The document asserts that users own code generated by Windsurf products to the extent permitted by law, and discloses that attribution filtering is applied to intercept generated code similar to non-permissively licensed code before it is shown to users. The document also acknowledges limitations in making representations about third-party model training data.
This analysis describes what Windsurf's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
This provision establishes the scope of the ownership assertion and the technical mechanism used to reduce non-permissive license exposure, while acknowledging that representations cannot be made about third-party model training data. Enterprise customers are offered indemnity clauses as a complementary contractual protection for compliance purposes.
Interpretive note: The legal enforceability and scope of the ownership assertion depends on jurisdiction-specific AI copyright law, which remains an area of active legal development in multiple jurisdictions.
The updated document establishes explicit commitments about how Windsurf protects data and manages security. The terms state that all data transmission is encrypted in transit and at rest, that access to production systems is restricted to a small number of employees or contractors based on business roles, and that production systems are monitored via logging, error handling, and monitoring dashboards. The document discloses that Windsurf obtained SOC 2 Type II certification as of March 2024 and that all employees and contractors are required to use multi-factor authentication and receive annual security training. These disclosures describe organizational practices rather than establishing new user-facing rights or obligations.
View change record →Changed detection methodology from 'line-by-line fuzzy matching algorithm of hashes' to 'Jaccardian edit-distance' and added explicit statement about sanitizing training data.
View full change record →Under this clause, the agreement asserts user ownership of generated code subject to applicable law, and discloses that attribution filtering is applied automatically for all users on all plans. The document acknowledges that the platform cannot guarantee the training data composition of third-party underlying models, which may affect the scope of the ownership and compliance representations.
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"You own all of the code generated by Windsurf's products, to the extent permitted by law. To the best of our ability, we have sanitized any of the public data that we use for training by removing any non-permissively licensed code, or code that is similar to the non-permissively licensed code via Jaccardian edit-distance. Any generated code that is similar to non-permissively licensed code is intercepted and not shown to the user to minimize any chances of non-permissive code being accepted by an unaware user.— Excerpt from Windsurf's Windsurf Security & Data Handling
1. REGULATORY LANDSCAPE: This provision engages copyright law and open-source license compliance considerations in jurisdictions where AI-generated code ownership and training data liability are actively being litigated or legislated. The EU AI Act may impose additional transparency obligations regarding training data. The FTC Act is relevant to the accuracy of representations about attribution filtering capabilities. No specific enforcement action is cited. 2. GOVERNANCE EXPOSURE: Medium. The acknowledgment that representations cannot be made about third-party model training data creates a residual IP compliance exposure that attribution filtering alone may not fully address. Enterprise customers are offered indemnity clauses, but individual and team plan users are not explicitly described as having equivalent contractual protections. 3. JURISDICTION FLAGS: EU/EEA organizations should assess this provision in the context of emerging AI training data transparency requirements under the EU AI Act. Organizations in jurisdictions with active AI copyright litigation should evaluate the sufficiency of attribution filtering as a technical control. 4. CONTRACT AND VENDOR IMPLICATIONS: Enterprise procurement teams should negotiate indemnity clause terms directly with Windsurf if IP compliance exposure is a material concern. The document indicates indemnity is available for enterprise customers but does not specify the scope or limits of that indemnity, which should be reviewed in contract negotiations. 5. COMPLIANCE CONSIDERATIONS: Legal teams should assess whether the attribution filtering disclosure and the caveat regarding third-party model training data are sufficient for their organization's AI governance and IP compliance policies. Attribution and audit logging features available on Enterprise Hybrid and Self-hosted deployments may provide additional compliance documentation capabilities.
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This provision establishes the scope of the ownership assertion and the technical mechanism used to reduce non-permissive license exposure, while acknowledging that representations cannot be made about third-party model training data. Enterprise customers are offered indemnity clauses as a complementary contractual protection for compliance purposes.
Under this clause, the agreement asserts user ownership of generated code subject to applicable law, and discloses that attribution filtering is applied automatically for all users on all plans. The document acknowledges that the platform cannot guarantee the training data composition of third-party underlying models, which may affect the scope of the ownership and compliance representations.
No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by Windsurf.