Python Library for storing OAuth credentials in many locations

What's this for?

By their very nature, OAuth credentials are valuable and dangerous, and have to be stored securely. As a result, the same tasks to store these tokens in a simple and secure fashion have to be written each time, or copied and pasted around - leading to potential issues as problems are found and not fixed in all places.

This library will store OAuth tokens in any of the following places:

1. Secret Manager
2. Firestore
3. Google Cloud Storage files
4. A local json file

Other storage locations can be added at will simply by extending the AbstractDatastore class in the same way as the four examples.

Initial Setup And Installation

Enable the APIs on Google Cloud

In order to use the connectors to any of the Google Cloud storage methods (Secret Manager, Firestore and Google Cloud Storage) you will have to ensure that the relevant APIs have been enabled. Follow the instructions listed in the developer documentation to enable the API you need.

Ensure the app's service account has acces to the APIs

Implementation specific

Secret Manager

Two secrets will need to be manually added to Secret Manager before the library can be used. These are the client id and client secret. The easiest way to do this is using a small shell script like this:

#!/bin/bash

while [[ $1 == -* ]] ; do
  case $1 in
    --project*)
      IFS="=" read _cmd PROJECT <<< "$1" && [ -z ${PROJECT} ] && shift && PROJECT=$1
      ;;
    --client-id*)
      IFS="=" read _cmd CLIENT_ID <<< "$1" && [ -z ${CLIENT_ID} ] && shift && CLIENT_ID=$1
      ;;
    --client-secret*)
      IFS="=" read _cmd CLIENT_SECRET <<< "$1" && [ -z ${CLIENT_SECRET} ] && shift && CLIENT_SECRET=$1
      ;;
    *)
      usage
      echo ""
      echo "Unknown parameter $1."
      exit
  esac
  shift
done

if [ -z ${CLIENT_ID} ] || [ -z ${CLIENT_SECRET} ] || [ -z ${PROJECT} ]; then
  echo You must supply CLIENT_ID and CLIENT_SECRET.
  exit
fi

gcloud --project ${PROJECT} secrets create client_id --replication-policy=automatic 2>/dev/null
echo "{ \"client_id\": \"${CLIENT_ID}\" }" | gcloud --project ${PROJECT} secrets versions add client_id --data-file=-

gcloud --project ${PROJECT} secrets create client_secret --replication-policy=automatic 2>/dev/null
echo "{ \"client_id\": \"${CLIENT_SECRET}\" }" | gcloud --project ${PROJECT} secrets versions add client_secret --data-file=-

The library will create any further secrets and versions automatically. It will also remove all but the latest secret each time an update occurs. This reduces the usage cost of Secret Manager substantially as projects are charged based partially on number of active (ie not destroyed) secret versions.

Firestore

Firestore requires no additional configuration.

Google Cloud Storage

To use Google Cloud Storage you must have a bucket created in which the user token files and project secrets are to be stored and to which the app's service account has read/write access. This should then be locked down so that no other non-administrators have access.

Local files

No special configuration is required. This implementation is HIGHLY insecure, and is provided simply for testing/development purposes.

Examples

Fetching a token from storage

from auth.credentials_helpers import encode_key
from auth.secret_manager import SecretManager

manager = SecretManager(project='<gcp project name>')
key = manager.get_document(encode_key('<token id>'))

Note the use of encode_key. This is because many of the storage systems supported do not allow special characters, and the most convenient identifier for most OAuth tokens is the email address of the user. encode_key is a base64 encoder - and no decoding is necessary.

The example given uses Secret Manager (part of Google Cloud). To use (say) GCS, the code would change like this:

from auth.credentials_helpers import encode_key
from auth.gcs_datastore import GCSDatastore

manager = GCSDatastore(project='<gcp project name>', bucket='<gcs bucket>')
key = manager.get_document(encode_key('<token id>'))

All that changes is where the datastore is!

Storing a token

Secret Manager

from auth.secret_manager import SecretManager
manager = SecretManager(project='<gcp project name>')

manager.update_document(id=encode_key('<token_id>'), new_data=<token string>)

This will implicitly create a secret if there was not one already, or simply update an existing secret with a new 'live' version of the secret.

Removing a secret

from auth.secret_manager import SecretManager
manager = SecretManager(project='<gcp project name>')

manager.delete_document(id=encode_key('<token_id>'))

Listing all the available secrets

from auth.secret_manager import SecretManager
manager = SecretManager(project='<gcp project name>')

manager.list_documents()