Introduction to the Foundations of GitHub Copilot
Privacy Concerns, Data Usage, and Collection
According to its published privacy policy, GitHub Copilot follows defined guidelines on how user data is collected and handled.
When you use GitHub Copilot, the tool captures the code around your cursor (the prompt) and metadata related to open files to generate coding suggestions through its language models. These suggestions, along with how users interact with them - whether they are accepted or rejected - are crucial for improving Copilot's performance and accuracy. This data is used to train the model and enhance the tool's capabilities unless you opt out of data collection or have a Business or Enterprise subscription.
For Copilot Pro, GitHub may retain prompts and suggestions for up to 28 days and, with user consent, use them to improve its models. For Copilot Business and Enterprise, customer code and prompts are not used for training GitHub's models. In all cases, Copilot does not store entire private repositories, share your code with other users, have access to your local files, or retain a long-term memory of your prompts and code.
The official GitHub Copilot privacy policy outlines the following categories of data collected:
| Category | Description |
|---|---|
| User engagement data | Pseudonymous identifiers from interactions with Copilot, such as accepted or dismissed completions, error messages, system logs, and product usage metrics. |
| Prompts | Inputs for chat or code, along with surrounding context, sent to Copilot's AI to generate suggestions. |
| Suggestions | AI-generated code lines or chat responses provided to users based on their prompts. |
| Feedback Data | Real-time feedback such as thumbs up/down, optional comments, and input from support tickets. |
To facilitate this, data transmission from your local machine to GitHub's servers involves securely sending contextual information about the code and file being edited, as well as data on user interactions, to GitHub's Azure tenant. All transmitted data is encrypted in transit using Transport Layer Security (TLS), and any data retained at rest adheres to the robust standards of FIPS Publication 140-2, ensured by Microsoft Azure's encryption capabilities.
Initially, GitHub Copilot was not part of GitHub’s compliance scope for standards and certifications.
GitHub Copilot is now backed by the same compliance framework and security controls that apply to GitHub Enterprise Cloud. Over time, Copilot has been brought into the scope of major international standards and certifications to make it suitable for enterprise use operating in regulated environments. The following table summarizes the key certifications, security measures, and protections that GitHub Copilot offers as of mid-2025:
| Standard / Protection | Who It Applies To | What It Means in Practice |
|---|---|---|
| SOC 2 |
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