Addressing a Secret by a path segment makes its name part of the URL's
structure, not just its content. The name arrives from a public Rust API that
does no validation -- validation is the service's -- so a name carrying path
syntax decided which handler received the request. `create_secret("../jobs",
value)` resolved to `/v1/jobs/create` and delivered a body holding a live
credential to a route with none of this one's body suppression.
Each component of an identifier is now percent-encoded before the delimiter
joins them. Per component, not over the joined string: the delimiter stays a
delimiter, and a component cannot become two. Every character a Secret name and
a namespace segment may hold is unreserved, so an identifier the service would
accept passes through byte-identical and reads like the table and Function
identifiers beside it -- `/v1/secret/prod$openai-prod.v1/drop`. One the service
would refuse is merely made to arrive, so that it can be refused. This is not
name validation; it is what makes the service's validation reachable.
Encoding cannot cover a dot-only component. `.` and `..` are unreserved, so
nothing in them needs escaping character by character, but URL parsing resolves
dot segments after percent-decoding -- `%2E%2E` is a double-dot segment as
surely as `..` is, and no spelling of one reaches a route. Those are refused
before a request is built, with the client reporting that it cannot express the
request rather than sending one that resolves elsewhere.
Tables and Functions join their identifiers unencoded and have the same gap:
`drop_table("../jobs", &[])` produces `/v1/jobs/drop/` today. That is filed
separately rather than widened into this change, which is already the first
route to carry a credential in its body.
Tests: the two reproducers from review are kept as regression tests -- a name
cannot leave `/v1/secret/`, and two distinct identities cannot share one URL --
alongside one that pins the ordinary case as unencoded.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UfmeJ533rQDnPBkMtjerV6
The Multimodal AI Lakehouse
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors
The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
Demo: Multimodal Search by Keyword, Vector or with SQL
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Products:
- Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
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Ecosystem:
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How to Install:
Follow the Quickstart doc to set up LanceDB locally.
API & SDK: We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|---|---|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/rest |
Join Us and Contribute
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.
Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.
