Google Policy Simulator API

Name: Policy Simulator API
Brand: Google Cloud Policy Simulator API
Availability: InStock

✓ Official Vendor SpecSecurityComplianceoauth23 EndpointsREST

Install Jentic One Beta

Connect the Policy Simulator API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Policy Simulator API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Policy Simulator API.

Create a Replay under an organisation, folder, or project to model a candidate IAM policy change

Fetch the status and metadata of an in-flight or completed Replay

List per-access ReplayResults showing decision differences between baseline and proposed policies

GET STARTED

Start building with Policy Simulator API

Explore with Jentic

View OpenAPI Document

For Agents

Simulate proposed IAM policy changes by replaying past access requests and comparing decisions before applying the change.

Use for: Simulate a Cloud IAM policy change before applying it, Create a Replay to test removing a role binding, List per-access decisions for a Policy Simulator Replay, Check whether tightening a custom role would break production access

Not supported: Does not modify IAM policies, query historical activity, or troubleshoot a single live access denial - use only to create and read IAM Replays.

Use Cases

Patterns agents use Policy Simulator API for, with concrete tasks.

★ Pre-Change IAM Validation

Before a platform team removes an over-broad role binding, they create a Replay against the proposed policy to confirm no real access was relying on the removed permissions. The Replay reads recent access logs under the parent, evaluates each request twice, and lists differences. Teams skip the change if differences include traffic from production identities and proceed if the diff is empty.

POST /v1/{parent}/replays with body containing the proposed policy override, then GET /v1/{name} until state=SUCCEEDED, then GET /v1/{parent}/results and report any AccessTuples whose decision flipped from ALLOW to DENY.

Bulk Custom Role Tightening

Security engineers tightening a custom role across a large organisation use Replay to evaluate the proposed changes against thousands of past access requests in one batch. Per-access ReplayResults pinpoint every identity, resource, and permission whose decision would change, letting the team build a targeted exception list before they roll out the new role definition.

Create a Replay with the tightened custom role, list ReplayResults filtered to decision=DIFFERENT, and aggregate by principal and resource to produce an exception list.

Audit Evidence for IAM Changes

Compliance programmes require evidence that proposed IAM changes were assessed before they were applied. By creating a Replay per change request and attaching the Replay name and ReplayResults summary to the change ticket, teams produce automated evidence that satisfies SOC 2 and ISO 27001 control objectives without manual screenshots.

On every IAM change request, POST /v1/{parent}/replays with the proposed delta, attach the returned Replay name to the change ticket, and store the SUCCEEDED status as audit evidence.

AI Agent Policy Modelling via Jentic

Cloud security agents that propose IAM cleanups can call Policy Simulator through Jentic to validate every proposed change before they emit a write. Jentic stores the cloud audit credentials in its vault and exposes the replays.create, replays.get, and results.list operations as three search-load-execute calls so the agent can model, poll, and read results in a single short flow.

Search Jentic for 'simulate a Google Cloud IAM policy change', load the replays.create schema, execute it with the proposed policy, then poll replays.get and list results once succeeded.

Key Endpoints

3 endpoints — the google cloud policy simulator api lets administrators model the impact of a proposed iam policy change before they apply it.

METHOD

PATH

DESCRIPTION

GET

/v1/{name}

Get a single Replay by name with status and metadata

POST

/v1/{parent}/replays

Create a Replay under an organisation, folder, or project

GET

/v1/{parent}/results

List ReplayResults for a completed Replay

GET

/v1/{name}

Get a single Replay by name with status and metadata

POST

/v1/{parent}/replays

Create a Replay under an organisation, folder, or project

GET

/v1/{parent}/results

List ReplayResults for a completed Replay

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your Google Cloud service-account credential for the Policy Simulator API is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'simulate a Google Cloud IAM policy change', and Jentic returns the matching replays create, get, or results list operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

Time to first call

FAQs

Specific to using Policy Simulator API through Jentic.

What authentication does the Policy Simulator API use?

It uses OAuth 2.0 with the https://www.googleapis.com/auth/cloud-platform scope and is typically called with a service account that has org- or folder-level IAM audit permissions. Through Jentic the credential is held encrypted in your Jentic One instance and a scoped access token is injected at call time.

Can I check whether removing a role binding will break access?

Yes. POST /v1/{parent}/replays with the proposed policy override creates a Replay that re-evaluates recent access requests against the candidate policy. GET /v1/{parent}/results then lists every request whose decision changed, so removed bindings that production traffic actually depended on surface as ALLOW-to-DENY flips.

What are the rate limits for this API?

The API enforces standard Google Cloud project quotas measured in queries per minute. Replays are asynchronous - the create call returns quickly and the heavy work is done server-side, so the practical bottleneck is usually the time the Replay itself takes rather than QPS.

How do I simulate an IAM change through Jentic?

Run jentic search 'simulate a Google Cloud IAM policy change', load the schema for POST /v1/{parent}/replays, execute it with the proposed policy override, then call /v1/{name} to poll status and /v1/{parent}/results to read the per-access decisions.

Is the Policy Simulator API free?

There is no per-call charge for creating Replays or reading results. Standard Google Cloud project quotas apply, and Replay execution time depends on the volume of access logs under the chosen parent.

Can I run a Replay across an entire organisation at once?

Yes. The {parent} path parameter accepts organizations/{org}/locations/{loc}, folders/{folder}/locations/{loc}, or projects/{project}/locations/{loc}. Org-level Replays cover all access logs under the organisation, but they take longer and consume more quota than narrower scopes.

Can I limit what my agent is allowed to do with the Policy Simulator API?

Yes. Because Jentic One is self-hosted, you set the rules that decide which operations and credentials your agent may use, and the Policy Simulator API puts the replay resource in the URL path (/v1/{parent}/replays and /v1/{name}), so you can pin the agent to a single organisation, folder, or project parent. You can allow only the create-Replay and list-ReplayResults calls, meaning the agent can model a candidate policy and read the decision diffs there and nothing else. None of these operations mutate a live IAM policy, so a scoped agent can validate proposed changes without ever altering production access.