What you are evaluating
Scope this entry to the AI Guardrails input/output service. Broader Check Point AI Agent Runtime Security and workforce controls require their own integration review. The privacy sheet distinguishes hosted processing from a self-hosted deployment.
A useful evaluation context
Developers can assess content inspection at their application boundary while keeping credential and tool authorization separate.
Documented capabilities
The vendor describes these capabilities in the linked sources. Availability depends on the product edition and supported environment.
- Submitted model inputs and outputs can be inspected for prompt attacks and sensitive-data exposure.
- The service supplies structured detection and policy information for application integration.
- The documented self-hosted option changes the data-processing boundary from the hosted service.
Where it fits in the work
- Map which prompt, retrieval and response fields leave the application for inspection.
- Send benign cases and a synthetic secret through the same integration path.
- Verify the application enforces the returned decision and inspect the configured retention behavior.
APPLY THE IDEA / ILLUSTRATIVE EXERCISE
Make the outcome observable.
A test assistant reads an instruction-bearing document alongside a synthetic customer identifier.
Evidence to look for
The result distinguishes the detected policy condition, the enforced application action and the content recorded in service logs.
Use synthetic data and an authorized test environment. Agree the scope and recovery steps before enabling enforcement.
Questions for your evaluation
- Which content is retained, in which region and for how long?
- What does application code do when the inspection service is unavailable?
- Which advertised agent-action controls are included in this exact offering?
Names you may encounter: Lakera Guard. Historical names do not establish current availability or feature equivalence.