## Pin your `fastapi` version { #pin-your-fastapi-version }

The first thing you should do is to "pin" the version of **FastAPI** you are using to the specific latest version that you know works correctly for your application.

auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a
# For new protobuf, if V.x.y is gencode version, then runtime version U must be
# V <= U <= V+1

auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a
# For new protobuf, if V.x.y is gencode version, then runtime version U must be
# V <= U <= V+1

You can learn more about [FastAPI versions and how to pin and upgrade them](https://fastapi.tiangolo.com/deployment/versions/) for your project in the docs.

## Reporting a Vulnerability

pkg regexp, method (*Regexp) UnmarshalText([]uint8) error #46159
pkg runtime, method (*PanicNilError) Error() string #25448
pkg runtime, method (*PanicNilError) RuntimeError() #25448
pkg runtime, method (*Pinner) Pin(interface{}) #46787
pkg runtime, method (*Pinner) Unpin() #46787
pkg runtime, type PanicNilError struct #25448
pkg runtime, type Pinner struct #46787

## 0.112.1

### Upgrades

* ⬆️ Allow Starlette 0.38.x, update the pin to `>=0.37.2,<0.39.0`. PR [#11876](https://github.com/fastapi/fastapi/pull/11876) by [@musicinmybrain](https://github.com/musicinmybrain).

### Docs

        already installed on the system.
*   Using .post1 instead of a full minor release allowed us to push this release
    out quickly. However, please note the following caveat:
    *   For users wishing to pin their Python dependency in a requirements file
        or other situation, under Python's version specification rules,
        `tensorflow[and-cuda]==2.15.0` will not install this fixed version.