Cybersecurity Skills Wrap

What problem it addresses

When AI agents perform security analysis, detection response, compliance mapping, or threat-intelligence tasks, plain prompts often lack stable structure. Models may produce generic advice that is hard to align with frameworks such as MITRE ATT&CK and NIST CSF 2.0, and harder still to audit or reproduce. Cybersecurity Skills Wrap is not a single point tool. It organizes cybersecurity capabilities into structured skills that agents can call, reducing the translation cost between security-domain language and actionable steps.

How the skill works

The package is a Python wrapper containing 754 structured cybersecurity skills, mapped to five frameworks:

• MITRE ATT&CK: alignment with tactics, techniques, and procedures.
• NIST CSF 2.0: governance, identify, protect, detect, respond, and recover contexts.
• ATLAS: threat modeling for OT/ICS environments.
• D3FEND: mapping defensive technologies and countermeasures.
• NIST AI RMF: AI system risk-management perspective.

Typical use cases include asking an agent to analyze a malware sample, assess an attack chain, or map log alerts to ATT&CK techniques. The wrap layer selects the relevant skills and returns structured output, which is useful when teams need framework-aligned phrasing, automated orchestration, or a shared security vocabulary.

Boundaries and notes

This is a skill wrapper and mapping layer, not a replacement for EDR, SIEM, SOC tooling, or human investigation. Output quality depends on input data, model capability, and task context. For production incident response, retain human review, least privilege, and evidence-chain auditing. When the task requires live threat intelligence, private asset topology, or compliance forensics, treat it as a context-structuring tool rather than a final decision system.