export SPLUNK_TOKEN=your_splunk_token
Load in Python:
import os
from dotenv import load_dotenv
load_dotenv()
# Skills will reference these
vt_key = os.getenv('VIRUSTOTAL_API_KEY')
misp_url = os.getenv('MISP_URL')
Integration Examples
With Claude Code / Cursor
Place in your project's .claud/ or .cursorrules:
# Cybersecurity Skills Context
This project has access to 754 cybersecurity skills in the `skills/` directory.
When I ask security questions:
1. Scan skill frontmatter in skills/*/SKILL.md
2. Match by domain, subdomain, or tags
3. Load top 3 relevant skills fully
4. Follow the Workflow sections step-by-step
5. Verify results using Verification sections
Example: "analyze this memory dump"
→ load performing-memory-forensics-with-volatility3/SKILL.md
→ execute Volatility3 commands from Workflow
→ validate findings using Verification checklist
With Custom AI Agent (Python)
class CybersecurityAgent:
def __init__(self, skills_dir='skills'):
self.loader = SkillLoader(skills_dir)
self.skill_index = self.loader.scan_all_frontmatter()
def handle_query(self, user_query):
"""Process security query using relevant skills"""
# Step 1: Find relevant skills
relevant = self._match_skills(user_query)
# Step 2: Load top matches
top_skills = [
self.loader.load_full_skill(s['name'])
for s in relevant[:3]
]
# Step 3: Extract workflow steps
workflows = []
for skill in top_skills:
content = skill['content']
# Extract Workflow section
if '## Workflow' in content:
start = content.index('## Workflow')
end = content.index('##', start + 1) if '##' in content[start + 1:] else len(content)
workflows.append(content[start:end])
return {
'matched_skills': [s['metadata']['name'] for s in top_skills],
'workflows': workflows,
'framework_mappings': self._get_mappings(top_skills)
}
def _match_skills(self, query):
"""Simple keyword matching (replace with semantic search)"""
query_lower = query.lower()
scores = []
for skill in self.skill_index:
score = 0
desc = skill['description'].lower()
tags = ' '.join(skill.get('tags', [])).lower()
# Score by keyword matches
for word in query_lower.split():
if word in desc:
score += 2
if word in tags:
score += 1
if score > 0:
scores.append((score, skill))
return [s for _, s in sorted(scores, reverse=True)]
def _get_mappings(self, skills):
"""Extract framework mappings from loaded skills"""
mappings = {
'attack': set(),
'nist_csf': set(),
'atlas': set()
}
for skill in skills:
meta = skill['metadata']
mappings['attack'].update(meta.get('attack_techniques', []))
mappings['nist_csf'].update(meta.get('nist_csf', []))
mappings['atlas'].update(meta.get('atlas_techniques', []))
return {k: list(v) for k, v in mappings.items()}
# Usage
agent = CybersecurityAgent()
response = agent.handle_query("investigate credential dumping attack")
print("Matched skills:", response['matched_skills'])
print("\nATT&CK Techniques:", response['framework_mappings']['attack'])
print("\nFirst workflow:")
print(response['workflows'][0][:500])
Troubleshooting
Skill Not Found
def verify_skill_exists(skill_name):
"""Check if skill exists and is properly formatted"""
skill_path = f'skills/{skill_name}/SKILL.md'
if not os.path.exists(skill_path):
print(f"❌ Skill not found: {skill_path}")
return False
with open(skill_path, 'r') as f:
content = f.read()
if not content.startswith('---'):
print(f"❌ Invalid format: missing YAML frontmatter")
return False
try:
yaml_end = content.find('---', 3)
frontmatter = yaml.safe_load(content[3:yaml_end])
required_fields = ['name', 'description', 'domain', 'subdomain']
for field in required_fields:
if field not in frontmatter:
print(f"❌ Missing required field: {field}")
return False
print(f"✅ Skill valid: {skill_name}")
return True
except Exception as e:
print(f"❌ YAML parse error: {e}")
return False
Framework Mapping Missing
If a skill doesn't show framework mappings, check references/standards.md:
def audit_framework_mappings(skill_name):
"""Check which framework mappings exist for a skill"""
refs_path = f'skills/{skill_name}/references/standards.md'
if not os.path.exists(refs_path):
print(f"⚠️ No references/standards.md found")
return
with open(refs_path, 'r') as f:
content = f.read()
frameworks = {
'ATT&CK': r'T\d{4}',
'NIST CSF': r'[A-Z]{2}\.[A-Z]{2}',
'ATLAS': r'AML\.T\d{4}',
'D3FEND': r'D3-[A-Z]+',
'AI RMF': r'[A-Z]+-\d+\.\d+'
}
import re
for name, pattern in frameworks.items():
matches = re.findall(pattern, content)
if matches:
print(f"✅ {name}: {', '.join(set(matches))}")
else:
print(f"⚠️ {name}: No mappings found")
Key Features Summary
- 754 skills across 26 security domains
- 5 framework mappings: ATT&CK, NIST CSF, ATLAS, D3FEND, AI RMF
- Progressive loading: scan frontmatter (~30 tokens), load full content only when needed
- Structured workflows: step-by-step procedures in every skill
- Helper scripts: working Python scripts in
scripts/directories - Framework standards: complete mappings in
references/standards.md - agentskills.io compliant: works with 26+ AI coding platforms
License
Apache 2.0 — see repository for full license text.
Contributing
Contributions welcome following the project's CONTRIBUTING.md guidelines. All skills must include YAML frontmatter, structured Markdown sections, and framework mappings.
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