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Assuredworkloads Environment Assessor

GoogleOfficialPublished by Google

  • Skill
  • Research and analysis
  • Security
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Discover Google Cloud resource telemetry and effective Org Policies, evaluate brownfield workloads against sovereign data boundary and compliance standards (EU Data Boundary with Support, FedRAMP Moderate/High, DoD IL4/IL5, ITAR, CJIS, US/EU Regional Data Boundaries), and recommend the optimal Assured Workloads Framework. Use when asked to: "assess my environment for compliance", "which Assured Workloads framework should I use?", "check if my folder is ready for EU sovereignty", "evaluate compliance posture for folders/123 or projects/xyz", or "discover compliance gaps before deployment". Do NOT use for live mutating policy deployments, generating deep audit reports via Cloud Audit Manager, generating remediation scripts, or authoring custom Assured Workloads frameworks.
— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Assured Workloads Environment Assessor is a read-only tool designed to evaluate existing Google Cloud folders and projects against various compliance standards. It performs non-mutating discovery of resource telemetry and effective organization policies to determine how well a workload aligns with specific Assured Workloads frameworks. The tool provides a quantitative scorecard and actionable recommendations for transitioning workloads into Monitoring or Preventive modes, helping users identify potential compliance gaps without altering their current infrastructure.

What it does

  • Discovers resource telemetry and effective organization policies across folders and projects.
  • Evaluates brownfield workloads against sovereign data boundaries and compliance standards.
  • Recommends the most suitable Assured Workloads framework based on active resource footprints.
  • Provides a quantitative scorecard assessing location residency, service usage, and CMEK readiness.
  • Generates an executive assessment report using the Minto Pyramid Principle.
  • Identifies potential compliance drift indicators without performing live policy mutations.

When to use it

  • When you need to assess an existing environment for compliance readiness.
  • When you are unsure which Assured Workloads framework is appropriate for your specific regulatory needs.
  • When you want to discover compliance gaps before deploying new workloads.
  • When you need to check if a folder is prepared for specific sovereignty requirements like EU data boundaries.

Advantages

  • Zero-risk, non-mutating assessment that does not alter existing organization policies.
  • Provides clear, data-driven recommendations for framework selection.
  • Supports continuous observability through Monitoring (Detective) mode.
  • Helps avoid production outages by identifying readiness gaps before enforcing preventive controls.
  • Zero-cost assessment using standard read-only Google Cloud APIs.

Usage examples

“Assess my environment for compliance in folders/123.”
The agent will scan the folder, analyze effective policies, and provide a report on compliance posture and recommended frameworks.
“Which Assured Workloads framework should I use for my project in us-central1?”
The agent will evaluate the project's resource footprint and suggest frameworks like FedRAMP or US Data Boundary based on the region and service usage.
“Check if my folder is ready for EU sovereignty.”
The agent will analyze the folder's current resource locations and policies to determine alignment with EU Data Boundary frameworks.
“Discover compliance gaps for projects/xyz before deployment.”
The agent will perform a pre-flight check against relevant controls and highlight potential drift indicators that should be addressed.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google/assuredworkloads-environment-assessor/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip assuredworkloads-environment-assessor.zip -d .agents/skills

Documentation by Google

Compliance Environment Assessor Skill

This skill performs zero-risk, non-mutating compliance discovery, physical telemetry profiling, and data boundary framework recommendation across Google Cloud Folders (folders/{folder_id}) and Projects (projects/{project_id}).

Usage Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read and follow the instructions in Usage Attribution.

Safety & Execution Tier (CRITICAL)

  • Tier R (Strictly Read-Only): All discovery operations execute read-only queries (gcloud asset search-all-resources, gcloud compliance-manager frameworks list, gcloud compliance-manager cloud-controls describe, and gcloud org-policies describe --effective). You MUST NEVER execute mutating commands (gcloud compliance-manager framework-deployments create, gcloud org-policies set-policy, or gcloud resource-manager ...).


Grounding Guardrails: Google Cloud & Assured Workloads Precedence (CRITICAL)

To prevent hallucinations, incorrect compliance assessments, and false blockers derived from generic LLM pre-training, the agent is governed by strict Grounding Guardrails:

  1. Strict Prohibition on Generic LLM Pre-Training Priors:

    • You MUST NOT derive compliance rules, API semantics, or deployment constraints from generic web pre-training (e.g., generic NIST/FedRAMP certification audit checklists, AWS/Azure architectures, or legacy on-prem IT auditor mindsets).

    • In traditional IT audits, non-compliance is a binary go/no-go gate that blocks deployment. In Google Cloud Assured Workloads, deploying in Monitoring (Detective) mode enables detective controls without mutating existing Organization Policies, allowing continuous observability without halting Day 0 rollout. You MUST NOT confuse these paradigms.

  2. Authoritative Assured Workloads Scope & Deployment Grounding:

    • Assured Workloads binds compliance frameworks directly to existing or new Google Cloud folders (folders/...) and projects (projects/...).

    • Existing Workloads (Folders or Projects): Recommend deploying in Monitoring (Detective) mode first to assess and remediate findings safely without mutating existing Organization Policies, and then transitioning to Preventive mode.

    • New Workloads (Folders or Projects): Recommend starting in Preventive mode or Monitoring (Detective) mode.

    • Google Cloud Console Deployment: Always guide the user to deploy the recommended framework via the Assured Workloads Frameworks tab in Google Cloud Console (https://console.cloud.google.com/compliance/configure/frameworks?organizationId=ORGANIZATION_ID). Do NOT recommend gcloud assured workloads create (which only provisions new greenfield folders using legacy regime enums and cannot bind frameworks to existing folders or projects).

  3. Client-Side Org Policy Readiness vs. Server-Side CES Boundary:

    • Client-Side Scope: Pre-flight evaluation via scripts/evaluate_control_rules.py assesses ONLY the 3 high-confidence Organization Policy parameter sets bound in Framework.cloudControlDetails[].parameters:

      1. Resource Locations (builtin-restrict-resource-locations / constraints/gcp.resourceLocations)

      2. Service Usage Restrictions / SUR (builtin-enforce-service-usage-restrictions / constraints/gcp.restrictServiceUsage)

      3. CMEK Encryption Requirements (builtin-require-cmek / constraints/gcp.restrictNonCmekServices)

    • Server-Side CES Scope: Complex Continuous Evaluation Service (ces_rule) and REST API rules (rest_api_measurement) are evaluated server-side by the Continuous Evaluation Service (CES) after the framework is deployed.

    • Terminology Invariant: You MUST frame client-side findings as Pre-Flight Org Policy Readiness Recommendations / Potential Drift Indicators (orgPolicyDriftIndicators), NEVER as definitive compliance "violations" or "deployment blockers" that could contradict an actual post-deployment CES run.

  4. Static Built-In Catalog, Session Caching, Support Routing & KAJ Flow:

    • Built-in Frameworks (type: BUILT_IN) returned by gcloud compliance-manager frameworks list are static configurations uniform across organizations. Fetch frameworks.json once per session and reuse the cached file across all candidate evaluations and follow-up queries.

    • Personnel Support Model: Determine whether a framework requires a Paid Sovereign/Regulated Support Subscription or uses Standard Commercial Support ($0 support uplift) from the framework's public displayName and description in frameworks.json:

      • Paid Sovereign/Regulated Support Subscription: Frameworks whose description specifies support personnel access controls (e.g., "Support access controls are set to ...", -and-support variants such as builtin-eu-data-boundary-and-support and builtin-us-data-boundary-and-support, or regulated standards such as builtin-il4, builtin-il5, builtin-itar, builtin-fedramp-high, builtin-cjis).

      • Standard Commercial Support ($0 support uplift): Regional-only Data Boundary frameworks whose description sets data location controls only without a support access controls clause (e.g., builtin-us-data-boundary, builtin-eu-data-boundary, builtin-uk-data-boundary, builtin-japan-data-boundary).

      • Important: Do NOT use the mere presence of builtin-restrict-technical-support-services in cloudControlDetails as a discriminator, because both regional-only and paid-support Data Boundary frameworks include that control.

    • Key Access Justifications (KAJ) & EKM: Recommend -with-access-justifications framework variants only when the customer explicitly requests KAJ/EKM, or when disambiguating between matching regional variants in frameworks.json.

  5. Deterministic Tool Gating:

    • You MUST NOT guess compatibility scores ($$S_{\text{composite}}$$) or resource inventories.

    • You MUST execute scripts/evaluate_control_rules.py with --frameworks-file=frameworks.json.

Prerequisites

Before executing environment assessment, ensure your local or Cloud Shell environment meets the following prerequisites:

  1. Google Cloud SDK:

  2. Project Setup & Target Selection:

    • Select or configure an administrative project for running assessment queries:

      gcloud config set project PROJECT_ID
  3. Region Configuration & Availability:

    • Configure a well-supported default region (e.g. us-central1):

      gcloud config set compute/region us-central1
    • Consult official region availability documentation: Google Cloud Locations.

  4. Required API Enablement:

    • Enable the required Google Cloud APIs on the administrative project:

      gcloud services enable \
        cloudasset.googleapis.com \
        orgpolicy.googleapis.com \
        assuredworkloads.googleapis.com \
        cloudsecuritycompliance.googleapis.com
  5. Authentication Setup:

    • Authenticate your user or service account identity and establish application default credentials:

      gcloud auth login
      gcloud auth application-default login
  6. Billing & Quota Project Setup (Zero Billing Impact):

    • Zero-Cost Assessment Guarantee: Running this assessment incurs $0 in Google Cloud infrastructure and API billing charges. All discovery operations (gcloud asset search-all-resources, gcloud compliance-manager frameworks list, and gcloud org-policies describe --effective) are free read-only metadata queries.

    • Quota Project Requirement: Google Cloud Service Infrastructure requires an administrative project with an active Cloud Billing account attached to allocate API rate limits and meter service usage (sent via the X-Goog-User-Project header), even for free APIs.

    • Pre-Flight Verification:

      # 1. Verify active Cloud Billing account is attached to administrative project
      gcloud billing projects describe PROJECT_ID --format="value(billingEnabled)"
      
      # 2. If using a shared project, ensure your user identity has permission to consume project quota
      gcloud projects add-iam-policy-binding PROJECT_ID \
        --member="user:USER_EMAIL" \
        --role="roles/serviceusage.serviceUsageConsumer"
      
      # 3. Synchronize Application Default Credentials quota project
      gcloud auth application-default set-quota-project PROJECT_ID
  7. Commands & Payloads Reference:


Step-by-Step Operating Workflow

Step 1: Ingest Scope & Resolve Organization ID
  1. Accept or prompt for the target scope (folders/{folder_id} or projects/{project_id}). If the user provides an open-ended scope without stating a regulatory regime, DO NOT block on broad questionnaires. Proceed immediately to ingest telemetry.

  2. Automatically resolve the parent Organization ID from the scope to drive downstream catalog queries:

    • For Folders:

      gcloud resource-manager folders describe FOLDER_ID --format="value(parent)"

      (If the parent is another folder, traverse up ancestors until organizations/{org_id} is found)

    • For Projects:

      gcloud projects get-ancestors PROJECT_ID --format="value(id,type)"
Step 2: Ingest Asset Telemetry & Effective Org Policies via Two-Pass Telescoping Protocol

To guarantee 100% coverage across the scope hierarchy while keeping payloads compact, telemetry ingestion executes in two telescoping passes (see Google Cloud CLI Commands Reference):

  1. Pass 1: Macro Footprint & API Enumeration (100% Scope Coverage):

    gcloud asset search-all-resources \
      --scope="folders/FOLDER_ID" \
      --page-size=500 \
      --format="json(name,assetType,location)" > macro_telemetry.json
    • Pagination & Scope Semantics: --page-size=500 fetches 500 cloud assets per HTTP API page (the maximum batch size permitted by Cloud Asset Inventory), automatically paginating through all assets strictly inside folders/FOLDER_ID and its descendant projects.

    • Full Location & SUR Coverage: macro_telemetry.json captures 100% of active location and assetType values required to evaluate both builtin-restrict-resource-locations (allowedLocations) and builtin-enforce-service-usage-restrictions (allowedServices / SUR).

    • If PERMISSION_DENIED is returned:

      • If the error states USER_PROJECT_DENIED or references roles/serviceusage.serviceUsageConsumer, the error is on the administrative quota project (it lacks an attached billing account or caller lacks serviceUsageConsumer). Follow the Quota Project Recovery playbook and stop running further commands.

      • If the error references the target scope (folders/... or projects/...), HALT ALL TOOL CALLS IMMEDIATELY (do not run Step 2.2, Step 3, or any further commands) and inform the user they require roles/cloudasset.viewer and roles/orgpolicy.policyViewer on that scope.

    • If 0 resources are returned, inform the user the target scope is empty.

  2. Inspect Effective Universal Org Policies on Scope (38/38 Frameworks):

    gcloud org-policies describe gcp.resourceLocations \
      --folder=FOLDER_ID \
      --effective \
      --format="json(name,spec.rules)" > effective_locations.json
    
    gcloud org-policies describe gcp.restrictServiceUsage \
      --folder=FOLDER_ID \
      --effective \
      --format="json(name,spec.rules)" > effective_services.json
    
    gcloud org-policies describe gcp.restrictTLSVersion \
      --folder=FOLDER_ID \
      --effective \
      --format="json(name,spec.rules)" > effective_tls.json
Step 3: Fetch & Cache Built-In Framework Catalog and Filter by Location + SUR
  1. Fetch & Cache Built-In Framework Catalog (with Bound Parameters):

    if [ ! -s frameworks.json ]; then
      gcloud compliance-manager frameworks list \
        --organization=ORGANIZATION_ID \
        --location=global \
        --filter="category:ASSURED_WORKLOADS" \
        --format="json(name,majorRevisionId,displayName,description,category,cloudControlDetails)" > frameworks.json
    fi
    • Session Caching: Because built-in ASSURED_WORKLOADS frameworks are static definitions uniform across organizations, cache the output in frameworks.json and reuse it for all candidate evaluations and follow-up questions.

  2. Filter Candidates by Location + SUR Footprint & Clarify Intent:

    • Exclude location-less control-plane management metadata (cloudresourcemanager.googleapis.com/*, orgpolicy.googleapis.com/*, cloudasset.googleapis.com/*, accesscontextmanager.googleapis.com/*, and location: "global" hierarchy nodes) from data-plane location checks.

    • Match active data-plane regions (location) and active service prefixes (assetType) from macro_telemetry.json against each framework's builtin-restrict-resource-locations (allowedLocations) and builtin-enforce-service-usage-restrictions (allowedServices / SUR) parameters in frameworks.json:

      • US-Only Regions (us-central1, us-east4): Candidates include DoD IL5 (builtin-il5, adjudicated support), ITAR (builtin-itar, US persons support), FedRAMP High/Moderate, or US Regional Data Boundary (builtin-us-data-boundary, standard commercial support).

      • EU-Only Regions (europe-west3, europe-west1): Candidates include EU Data Boundary and Support (builtin-eu-data-boundary-and-support) vs. standard EU Regional Boundary (builtin-eu-data-boundary).

    • Targeted Disambiguation:

      • If multiple frameworks match the physical footprint and user regulatory intent is unstated (e.g., an open-ended request with no regime specified), DO NOT finalize a single primary recommendation yet — present the matching candidate frameworks and STOP to ask the user a targeted clarifying question about their regulatory intent (e.g., EU Sovereignty, US FedRAMP/IL5) and personnel support model (Standard Commercial Support vs. Paid Sovereign/Regulated Support).

      • Recommend -with-access-justifications (KAJ/EKM) framework variants only if the customer explicitly asks for KAJ/EKM or when disambiguating between matching regional variants.

      • Out-of-Scope / Non-Catalog Compliance Standards (e.g., CMMC, UK GDPR): If the user asks to evaluate a compliance standard or legal certification that is not present as a built-in ASSURED_WORKLOADS framework in frameworks.json (such as CMMC, UK GDPR, SOC 2, or PCI-DSS), DO NOT fabricate or pass non-existent framework IDs (e.g., builtin-cmmc or builtin-uk-gdpr) to evaluate_control_rules.py. Explicitly state that the requested standard is not a standalone Assured Workloads Data Boundary framework, explain the catalog scope boundary (Data Boundary enforces regional data residency, SUR, CMEK, and sovereign support routing rather than legal privacy or third-party certification audits), and offer the closest adjacent ASSURED_WORKLOADS frameworks from frameworks.json that match their active regional footprint (e.g., builtin-il5 or builtin-fedramp-high for US defense/CUI workloads, or builtin-eu-data-boundary-and-support / builtin-eu-data-boundary / builtin-uk-data-boundary for European/UK regional residency).

Step 4: Conditional Pass 2 CMEK Ingestion & Org Policy Evaluation
  1. Pass 2: Conditional Targeted Deep Ingestion for CMEK Resource Types: Derive TARGET_TYPES (the intersection of active CAI assetTypes in macro_telemetry.json and CMEK-governed services in builtin-require-cmek from frameworks.json). Only 6 of the 38 Data Boundary frameworks include builtin-require-cmek; if TARGET_TYPES is non-empty, fetch kmsKeys:

    TARGET_TYPES=$(python3 scripts/evaluate_control_rules.py \
      --get-target-asset-types \
      --framework=FRAMEWORK_ID \
      --telemetry-file=macro_telemetry.json \
      --frameworks-file=frameworks.json)
    
    if [ -n "${TARGET_TYPES}" ]; then
      gcloud asset search-all-resources \
        --scope="folders/FOLDER_ID" \
        --asset-types="${TARGET_TYPES}" \
        --page-size=500 \
        --format="json(name,assetType,location,kmsKeys)" > deep_telemetry.json
    fi
  2. Execute High-Confidence Org Policy Evaluator: Run scripts/evaluate_control_rules.py over macro_telemetry.json (and optional deep_telemetry.json) with frameworks.json to compute the 3 quantitative scores (locationScore, serviceScore, cmekScore, compositeScore) and orgPolicyDriftIndicators (when cmekRequired is false, always display the CMEK Readiness column as N/A in the scorecard):

    python3 scripts/evaluate_control_rules.py \
      --telemetry-file=macro_telemetry.json \
      --deep-telemetry-file=deep_telemetry.json \
      --framework=FRAMEWORK_ID \
      --frameworks-file=frameworks.json
  3. Evaluate Operational & Governance Impact:

    • Review cloudControlDetails in frameworks.json for parameterized and operational controls (builtin-restrict-kms-protection-levels, builtin-enforce-allowed-cmek-crypto-key-projects, builtin-restrict-cloud-function-generations, builtin-restrict-cloudstorage-auth-types, builtin-iam-disable-service-account-key-creation, builtin-disable-ssh-in-browser, builtin-enable-axt, and *-regulatory-settings controls like builtin-cloud-logging-regulatory-settings) and summarize their workflow impact in the final report.

Step 5: Render Executive Assessment Report (Minto Pyramid Structure)

Present an executive report structured around the Minto Pyramid Principle (Bottom Line Up Front -> Core Value Pillars -> Supporting Evidence -> Action Plan):

# Compliance Environment Assessment Report: [Scope URI]

## 1. Executive Conclusion & Recommendation (Bottom Line Up Front)
* **Primary Recommendation**: [Framework Name] (`organizations/{org_id}/locations/global/frameworks/{framework_id}`)
* **Org Policy Readiness Alignment**: [Composite Fit %]
* **Recommended Deployment Mode**:
  * **Existing Workloads (Folders or Projects)**: Deploy in **Monitoring (`Detective`) mode** first, then transition to **Preventive** mode after remediating findings.
  * **New Workloads (Folders or Projects)**: Start in **Preventive** mode or **Monitoring (`Detective`) mode**.
  * **Zero Production Outage Risk**: Monitoring (`Detective`) mode mutates zero Organization Policies on Day 0.
  * **Continuous Server-Side CES Observability**: Activates real-time Continuous Evaluation Service (CES) monitoring across all framework controls.
  * **No Migration Required**: Protects existing folders and projects in-place without migrating resources.

---

## 2. Core Value Drivers: Why Assured Workloads Fits This Scope
1. **Residency & Boundary Alignment (`gcp.resourceLocations`)**: Active regional workloads are evaluated against allowed regions ([e.g. 100% US-contained]).
2. **Service & API Compatibility (`gcp.restrictServiceUsage` / SUR)**: Active service APIs are evaluated against accredited service allowlists ([e.g. 100% approved services]).
3. **Non-Disruptive Posture Hardening**: Enrolling existing workloads in Monitoring (`Detective`) mode provides server-side CES posture evaluation while allowing your team to triage Org Policy readiness safely before moving to Preventive mode.

---

## 3. Objective Assessment Scorecard & Org Policy Readiness Triage

### Quantitative Org Policy Readiness Scorecard
| Candidate Framework | Location Residency (`locationScore`) | Service Usage / SUR (`serviceScore`) | CMEK Readiness (`cmekScore`) | Composite Alignment | Personnel Support Model |
| :--- | :--- | :--- | :--- | :--- | :--- |
| **[Framework 1]** | [XX%] | [XX%] | [XX% or N/A] | **[XX%]** | [Support Model] |
| **[Framework 2]** | [XX%] | [XX%] | [XX% or N/A] | **[XX%]** | [Support Model] |

### Active Resource & Effective Org Policy Baseline
* **Discovered Inventory**: [Total Assets count] across [Active resource types and regions].
* **Effective Org Policy Baseline**: [Effective `gcp.resourceLocations`, `gcp.restrictServiceUsage`, and `gcp.restrictTLSVersion` posture].

### Pre-Flight Org Policy Readiness Recommendations (Prior to Preventive Mode)
*Pre-flight drift indicators do NOT block Day 0 deployment in Monitoring (`Detective`) mode. Address these prior to enabling Preventive policy enforcement (authoritative CES and REST control evaluations run server-side after deployment):*
* **[Priority 1]**: [e.g. Configure CMEK keys on unencrypted resources before toggling `builtin-require-cmek` to `PREVENTIVE`].
* **[Priority 2]**: [e.g. Operational impact of bound controls such as `builtin-restrict-kms-protection-levels` or `builtin-cloud-logging-regulatory-settings`].

---

## 4. Deployment Action Plan & Commercial Advisory

### Deploy via Google Cloud Console — Assured Workloads Frameworks Tab (Recommended)
Review and deploy the recommended framework directly in the Google Cloud Console **Assured Workloads -> Frameworks** tab:
👉 **[Open Assured Workloads Frameworks Console](https://console.cloud.google.com/compliance/configure/frameworks?organizationId=ORGANIZATION_ID)**
* **Existing Workloads (Folders or Projects)**: Deploy in **Monitoring (`Detective`) mode** to evaluate posture and remediate findings with zero Day 0 Organization Policy mutations, then transition to **Preventive** mode.
* **New Workloads (Folders or Projects)**: Start directly in **Preventive** mode or in **Monitoring (`Detective`) mode**.

### Commercial & Licensing Advisory
* Assured Workloads compliance regimes may carry support routing or licensing entitlements depending on whether the framework enforces regional data location controls only (standard commercial support, $0 support uplift) or specifies support personnel access controls in its `displayName` and `description` (paid sovereign/regulated support).
* Review full pricing details and entitlement tiers at: https://cloud.google.com/assured-workloads/pricing
Step 6: Handling Customer Follow-Up Questions on Specific Services

When a customer follows up with a specific question about how a recommended or candidate framework affects a particular Google Cloud service (e.g., Cloud Run, Cloud Storage, Spanner, GKE, Cloud SQL, Vertex AI, Cloud Logging):

  1. Inspect Cached frameworks.json Locally (or Fetch via Step 3 frameworks list if Not Cached):

    • If frameworks.json is not yet present in the current working directory, run the Step 3 gcloud compliance-manager frameworks list command first to populate frameworks.json.

    • Check whether <service>.googleapis.com is permitted in builtin-enforce-service-usage-restrictions (allowedServices) and whether CMEK is required in builtin-require-cmek (services).

    • Identify all service-specific cloudControlDetails[].name entries bound in that framework (e.g., builtin-run-disable-ephemeral-disk, builtin-restrict-cloudstorage-auth-types, builtin-disable-spanner-multi-region, builtin-cloud-logging-regulatory-settings) and any bound parameters.

  2. Fetch Authoritative Control Details On Demand:

    • Because Framework.cloudControlDetails omits control descriptions, enforcement modes, and remediation steps, run cloud-controls describe for the relevant control ID(s):

      gcloud compliance-manager cloud-controls describe CONTROL_ID \
        --organization=ORGANIZATION_ID \
        --location=global \
        --format="json(name,displayName,description,supportedEnforcementModes,remediationSteps,parameterSpec)"
    • Extract the exact underlying Organization Policy constraint (e.g., run.managed.disableEphemeralDisk, storage.restrictAuthTypes), supportedEnforcementModes (PREVENTIVE vs. DETECTIVE), and remediationSteps from the response.

  3. Check Effective Folder/Project Policy If Requested:

    • If the customer asks whether their folder already enforces that service-specific Org Policy constraint, run:

      gcloud org-policies describe CONSTRAINT_NAME \
        --folder=FOLDER_ID \
        --effective \
        --format="json(name,spec.rules)"

Failure Modes & Error Recovery Playbook

Error ConditionImmediate ActionUser Recovery Guidance
USER_PROJECT_DENIED or serviceusage.serviceUsageConsumerHALT discovery. Do not confuse with target scope permissions. Check administrative project billing status and caller quota permissions."The administrative project PROJECT_ID cannot be used for API quota. 1) Verify a Cloud Billing account is attached (gcloud billing projects describe PROJECT_ID), 2) Grant roles/serviceusage.serviceUsageConsumer on PROJECT_ID to your identity, or 3) Switch to a project you own: gcloud config set project <PROJECT_ID>."
PERMISSION_DENIED on CAISHALT discovery immediately. Do not speculate or guess resources."To analyze this environment, grant roles/cloudasset.viewer on folders/123 to your active identity."
PERMISSION_DENIED on Org PoliciesHALT policy inspection. Do not guess effective constraints."To inspect effective organization policies, grant roles/orgpolicy.policyViewer on folders/123."
Empty Scope (0 Resources)HALT evaluation. Inform user the scope contains no active assets."No active resources found in folders/123. Provision resources or select an active scope."
Conflicting Regulatory IntentEngage user in focused clarification probe.Present distinct requirements (e.g. DoD IL5 Adjudicated Support vs. ITAR US Persons) and ask for business requirement.
Zero Catalog MatchDetail multi-regional drift indicator.Explain why single-region sovereign data boundary frameworks were ruled out (e.g. multi-continental resource footprint spanning unapproved regions).
Out-of-Scope / Non-Catalog Standard (e.g., CMMC, UK GDPR)Do not invent framework IDs (builtin-cmmc, builtin-uk-gdpr). Explain catalog boundary and map to adjacent ASSURED_WORKLOADS candidates."Assured Workloads does not include a standalone [CMMC / UK GDPR] framework in frameworks.json. However, based on your active resources, we can evaluate an adjacent Assured Workloads Data Boundary framework such as builtin-il5 / builtin-fedramp-high (for US defense/federal workloads) or builtin-eu-data-boundary-and-support / builtin-uk-data-boundary (for European/UK regional residency)."

Files

scripts/evaluate_control_rules.py

#!/usr/bin/env python3
r"""Hermetic CLI utility for evaluating CAIS telemetry against Org Policy specs.

Evaluates the 3 deterministic Organization Policy parameter sets bound in
`google.cloud.cloudsecuritycompliance.v1.Framework.cloudControlDetails`:
  1. Resource Locations (`builtin-restrict-resource-locations`)
  2. Service Usage Restrictions / SUR
     (`builtin-enforce-service-usage-restrictions`)
  3. CMEK Encryption Requirements (`builtin-require-cmek`)

Usage:
  python3 scripts/evaluate_control_rules.py \
    --telemetry-file=macro_telemetry.json \
    --deep-telemetry-file=deep_telemetry.json \
    --framework=builtin-il5 \
    --frameworks-file=frameworks.json
"""

import argparse
import json
import sys
import types
from typing import Any

CONTROL_PLANE_SERVICE_PREFIXES: frozenset[str] = frozenset({
    "cloudresourcemanager.googleapis.com",
    "orgpolicy.googleapis.com",
    "cloudasset.googleapis.com",
    "accesscontextmanager.googleapis.com",
})

CONTROL_PLANE_ASSET_TYPES: frozenset[str] = frozenset({
    "cloudresourcemanager.googleapis.com/Organization",
    "cloudresourcemanager.googleapis.com/Folder",
    "cloudresourcemanager.googleapis.com/Project",
    "orgpolicy.googleapis.com/Policy",
    "cloudasset.googleapis.com/Feed",
    "logging.googleapis.com/BillingAccountSettings",
    "logging.googleapis.com/OrganizationSettings",
    "logging.googleapis.com/FolderSettings",
})

# Standard CAI data-plane asset types associated with CMEK-governed services
# when get_target_asset_types is invoked without Pass 1 active_resources.
DEFAULT_CMEK_SERVICE_ASSET_TYPES: types.MappingProxyType[
    str, tuple[str, ...]
] = types.MappingProxyType({
    "compute.googleapis.com": (
        "compute.googleapis.com/Instance",
        "compute.googleapis.com/Disk",
    ),
    "storage.googleapis.com": ("storage.googleapis.com/Bucket",),
    "sqladmin.googleapis.com": ("sqladmin.googleapis.com/Instance",),
    "container.googleapis.com": ("container.googleapis.com/Cluster",),
    "bigquery.googleapis.com": (
        "bigquery.googleapis.com/Dataset",
        "bigquery.googleapis.com/Table",
    ),
    "pubsub.googleapis.com": ("pubsub.googleapis.com/Topic",),
    "secretmanager.googleapis.com": ("secretmanager.googleapis.com/Secret",),
    "spanner.googleapis.com": ("spanner.googleapis.com/Instance",),
    "run.googleapis.com": ("run.googleapis.com/Service",),
    "artifactregistry.googleapis.com": (
        "artifactregistry.googleapis.com/Repository",
    ),
    "aiplatform.googleapis.com": ("aiplatform.googleapis.com/Dataset",),
})

# Location value groups used by constraints/gcp.resourceLocations in csclibrary
LOCATION_GROUP_PREFIXES: types.MappingProxyType[str, tuple[str, ...]] = (
    types.MappingProxyType({
        "us-locations": ("us-", "us"),
        "in:us-locations": ("us-", "us"),
        "eu-locations": ("europe-", "eu"),
        "in:eu-locations": ("europe-", "eu"),
    })
)

LOCATION_GROUP_EXACT_REGIONS: types.MappingProxyType[str, frozenset[str]] = (
    types.MappingProxyType({
        "canada-locations": frozenset(
            {"northamerica-northeast1", "northamerica-northeast2"}
        ),
        "in:canada-locations": frozenset(
            {"northamerica-northeast1", "northamerica-northeast2"}
        ),
        "australia-locations": frozenset(
            {"australia-southeast1", "australia-southeast2"}
        ),
        "in:australia-locations": frozenset(
            {"australia-southeast1", "australia-southeast2"}
        ),
        "india-locations": frozenset({"asia-south1", "asia-south2"}),
        "in:india-locations": frozenset({"asia-south1", "asia-south2"}),
        "japan-locations": frozenset({"asia-northeast1", "asia-northeast2"}),
        "in:japan-locations": frozenset({"asia-northeast1", "asia-northeast2"}),
        "israel-locations": frozenset({"me-west1"}),
        "in:israel-locations": frozenset({"me-west1"}),
        "ksa-locations": frozenset({"me-central2"}),
        "in:ksa-locations": frozenset({"me-central2"}),
        "switzerland-locations": frozenset({"europe-west6"}),
        "in:switzerland-locations": frozenset({"europe-west6"}),
        "uk-locations": frozenset({"europe-west2"}),
        "in:uk-locations": frozenset({"europe-west2"}),
    })
)


def is_control_plane_metadata(resource: dict[str, Any]) -> bool:
  """Identifies control-plane metadata to exclude from workload evaluation."""
  asset_type = resource.get("assetType", "")
  prefix = asset_type.split("/")[0] if "/" in asset_type else asset_type
  return (
      prefix in CONTROL_PLANE_SERVICE_PREFIXES
      or asset_type in CONTROL_PLANE_ASSET_TYPES
  )


def _extract_string_list_from_param_value(
    param_val: dict[str, Any],
) -> list[str]:
  """Extracts a list of strings from a v1.ParamValue protobuf JSON structure."""
  if not isinstance(param_val, dict):
    return []
  if "stringListValue" in param_val:
    values = param_val["stringListValue"].get("values", [])
    return [str(val) for val in values if val]
  if "stringValue" in param_val and param_val["stringValue"]:
    return [str(param_val["stringValue"])]
  if "oneofValue" in param_val and isinstance(param_val["oneofValue"], dict):
    nested_param_val = param_val["oneofValue"].get("parameterValue", {})
    return _extract_string_list_from_param_value(nested_param_val)
  return []


def parse_framework_org_policy_spec(
    frameworks: list[dict[str, Any]], framework_id: str
) -> dict[str, Any]:
  """Extracts the 3 quantitative Org Policy parameter sets from a Framework."""
  if not frameworks:
    raise ValueError(
        "Empty frameworks list provided. Assured Workloads Frameworks Library"
        " export is empty."
    )

  clean_framework_id = framework_id.split("/")[-1].strip()
  matched_framework: dict[str, Any] | None = None
  for framework in frameworks:
    framework_name = framework.get("name", "")
    candidate_id = framework_name.split("/")[-1] if framework_name else ""
    if candidate_id == clean_framework_id or candidate_id.replace(
        "_", "-"
    ) == clean_framework_id.replace("_", "-"):
      matched_framework = framework
      break

  if matched_framework is None:
    raise ValueError(
        f"Framework '{clean_framework_id}' not found in frameworks.json export."
        " Ensure 'gcloud compliance-manager frameworks list' output includes"
        " this framework."
    )

  allowed_locations: set[str] = set()
  allowed_services: set[str] = set()
  cmek_services: set[str] = set()
  cmek_required = False

  for control in matched_framework.get("cloudControlDetails", []):
    control_name = control.get("name", "")
    control_id = control_name.split("/")[-1] if control_name else ""
    params = control.get("parameters", [])

    if control_id == "builtin-restrict-resource-locations":
      for param in params:
        if param.get("name") in ("locations", "allowedLocations"):
          allowed_locations.update(
              _extract_string_list_from_param_value(
                  param.get("parameterValue", {})
              )
          )
    elif control_id == "builtin-enforce-service-usage-restrictions":
      for param in params:
        if param.get("name") in ("serviceUsage", "allowedServices"):
          allowed_services.update(
              _extract_string_list_from_param_value(
                  param.get("parameterValue", {})
              )
          )
    elif control_id == "builtin-require-cmek":
      cmek_required = True
      for param in params:
        if param.get("name") == "services":
          cmek_services.update(
              _extract_string_list_from_param_value(
                  param.get("parameterValue", {})
              )
          )

  return {
      "framework_id": clean_framework_id,
      "allowed_locations": allowed_locations,
      "allowed_services": allowed_services,
      "cmek_services": cmek_services,
      "cmek_required": cmek_required,
  }


def is_location_allowed(location: str, allowed_locations: set[str]) -> bool:
  """Checks whether a CAIS resource location satisfies resourceLocations."""
  if not allowed_locations:
    return True
  loc = location.strip().lower()
  region = "-".join(loc.split("-")[:2]) if "-" in loc else loc

  normalized_allowed = {
      allowed_loc.strip().lower() for allowed_loc in allowed_locations
  }
  if (
      loc in normalized_allowed
      or region in normalized_allowed
      or f"in:{loc}-locations" in normalized_allowed
      or f"in:{region}-locations" in normalized_allowed
  ):
    return True

  for group_token, prefixes in LOCATION_GROUP_PREFIXES.items():
    if group_token in normalized_allowed:
      if any(
          loc == prefix
          or loc.startswith(prefix)
          or region == prefix
          or region.startswith(prefix)
          for prefix in prefixes
      ):
        return True

  for group_token, exact_regions in LOCATION_GROUP_EXACT_REGIONS.items():
    if group_token in normalized_allowed:
      if loc in exact_regions or region in exact_regions:
        return True

  return False


def get_target_asset_types(
    framework_id: str,
    frameworks: list[dict[str, Any]],
    active_resources: list[dict[str, Any]] | None = None,
) -> list[str]:
  """Derives the CAIS asset types requiring Pass 2 CMEK inspection (`kmsKeys`).

  Only the 6/38 Data Boundary frameworks that include `builtin-require-cmek`
  require Pass 2 CMEK ingestion; for the remaining 32/38 frameworks, this
  returns an empty list so Pass 2 is skipped.

  Args:
    framework_id: Target framework identifier (e.g. 'builtin-il5').
    frameworks: Parsed list of v1.Framework objects from frameworks.json.
    active_resources: Optional Pass 1 CAIS resource list to intersect against.

  Returns:
    Sorted list of CAIS assetType strings requiring Pass 2 CMEK inspection.
  """
  spec = parse_framework_org_policy_spec(frameworks, framework_id)
  if not spec["cmek_required"] or not spec["cmek_services"]:
    return []

  cmek_services: set[str] = spec["cmek_services"]
  if active_resources is not None:
    targets: set[str] = set()
    for resource in active_resources:
      if is_control_plane_metadata(resource):
        continue
      asset_type = resource.get("assetType", "")
      if "/" not in asset_type:
        continue
      service_prefix = asset_type.split("/")[0]
      if service_prefix in cmek_services:
        targets.add(asset_type)
    return sorted(targets)

  default_targets: set[str] = set()
  for service_name in cmek_services:
    for asset_type in DEFAULT_CMEK_SERVICE_ASSET_TYPES.get(service_name, ()):
      default_targets.add(asset_type)
  return sorted(default_targets)


def _extract_kms_keys(resource: dict[str, Any]) -> list[str]:
  """Extracts kmsKeys from CAIS ResourceSearchResult or additionalAttributes."""
  top_keys = resource.get("kmsKeys")
  if isinstance(top_keys, list) and top_keys:
    return [str(key) for key in top_keys if key]
  if isinstance(top_keys, str) and top_keys:
    return [top_keys]
  attrs = resource.get("additionalAttributes", {})
  if isinstance(attrs, dict):
    attr_keys = attrs.get("kmsKeys", [])
    if isinstance(attr_keys, list) and attr_keys:
      return [str(key) for key in attr_keys if key]
  return []


def evaluate_telemetry(
    resources: list[dict[str, Any]],
    framework_id: str,
    frameworks: list[dict[str, Any]],
    deep_resources: list[dict[str, Any]] | None = None,
) -> dict[str, Any]:
  """Evaluates CAIS telemetry against the 3 deterministic Org Policy specs."""
  spec = parse_framework_org_policy_spec(frameworks, framework_id)
  cmek_required: bool = spec["cmek_required"]

  # Index Pass 2 deep telemetry kmsKeys by resource name so Pass 1 telemetry
  # remains the full-scope source of truth for Location and SUR.
  deep_kms_by_name: dict[str, list[str]] = {}
  if deep_resources:
    for deep_resource in deep_resources:
      resource_name = deep_resource.get("name")
      if resource_name:
        deep_kms_by_name[resource_name] = _extract_kms_keys(deep_resource)

  workload_resources = [
      resource
      for resource in resources
      if not is_control_plane_metadata(resource)
  ]
  total_assets = len(workload_resources)

  evaluation_note = (
      "Pre-flight readiness indicators evaluate high-confidence Organization"
      " Policy parameters (location, service usage, CMEK) over CAIS metadata."
      " Authoritative CES and REST control evaluations run server-side via the"
      " Continuous Evaluation Service (CES) after framework deployment."
  )

  if total_assets == 0:
    return {
        "frameworkId": framework_id,
        "totalAssets": 0,
        "cmekRequired": cmek_required,
        "scores": {
            "locationScore": 1.0,
            "serviceScore": 1.0,
            "cmekScore": 1.0,
            "compositeScore": 1.0,
        },
        "orgPolicyDriftIndicators": {
            "outOfBoundaryLocations": [],
            "unapprovedServices": [],
            "missingCmekAssets": [],
        },
        "evaluationNote": evaluation_note,
    }

  # 1. Location Org Policy Check (constraints/gcp.resourceLocations)
  allowed_locations: set[str] = spec["allowed_locations"]
  loc_targets = [
      resource
      for resource in workload_resources
      if resource.get("location") and resource.get("location") != "global"
  ]
  compliant_loc_count = 0
  out_of_boundary_locations: list[dict[str, Any]] = []
  for resource in loc_targets:
    loc = resource.get("location", "")
    if is_location_allowed(loc, allowed_locations):
      compliant_loc_count += 1
    else:
      out_of_boundary_locations.append(
          {"name": resource.get("name"), "location": loc}
      )

  total_loc_assets = len(loc_targets)
  location_score = (
      compliant_loc_count / total_loc_assets if total_loc_assets else 1.0
  )

  # 2. Service Usage Restriction Check (constraints/gcp.restrictServiceUsage)
  allowed_services: set[str] = spec["allowed_services"]
  compliant_svc_count = 0
  unapproved_services: list[dict[str, Any]] = []
  for resource in workload_resources:
    asset_type = resource.get("assetType", "")
    prefix = asset_type.split("/")[0] if "/" in asset_type else asset_type
    if not allowed_services or prefix in allowed_services:
      compliant_svc_count += 1
    else:
      unapproved_services.append(
          {"name": resource.get("name"), "assetType": asset_type}
      )

  service_score = compliant_svc_count / total_assets if total_assets else 1.0

  # 3. CMEK Org Policy Check (constraints/gcp.restrictNonCmekServices)
  cmek_services: set[str] = spec["cmek_services"]
  missing_cmek_assets: list[str] = []
  if cmek_required and cmek_services:
    cmek_targets = [
        resource
        for resource in workload_resources
        if (
            resource.get("assetType", "").split("/")[0]
            if "/" in resource.get("assetType", "")
            else resource.get("assetType", "")
        )
        in cmek_services
    ]
    for resource in cmek_targets:
      resource_name = resource.get("name", "")
      kms_keys = _extract_kms_keys(resource) or deep_kms_by_name.get(
          resource_name, []
      )
      if not kms_keys:
        missing_cmek_assets.append(resource_name)
    cmek_score = (
        1.0 - (len(missing_cmek_assets) / len(cmek_targets))
        if cmek_targets
        else 1.0
    )
  else:
    cmek_score = 1.0

  if cmek_required:
    composite_score = round(
        0.40 * location_score + 0.35 * service_score + 0.25 * cmek_score, 4
    )
  else:
    composite_score = round(
        (0.40 / 0.75) * location_score + (0.35 / 0.75) * service_score, 4
    )

  return {
      "frameworkId": framework_id,
      "totalAssets": total_assets,
      "cmekRequired": cmek_required,
      "scores": {
          "locationScore": round(location_score, 4),
          "serviceScore": round(service_score, 4),
          "cmekScore": round(cmek_score, 4),
          "compositeScore": composite_score,
      },
      "orgPolicyDriftIndicators": {
          "outOfBoundaryLocations": out_of_boundary_locations,
          "unapprovedServices": unapproved_services,
          "missingCmekAssets": missing_cmek_assets,
      },
      "evaluationNote": evaluation_note,
  }


def main() -> None:
  parser = argparse.ArgumentParser(
      description=(
          "Evaluate CAIS telemetry against Assured Workloads Organization"
          " Policy parameters from frameworks.json."
      )
  )
  parser.add_argument(
      "--framework", required=True, help="Framework ID (e.g. builtin-il5)"
  )
  parser.add_argument(
      "--telemetry-file",
      required=False,
      help="Path to Pass 1 CAIS macro telemetry JSON export",
  )
  parser.add_argument(
      "--deep-telemetry-file",
      required=False,
      help="Optional path to Pass 2 CAIS deep telemetry JSON export (kmsKeys)",
  )
  parser.add_argument(
      "--frameworks-file",
      required=True,
      help=(
          "Path to frameworks JSON export from 'gcloud compliance-manager"
          " frameworks list' (authoritative SOT)"
      ),
  )
  parser.add_argument(
      "--get-target-asset-types",
      action="store_true",
      help=(
          "Derive and print CMEK-governed CAIS asset types for Pass 2"
          " inspection"
      ),
  )
  args = parser.parse_args()

  try:
    with open(args.frameworks_file, "r", encoding="utf-8") as f:
      frameworks = json.load(f)

    if args.get_target_asset_types:
      active_resources = None
      if args.telemetry_file:
        with open(args.telemetry_file, "r", encoding="utf-8") as f:
          active_resources = json.load(f)
      target_types = get_target_asset_types(
          args.framework, frameworks, active_resources
      )
      print(",".join(target_types))
      return

    if not args.telemetry_file:
      sys.stderr.write(
          "EVALUATION_ERROR: --telemetry-file is required for rule"
          " evaluation.\n"
      )
      sys.exit(1)

    with open(args.telemetry_file, "r", encoding="utf-8") as f:
      resources = json.load(f)

    deep_resources = None
    if args.deep_telemetry_file:
      try:
        with open(args.deep_telemetry_file, "r", encoding="utf-8") as f:
          deep_resources = json.load(f)
      except FileNotFoundError:
        deep_resources = None

    result = evaluate_telemetry(
        resources, args.framework, frameworks, deep_resources=deep_resources
    )
    print(json.dumps(result, indent=2))
  except (ValueError, OSError, KeyError, TypeError) as e:
    sys.stderr.write(f"EVALUATION_ERROR: {str(e)}\n")
    sys.exit(1)


if __name__ == "__main__":
  main()

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Needs: Needs a command-line tool, Needs Python

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Published by
Google
Publisher
Google (Official)
Source
google/skills · skills/cloud/assuredworkloads-environment-assessor · commit 2194d3b
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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