AI Coding Assistants Comparison

Data Privacy & Security

GitHub Copilot

✓ Operates on Microsoft Azure infrastructure
✓ Prompts discarded after suggestions are generated
✓ Suggestions discarded after being shown
✓ TLS encrypted data in transit
✓ Microsoft Azure's data encryption at rest
✓ AI-based vulnerability prevention system

Cursor

✓ Privacy Mode available
✓ No plaintext code storage with Privacy Mode
✓ AES 256 encryption for data at rest
✓ TLS 1.2 minimum for data in transit
✓ Code embeddings architecture stores no raw code in cloud
✓ Respects .gitignore and .cursorignore files
✓ Complete data removal within 30 days of account deletion

Windsurf (Codeium)

✓ Zero data retention for paid users
✓ Data protected at rest by major cloud providers
✓ SSL encryption in transit
✓ No sharing or selling of collected data
✓ Opt-out available for Individual Plan users
✓ Self-hosted deployments option for Enterprise customers

Use of Third-Party Services

GitHub Copilot

ℹ Operates within Microsoft Azure ecosystem
ℹ Limited details on interactions with other third-party AI model providers

Cursor

ℹ Infrastructure hosted on AWS
ℹ Uses Fireworks for custom models
ℹ Zero data retention agreements with OpenAI and Anthropic
ℹ Uses Google Cloud Vertex API (Gemini)
ℹ Embeddings stored with Turbopuffer on Google Cloud
ℹ Uses Exa and SerpApi for web search
ℹ Other subprocessors: MongoDB, Datadog, Databricks/Foundry/Voltage Park

Windsurf (Codeium)

ℹ Relies on major cloud providers for data protection
ℹ May offer tools to export User Content to third-party services
ℹ Users can integrate with Third-Party Platforms (e.g., IDEs, web search)
ℹ Uses Google Analytics according to its privacy policy

Compliance & Certifications

GitHub Copilot

SOC 2 GDPR Enterprise Security

Cursor

SOC 2 Type II Annual Penetration Testing Control Self-Assessments

Windsurf (Codeium)

SOC 2 Type II

Common Privacy & Security Concerns Addressed

AI Model Training on User Data

+

GitHub Copilot

In enterprise accounts, user data is not used for AI training. The models are trained on vast public datasets, and suggestions are based on learned patterns, not direct copies of training data.

Cursor

With Privacy Mode enabled, the code data submitted will never be trained on. Even without Privacy Mode, the Privacy Policy details limited circumstances where Materials might be used for improvement, explicitly stating that Inputs and Outputs are not used to train models unless flagged for trust and safety, explicitly reported, or the user opts in.

Windsurf (Codeium)

Will never train generative models on private data. For Autocomplete User Content (Individual Plan), it may be used to improve discriminative models (ranking code) but is anonymized, and users can opt out. Chat User Content (Individual Plan) may be used to improve both generative and discriminative models after anonymization, with an opt-out that results in losing access to Chat Services. For Pro Users, Customer Data can be limited to real-time suggestion generation and deletion, explicitly not used for training.

Potential Data Leakage Risks

+

GitHub Copilot

Includes filters at the proxy server to detect and discard potentially harmful or sensitive information in prompts and suggestions.

Cursor

Privacy Mode is designed to prevent storage of plaintext code by Cursor and its subprocessors. The parallel infrastructure for privacy and non-privacy mode requests aims to enhance resilience against accidental data exposure. Codebase indexing uses obfuscated file paths.

Windsurf (Codeium)

Zero data retention policy for paid users minimizes the window for potential leakage. Self-hosting option eliminates Codeium's access to the data entirely for enterprise clients. Data in transit and at rest is encrypted.

IP Protection Measures

+

GitHub Copilot

GitHub does not claim ownership of suggestions, and users retain ownership of their code. A filter compares suggestions against public GitHub repositories, and suggestions with exact matches longer than 150 characters are not provided. An upcoming code referencing feature will provide links to potentially matching public code and licensing information.

Cursor

Cursor customers own all the code generated by Cursor. The codebase indexing feature is designed to retrieve relevant local code without storing plaintext on servers.

Windsurf (Codeium)

The Terms of Service outline that users are responsible for ensuring they have the necessary rights to their User Content and that it does not infringe on third-party rights. Exafunction may use Autocomplete User Content and Chat User Content (anonymized and opt-out available for Individual Plan) to improve services. For Pro users, they retain control over their Customer Data with options for limited use and deletion.

Key Differentiators

GitHub Copilot

Benefit of being deeply integrated into the development workflow and backed by Microsoft's Azure infrastructure, offering a widely adopted solution. Its public code filter and upcoming referencing feature directly address copyright concerns related to generated code.

Cursor

Strongest emphasis on user privacy with its robust and default-enabled Privacy Mode for team users, guaranteeing zero data retention and no training on private code. The unique approach to codebase indexing, where plaintext code is not stored on servers, is a significant differentiator.

Windsurf (Codeium)

Offers a self-hosting option for enterprise customers, providing the highest level of data control. The automatic zero data retention for paid users simplifies data privacy management. Clear distinctions in how user content is used for model improvement, with opt-out options for individual users, provide transparency.

Potential Risks and Additional Details for Enterprise Adoption

Third-Party Dependencies

All three tools rely on cloud infrastructure and, in the case of Cursor, multiple AI model providers and other subprocessors. Enterprises should carefully review the security and privacy policies of these subprocessors and ensure they align with their own governance requirements. Cursor provides a list of its subprocessors.

Evolving AI and Security Landscape

The field of AI and related security risks are constantly evolving. Enterprises should stay informed about the latest vulnerabilities and security practices in the AI space and ensure their chosen tool provider maintains up-to-date security measures.

User Data Protection

Organizations must consider how their developers' code and data are protected when using these tools. Implementing proper access controls, monitoring usage patterns, and educating developers about potential security risks are essential steps for safe adoption.