Azure AI Content Safety (Prompt Shields) vs Guardrails AI

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.

Guardrails AI

Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library.

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

Guardrails AI

1. Pin guardrails-ai==0.11.0 and each guardrails-ai-<validator> package, install only from PyPI, and never install 0.10.1
2. Import validators from guardrails_ai.<name>, not guardrails.hub, and don't run guardrails hub install
3. Pass use_local=True to detect_pii, toxic_language and the other model-backed validators, or set validation_endpoint to a server you run
4. Set enable_metrics to false in ~/.guardrailsrc if you don't want usage metrics sent
5. Avoid building on reask and RAIL. The open 1.0.0 issues plan to remove both