> For the complete documentation index, see [llms.txt](https://docs.toucanai.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.toucanai.cloud/govern/security-model/secrets-and-encryption.md). # Secrets & encryption {% hint style="info" %} **Target Audience**: Developers and security reviewers configuring Toucan AI or evaluating how secrets are protected. {% endhint %} ### TL;DR * **Database connection credentials** (passwords, keys) are encrypted before being stored on the Toucan AI platform. * **Embed tokens** are encrypted and short-lived. * **Query result rows** are not stored in a separate encrypted cache — they are processed per request (see [Data storage & retention](/govern/security-model/data-storage-and-retention.md)). * **Encryption at rest** for the platform database depends on your deployment *** ### When to use this Use this page to understand how Toucan AI protects secrets and what encryption does *not* cover. *** ### Database connection credentials When you connect a database to Toucan AI, connection secrets are **encrypted at rest** in the platform database. * Only authorized server-side operations can decrypt them to run queries on your behalf. * When you view or edit a connection in the product, sensitive fields are **masked** in the UI and API responses. * Keys can be rotated; older ciphertext may be re-encrypted when credentials are accessed. **Your responsibility**: protect who can create or edit database connections in your Toucan organization. *** ### Embed tokens Embed tokens are **encrypted** (JWE, AES-256-GCM) and expire after a short period (default **one hour**). * API keys used to mint tokens must stay on **your server**, never in browser code. * See [Token security](/govern/security-model/token-security.md) for integration guidance. *** ### Query data and caching Toucan AI does **not** maintain a dedicated encrypted cache of your query result datasets. Each data request runs against your database and uses the result in memory for that operation. See data flow described above. Protection for query data relies on: * TLS between services and your database (as configured) * Access control (tokens, permissions, RLS/CLS) * Not persisting bulk copies of your rows on the platform *** ### Deployment-level encryption Additional controls (disk encryption, managed database encryption, key management) are part of your **infrastructure and contract** with Toucan AI. *** ### Best practices * Rotate database passwords on a regular schedule. * Restrict Toucan organization roles so only trusted admins manage connections. * Never commit API keys or connection strings to source control. * Use TLS-enabled database endpoints where supported. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.toucanai.cloud/govern/security-model/secrets-and-encryption.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.