This weekend, I had a chance to explore an interesting open-source project called Anthropic Cybersecurity Skills.
The project focuses on cybersecurity “skills” for AI agents and security workflows. After spending some time reviewing the repository and testing different ideas in a lab environment, I believe this type of approach could become very useful for the future of SOC operations and defensive cybersecurity.
What Is This Repository?
This repository contains hundreds of cybersecurity skills designed for AI agents.
These skills are more than simple prompts. They are structured security workflows and operational knowledge for areas such as:
- Threat Hunting
- Incident Response
- Phishing Investigation
- SIEM Operations
- Cloud Security
- Detection Engineering
- Executive Reporting
- MITRE ATT&CK Mapping
Each skill explains:
- when to use it
- investigation steps
- validation methods
- response guidance
- recommended workflows
This helps AI systems behave more like experienced security analysts instead of only answering questions.
AI Assistant vs AI Agent
Today many people use AI assistants such as ChatGPT or Copilot. But AI agents are a little different. An AI assistant mostly helps answer questions.
An AI agent can:
- read logs
- analyze files
- follow investigation workflows
- generate reports
- recommend response actions
- create visualizations
- assist with detection engineering
This creates many interesting possibilities for SOC and blue team operations.
Why This Matters for SOC Teams
Security teams spend a large amount of time on:
- alert triage
- repetitive investigations
- reporting
- dashboard creation
- query writing
- incident documentation
AI agents combined with cybersecurity skills may help improve:
- investigation speed
- consistency
- documentation quality
- executive communication
- analyst productivity
For example, an AI agent could help:
- summarize suspicious login activity
- map incidents to MITRE ATT&CK
- recommend containment actions
- generate KQL, SPL, or Sigma rules
- build executive-friendly summaries
One Important Point
I think one of the safest ways to start learning this technology is by using:
- isolated lab environments
- manual sample logs
- test data
- human validation
Instead of directly connecting AI systems to production environments.
This helps security teams better understand:
- AI limitations
- hallucinations
- workflow design
- response quality
- operational risks
before introducing automation into real environments.
The Future of Cybersecurity Operations
I believe the future SOC model will look more like:
AI Agent + Human AnalystThe AI helps with:
- investigation guidance
- workflow execution
- summarization
- detection suggestions
- data correlation
The human analyst remains responsible for:
- validation
- risk decisions
- approvals
- business context
- final response actions
AI will probably not replace SOC analysts, but analysts who understand how to work with AI agents may become much more effective in the coming years.
Credit & Inspiration
Special thanks to Mahipal (@mukul975) for creating and maintaining the open-source repository: