IT & Software

Governance and Security

Safeguard Sensitive Data with This ChatGPT Prompt for Governance and Security Compliance

What This Prompt Does

Raises awareness about data governance, privacy risks, and security protocols when using public LLMs like ChatGPT.
Reinforces internal policies around sharing PII (personally identifiable information), proprietary source code, or confidential business data.
Encourages software engineers to practice safe prompting habits when using ChatGPT for ideation, debugging, or code generation in public environments.
Acts as a foundational reminder before prompting, ensuring that usage of ChatGPT aligns with corporate compliance standards.

Tips

Never include sensitive or identifiable information in prompts to public models—even in anonymized form—unless you are 100% sure it's permissible under your organization’s policies.
Create an internal checklist or use case document that clarifies what types of data are safe to share with LLMs and which are off-limits.
For enterprise use, consider setting up a private or isolated instance of ChatGPT via OpenAI's API, Azure OpenAI, or a fine-tuned internal model to maintain data privacy.
Use prompt templates that abstract or generalize real-world examples. Replace real class names, endpoints, or user data with placeholders like [FUNCTION_NAME], [API_KEY], [USER_DATA].
Educate your engineering teams with regular security briefings on the differences between public vs. private LLM deployments and how to use each appropriately.

Prompt

For public models, software engineers should adhere to internal guidelines. Anything you input into ChatGPT will be used in its training data and may be shared with other users and OpenAI / Microsoft. As such, sensitive data and company information should not be shared.
Now that you understand the basics, let’s dive into the best ChatGPT prompts for software engineering.

How To Use The Prompt

Use this prompt at the beginning of any session involving ChatGPT in a corporate, development, or collaborative environment. Tailor it to include:

[DEPLOYMENT TYPE]: Public ChatGPT, OpenAI API, Azure OpenAI, or internal model.
[SENSITIVITY LEVEL]: High (e.g., production data), Medium (e.g., code structure), Low (e.g., public documentation).
[COMPANY POLICY LINK OR SUMMARY]: Include links or notes on your internal guidelines.
[ALTERNATIVE TOOLS OR SANDBOXES]: If available, point users to internal tools that offer secure AI access.

Example:
"Deployment type: Public ChatGPT via browser; Sensitivity level: Medium – internal naming conventions and in-development code snippets; Policy reference: See 'AI Usage & Privacy Standards' on Confluence; Alternative tool: Internal AI code assistant hosted on Azure."

Example Input

#INFORMATION ABOUT MY ENVIRONMENT:
Deployment type: OpenAI public API (non-enterprise tier)
Sensitivity level: High – customer analytics and financial forecasting models
Company policy: Do not share any real customer data, private keys, model weights, or internal tools
Prompt strategy goal: Generate safe and generalized example code for internal documentation without exposing proprietary details

Additional Information

This governance and security prompt is essential for teams working with AI tools in regulated or IP-sensitive industries like finance, healthcare, defense, or SaaS. It helps:

Build risk awareness around prompt content.
Guide software teams to abstract and sanitize inputs before interacting with external models.
Support auditability by encouraging teams to document their use of AI tools responsibly.

By embedding this safety-first mindset into your prompt culture, you protect your organization’s intellectual property, maintain compliance, and preserve trust with clients and partners. This prompt isn’t just a best practice—it’s a non-negotiable for ethical and secure AI use in modern engineering teams.

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