Openai Security Ownership Map

What it does

This skill, openai-security-ownership-map, helps identify and map the ownership of OpenAI models and related resources. It provides a structured way to understand who is responsible for various aspects of an AI system built with OpenAI technologies. This includes identifying owners of training data, model weights, inference endpoints, and associated security responsibilities. Ultimately, it aims to improve accountability and transparency within AI development workflows.

When to use it

• Security Audits: During a security review of an application using OpenAI models, to clarify responsibility for different components.
• Incident Response: When investigating a security incident involving an OpenAI-powered system, to quickly determine who needs to be involved in remediation.
• Compliance Checks: To document and demonstrate adherence to organizational or regulatory requirements regarding AI model ownership.
• Team Onboarding: When new team members join a project using OpenAI models, to provide clear understanding of roles and responsibilities.

Key capabilities

• Model Ownership Mapping: Identifies owners for various components (training data, weights, endpoints).
• Security Responsibility Assignment: Links ownership with specific security duties.
• Structured Documentation: Generates organized documentation of the OpenAI model ecosystem.

Example prompts

• "Create an ownership map for our 'Customer Support Bot' application using GPT-4."
• "Who is responsible for securing the inference endpoint for the 'Image Generator'?"
• "Document the data lineage and ownership for the training dataset used by the 'Sentiment Analyzer'."

Tips & gotchas

The skill relies on accurate input regarding the components of your OpenAI system. Ensure you have a good understanding of your architecture before using this skill to generate an effective ownership map.