You seem to be talking mostly about the CD part. Some thoughts:

On the one hand, CD workflows are less exposed than CI workflows. You only deploy code that has made it through your review and CI processes. In a non-continuous deployment model, you only deploy code when you decide to. You are not running your CD workflow on a third-party pull request.

On the other hand, the actual CD permission is a big deal. If you leak a credential that can deploy to your k8s cluster, you are very, very pwned. Possibly in a manner that is extremely complex to recover from.

I also admit that I find it rather surprising that so many workflows have a push model of deployment like this. My intuition for how to design a CD-style system would be:

1. A release is tagged in source control.

2. Something consumes that release tag and produces a production artifact. This might be some sort of runner that checks out the tagged release, builds it, and produces a ghcr image. Bonus points if that process is cleanly reproducible and more bonus points if there's also an attestation that the release artifact matches the specified tag and all the build environment inputs. (I think that GitHub Actions can do this, other than the bonus points, without any secrets.)

3. Something tells production to update to the new artifact. Ideally this would trigger some kind of staged deployment. Maybe it's continuous, maybe it needs manual triggering. I think that, in many production systems, this could be a message from the earlier stages that tells an agent with production privileges to download and update. It really shouldn't be that hard to make a little agent in k8s or whatever that listens to an API call from a system like GitHub Actions, authenticates it using OIDC, and follows its deployment instructions.

P.S. An attested-reproducible CD build system might be an interesting startup idea.