- Make it easier to rotate `SECRET_KEY` by documenting this usage
for both sensitivity and rotation process. (ARCHBOM-1676).
- Just use a hash of the secret rather than HMAC + MD5. We're not
authenticating a message, so HMAC isn't really needed -- it just needs
to be unique, deterministic, and irreversible. SHAKE allows generation
of an arbitrary length hash without needing to truncate.
Also, rename tracking session ID generator for clarity -- there's no
encryption happening here.
Add additional test for existing claim of uniqueness.
* import task decorator from celery APP instance instead of celery package in CMS
* replaced task decorator with shared_task in cms and common
* Fixed import of shared_task
* Fixed import
These changes were initially made to make it easier to do SECRET_KEY rotations. Along the way, we found it made sense to refractor the code as well.
Changes made:
- changed get_to_create to create because now the code should only get to this block when a write is necessary
- added a lookup for anonymous_user_id. This is to return an existing anonymous_user_id rather than calculating. This will mitigate the results of SECRET_KEY rotation.
- Added monitoring to help us make better decisions: should we not sue SECRET_KEY, performance considerations...
- put old function behind toggle in case something goes wrong in production with new code
- refractoring function structure for better understanding
This annotation was causing a linting failure, and a TypeError down the road in
the feature toggle report processing step by
edx-toggles/scripts/feature_toggle_report.py.
Add an ADR about secret key usage.
Don't use secret keys for use cases which would result in breakage upon
rotation and which might slow down the act of rotation.
On a platform that is configured to upload video transcripts to S3
(`DEFAULT_FILE_STORAGE = "storages.backends.s3boto3.S3Boto3Storage"`),
uploads from the studio fail with a TypeError: "Unicode-objects must be
encoded before hashing"
A full stacktrace of the issue can be found here:
https://sentry.overhang.io/share/issue/2249b6f67d794c7e986cc288758f4ebe/
This error is triggered by md5 hashing in the botocore library, which
itself is used by the S3Boto3Storage storage class. This error does not
occur with filesystem-based uploads because it does not perform checksum
verification. The reason why this error would not occur on edx.org is
unknown. Similar issues were already fixed from edxval.
To address this issue, we encode the transcript file content prior to
sending it to s3.
We upgrade edx-lint to use the latest feature toggle and annotation custom
linter. Note that we do not yet make use of code annotation linting, typically
run with `code_annotations --lint ...`.
Note that we also fix new linting errors detected by the new checkers.
