Azure AI Content Safety (Prompt Shields) vs Google Cloud Model Armor

Azure AI Content Safety (Prompt Shields)

Prompt Shields checks up to five retrieved documents for indirect injection, not only the user prompt. Needs an Azure subscription with a card, a resource and a region that has the feature, before the first call.

Google Cloud Model Armor

2 million free tokens a month, then $0.10 per million. OAuth only, and a template must exist in the same location as the endpoint before the first call.

Azure AI Content Safety (Prompt Shields)

1. Send retrieved pages and tool results in the documents array of shieldPrompt, not in userPrompt, so document attacks are reported separately
2. Call text:shieldPrompt over REST with api-version=2024-09-01. The Python SDK 1.0.0 has no method for it
3. Keep each request under 10,000 characters across prompt and documents, and split long tool results
4. Create the resource in a region that lists Prompt Shields, since not every region has it
5. On F0 you get 5 requests a second. Queue checks or move to S0 before load testing

Google Cloud Model Armor

1. Create one template per location you call from. A template in us-central1 doesn't answer on the europe-west2 endpoint
2. Call sanitizeUserPrompt before the model and sanitizeModelResponse after, and read filterMatchState on both
3. Treat EXECUTION_SKIPPED as unchecked, not clean. It means the input went over the filter's 65,536-token cap
4. Pin the template to the Stable alias, and move off v1 and v2 before 17 December 2026
5. Retry 500, 502, 503 and 504 with truncated exponential backoff, and keep fan-out under the 1,200 queries a minute shared by the project