- name:Leave PR comment with the SaaS Documentation URI
uses:peter-evans/create-or-update-comment@v4
with:
issue-number:${{ env.PR_NUMBER }}
body:|
You can check the documentation for this PR here -> [SaaS Documentation](https://prowler-prowler-docs--${{ env.PR_NUMBER }}.com.readthedocs.build/projects/prowler-open-source/en/${{ env.PR_NUMBER }}/)
<b><i>See all the things you and your team can do with ProwlerPro at <a href="https://prowler.pro">prowler.pro</a></i></b>
<b><i>Prowler SaaS </b> and <b>Prowler Open Source</b> are as dynamic and adaptable as the environment they’re meant to protect. Trusted by the leaders in security.
</p>
<p align="center">
<b>Learn more at <a href="https://prowler.com">prowler.com</i></b>
</p>
<p align="center">
<a href="https://join.slack.com/t/prowler-workspace/shared_invite/zt-1hix76xsl-2uq222JIXrC7Q8It~9ZNog"><img width="30" height="30" alt="Prowler community on Slack" src="https://github.com/prowler-cloud/prowler/assets/3985464/3617e470-670c-47c9-9794-ce895ebdb627"></a>
`Prowler` is an Open Source security tool to perform AWS and Azure security best practices assessments, audits, incident response, continuous monitoring, hardening and forensics readiness.
**Prowler** is an Open Source security tool to perform AWS, Azure, Google Cloud and Kubernetes security best practices assessments, audits, incident response, continuous monitoring, hardening and forensics readiness, and also remediations! We have Prowler CLI (Command Line Interface) that we call Prowler Open Source and a service on top of it that we call <a href="https://prowler.com">Prowler SaaS</a>.
It contains hundreds of controls covering CIS, PCI-DSS, ISO27001, GDPR, HIPAA, FFIEC, SOC2, AWS FTR, ENS and custom security frameworks.
You can run Prowler from your workstation, an EC2 instance, Fargate or any other container, Codebuild, CloudShell and Cloud9.
You can run Prowler from your workstation, a Kubernetes Job, a Google Compute Engine, an Azure VM, an EC2 instance, Fargate or any other container, CloudShell and many more.
Prowler has been written in Python using the [AWS SDK (Boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html#) and [Azure SDK](https://azure.github.io/azure-sdk-for-python/).
## AWS
## General
-`Allowlist` now is called `Mutelist`.
- The `--quiet` option has been deprecated, now use the `--status` flag to select the finding's status you want to get from PASS, FAIL or MANUAL.
- All `INFO` finding's status has changed to `MANUAL`.
- The CSV output format is common for all the providers.
Since Prowler uses AWS Credentials under the hood, you can follow any authentication method as described [here](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-quickstart.html#cli-configure-quickstart-precedence).
Make sure you have properly configured your AWS-CLI with a valid Access Key and Region or declare AWS variables properly (or instance profile/role):
```console
aws configure
```
or
```console
export AWS_ACCESS_KEY_ID="ASXXXXXXX"
export AWS_SECRET_ACCESS_KEY="XXXXXXXXX"
export AWS_SESSION_TOKEN="XXXXXXXXX"
```
Those credentials must be associated to a user or role with proper permissions to do all checks. To make sure, add the following AWS managed policies to the user or role being used:
> Moreover, some read-only additional permissions are needed for several checks, make sure you attach also the custom policy [prowler-additions-policy.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-additions-policy.json) to the role you are using.
> If you want Prowler to send findings to [AWS Security Hub](https://aws.amazon.com/security-hub), make sure you also attach the custom policy [prowler-security-hub.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-security-hub.json).
## Azure
Prowler for Azure supports the following authentication types:
- Service principal authentication by environment variables (Enterprise Application)
- Current az cli credentials stored
- Interactive browser authentication
- Managed identity authentication
### Service Principal authentication
To allow Prowler assume the service principal identity to start the scan, it is needed to configure the following environment variables:
```console
export AZURE_CLIENT_ID="XXXXXXXXX"
export AZURE_TENANT_ID="XXXXXXXXX"
export AZURE_CLIENT_SECRET="XXXXXXX"
```
If you try to execute Prowler with the `--sp-env-auth` flag and those variables are empty or not exported, the execution is going to fail.
### AZ CLI / Browser / Managed Identity authentication
The other three cases do not need additional configuration, `--az-cli-auth` and `--managed-identity-auth` are automated options, `--browser-auth` needs the user to authenticate using the default browser to start the scan.
### Permissions
To use each one, you need to pass the proper flag to the execution. Prowler for Azure handles two types of permission scopes, which are:
- **Azure Active Directory permissions**: Used to retrieve metadata from the identity assumed by Prowler and future AAD checks (not mandatory to have access to execute the tool)
- **Subscription scope permissions**: Required to launch the checks against your resources, mandatory to launch the tool.
#### Azure Active Directory scope
Azure Active Directory (AAD) permissions required by the tool are the following:
- `Directory.Read.All`
- `Policy.Read.All`
#### Subscriptions scope
Regarding the subscription scope, Prowler by default scans all the subscriptions that is able to list, so it is required to add the following RBAC builtin roles per subscription to the entity that is going to be assumed by the tool:
- `Security Reader`
- `Reader`
# 💻 Basic Usage
To run prowler, you will need to specify the provider (e.g aws or azure):
> Running the `prowler` command without options will use your environment variable credentials.
By default, prowler will generate a CSV, a JSON and a HTML report, however you can generate JSON-ASFF (only for AWS Security Hub) report with `-M` or `--output-modes`:
```console
prowler <provider> -M csv json json-asff html
```
The html report will be located in the `output` directory as the other files and it will look like:
@@ -14,7 +14,7 @@ As an **AWS Partner** and we have passed the [AWS Foundation Technical Review (F
If you would like to report a vulnerability or have a security concern regarding Prowler Open Source or ProwlerPro service, please submit the information by contacting to help@prowler.pro.
The information you share with Verica as part of this process is kept confidential within Verica and the Prowler team. We will only share this information with a third party if the vulnerability you report is found to affect a third-party product, in which case we will share this information with the third-party product's author or manufacturer. Otherwise, we will only share this information as permitted by you.
The information you share with ProwlerPro as part of this process is kept confidential within ProwlerPro. We will only share this information with a third party if the vulnerability you report is found to affect a third-party product, in which case we will share this information with the third-party product's author or manufacturer. Otherwise, we will only share this information as permitted by you.
We will review the submitted report, and assign it a tracking number. We will then respond to you, acknowledging receipt of the report, and outline the next steps in the process.
The following demonstartes how to quickly install the resources necessary to perform a security baseline using Prowler. The speed is based on the prebuilt terraform module that can configure all the resources necessuary to run Prowler with the findings being sent to AWS Security Hub.
The following demonstrates how to quickly install the resources necessary to perform a security baseline using Prowler. The speed is based on the prebuilt terraform module that can configure all the resources necessary to run Prowler with the findings being sent to AWS Security Hub.
## Install
@@ -24,7 +24,7 @@ Installing Prowler with Terraform is simple and can be completed in under 1 minu
- It is likely an error will return related to the SecurityHub subscription. This appears to be Terraform related and you can validate the configuration by navigating to the SecurityHub console. Click Integreations and search for Prowler. Take note of the green check where it says *Accepting findings*
- It is likely an error will return related to the SecurityHub subscription. This appears to be Terraform related and you can validate the configuration by navigating to the SecurityHub console. Click Integrations and search for Prowler. Take note of the green check where it says *Accepting findings*
@@ -92,7 +92,7 @@ To make sure rules are working fine, run `/var/ossec/bin/ossec-logtest` and copy
```
You must see 3 phases goin on.
To check if there is any error you can enable the debug mode of `modulesd` setting the `wazuh_modules.debug=0` variable to 2 in `/var/ossec/etc/internal_options.conf` file. Restart wazun-manager and errors should appear in the `/var/ossec/logs/ossec.log` file.
To check if there is any error you can enable the debug mode of `modulesd` setting the `wazuh_modules.debug=0` variable to 2 in `/var/ossec/etc/internal_options.conf` file. Restart wazuh-manager and errors should appear in the `/var/ossec/logs/ossec.log` file.
f"{Fore.GREEN}Loading all CSV files from the folder {folder_path_overview} ...\n{Style.RESET_ALL}"
)
cli.show_server_banner=lambda*x:click.echo(
f"{Fore.YELLOW}NOTE:{Style.RESET_ALL} If you are a {Fore.GREEN}{Style.BRIGHT}Prowler SaaS{Style.RESET_ALL} customer and you want to use your data from your S3 bucket,\nrun: `{orange_color}aws s3 cp s3://<your-bucket>/output/csv ./output --recursive{Style.RESET_ALL}`\nand then run `prowler dashboard` again to load the new files."
Here you can find how to create new checks for Prowler.
**To create a check is required to have a Prowler provider service already created, so if the service is not present or the attribute you want to audit is not retrieved by the service, please refer to the [Service](./services.md) documentation.**
## Introduction
The checks are the fundamental piece of Prowler. A check is a simply piece of code that ensures if something is configured against cybersecurity best practices. Then the check generates a finding with the result and includes the check's metadata to give the user more contextual information about the result, the risk and how to remediate it.
To create a new check for a supported Prowler provider, you will need to create a folder with the check name inside the specific service for the selected provider.
We are going to use the `ec2_ami_public` check from the `AWS` provider as an example. So the folder name will be `prowler/providers/aws/services/ec2/ec2_ami_public` (following the format `prowler/providers/<provider>/services/<service>/<check_name>`), with the name of check following the pattern: `service_subservice_resource_action`.
???+ note
A subservice is an specific component of a service that is gonna be audited. Sometimes it could be the shortened name of the class attribute that is gonna be accessed in the check.
Inside that folder, we need to create three files:
- An empty `__init__.py`: to make Python treat this check folder as a package.
- A `check_name.py` with the above format containing the check's logic. Refer to the [check](./checks.md#check)
- A `check_name.metadata.json` containing the check's metadata. Refer to the [check metadata](./checks.md#check-metadata)
## Check
The Prowler's check structure is very simple and following it there is nothing more to do to include a check in a provider's service because the load is done dynamically based on the paths.
The following is the code for the `ec2_ami_public` check:
```python title="Check Class"
# At the top of the file we need to import the following:
# - Check class which is in charge of the following:
# - Retrieve the check metadata and expose the `metadata()`
# to return a JSON representation of the metadata,
# read more at Check Metadata Model down below.
# - Enforce that each check requires to have the `execute()` function
from prowler.lib.check.models import Check, Check_Report_AWS
# Then you have to import the provider service client
# read more at the Service documentation.
from prowler.providers.aws.services.ec2.ec2_client import ec2_client
# For each check we need to create a python class called the same as the
# file which inherits from the Check class.
class ec2_ami_public(Check):
"""ec2_ami_public verifies if an EC2 AMI is publicly shared"""
# Then, within the check's class we need to create the "execute(self)"
# function, which is enforce by the "Check" class to implement
# the Check's interface and let Prowler to run this check.
def execute(self):
# Inside the execute(self) function we need to create
# the list of findings initialised to an empty list []
findings = []
# Then, using the service client we need to iterate by the resource we
# want to check, in this case EC2 AMIs stored in the
# "ec2_client.images" object.
for image in ec2_client.images:
# Once iterating for the images, we have to intialise
# the Check_Report_AWS class passing the check's metadata
# using the "metadata" function explained above.
report = Check_Report_AWS(self.metadata())
# For each Prowler check we MUST fill the following
# Check_Report_AWS fields:
# - region
# - resource_id
# - resource_arn
# - resource_tags
# - status
# - status_extended
report.region = image.region
report.resource_id = image.id
report.resource_arn = image.arn
# The resource_tags should be filled if the resource has the ability
# of having tags, please check the service first.
report.resource_tags = image.tags
# Then we need to create the business logic for the check
# which always should be simple because the Prowler service
# must do the heavy lifting and the check should be in charge
# of parsing the data provided
report.status = "PASS"
report.status_extended = f"EC2 AMI {image.id} is not public."
# In this example each "image" object has a boolean attribute
# called "public" to set if the AMI is publicly shared
if image.public:
report.status = "FAIL"
report.status_extended = (
f"EC2 AMI {image.id} is currently public."
)
# Then at the same level as the "report"
# object we need to append it to the findings list.
findings.append(report)
# Last thing to do is to return the findings list to Prowler
return findings
```
### Check Status
All the checks MUST fill the `report.status` and `report.status_extended` with the following criteria:
- Status -- `report.status`
- `PASS` --> If the check is passing against the configured value.
- `FAIL` --> If the check is failing against the configured value.
- `MANUAL` --> This value cannot be used unless a manual operation is required in order to determine if the `report.status` is whether `PASS` or `FAIL`.
- Status Extended -- `report.status_extended`
- MUST end in a dot `.`
- MUST include the service audited with the resource and a brief explanation of the result generated, e.g.: `EC2 AMI ami-0123456789 is not public.`
### Check Region
All the checks MUST fill the `report.region` with the following criteria:
- If the audited resource is regional use the `region` (the name changes depending on the provider: `location` in Azure and GCP and `namespace` in K8s) attribute within the resource object.
- If the audited resource is global use the `service_client.region` within the service client object.
### Resource ID, Name and ARN
All the checks MUST fill the `report.resource_id` and `report.resource_arn` with the following criteria:
- Root resource --> Resource Type ARN `f"arn:{service_client.audited_partition}:<service_name>:{service_client.region}:{service_client.audited_account}:<resource_type>"`
- GCP
- Resource ID -- `report.resource_id`
- GCP Resource --> Resource ID
- Resource Name -- `report.resource_name`
- GCP Resource --> Resource Name
- Azure
- Resource ID -- `report.resource_id`
- Azure Resource --> Resource ID
- Resource Name -- `report.resource_name`
- Azure Resource --> Resource Name
### Python Model
The following is the Python model for the check's class.
As per April 11th 2024 the `Check_Metadata_Model` can be found [here](https://github.com/prowler-cloud/prowler/blob/master/prowler/lib/check/models.py#L36-L82).
```python
class Check(ABC, Check_Metadata_Model):
"""Prowler Check"""
def __init__(self, **data):
"""Check's init function. Calls the CheckMetadataModel init."""
data = Check_Metadata_Model.parse_file(metadata_file).dict()
# Calls parents init function
super().__init__(**data)
def metadata(self) -> dict:
"""Return the JSON representation of the check's metadata"""
return self.json()
@abstractmethod
def execute(self):
"""Execute the check's logic"""
```
###Using the audit config
Prowler has a [configuration file](../tutorials/configuration_file.md) which is used to pass certain configuration values to the checks, like the following:
As you can see in the above code, within the service client, in this case the `ec2_client`, there is an object called `audit_config` which is a Python dictionary containing the values read from the configuration file.
In order to use it, you have to check first if the value is present in the configuration file. If the value is not present, you can create it in the `config.yaml` file and then, read it from the check.
???+ note
It is mandatory to always use the `dictionary.get(value, default)` syntax to set a default value in the case the configuration value is not present.
## Check Metadata
Each Prowler check has metadata associated which is stored at the same level of the check's folder in a file called A `check_name.metadata.json` containing the check's metadata.
???+ note
We are going to include comments in this example metadata JSON but they cannot be included because the JSON format does not allow comments.
```json
{
# Provider holds the Prowler provider which the checks belongs to
"Provider": "aws",
# CheckID holds check name
"CheckID": "ec2_ami_public",
# CheckTitle holds the title of the check
"CheckTitle": "Ensure there are no EC2 AMIs set as Public.",
# CheckType holds Software and Configuration Checks, check more here
# Description holds the title of the check, for now is the same as CheckTitle
"Description": "Ensure there are no EC2 AMIs set as Public.",
# Risk holds the check risk if the result is FAIL
"Risk": "When your AMIs are publicly accessible, they are available in the Community AMIs where everyone with an AWS account can use them to launch EC2 instances. Your AMIs could contain snapshots of your applications (including their data), therefore exposing your snapshots in this manner is not advised.",
# RelatedUrl holds an URL with more information about the check purpose
"RelatedUrl": "",
# Remediation holds the information to help the practitioner to fix the issue in the case of the check raise a FAIL
"Remediation": {
# Code holds different methods to remediate the FAIL finding
"Code": {
# CLI holds the command in the provider native CLI to remediate it
The RelatedURL field must be filled with an URL from the provider's official documentation like https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/sharingamis-intro.html
Also, if not present you can use the Risk and Recommendation texts from the TrendMicro [CloudConformity](https://www.trendmicro.com/cloudoneconformity) guide.
### Python Model
The following is the Python model for the check's metadata model. We use the Pydantic's [BaseModel](https://docs.pydantic.dev/latest/api/base_model/#pydantic.BaseModel) as the parent class.
As per August 5th 2023 the `Check_Metadata_Model` can be found [here](https://github.com/prowler-cloud/prowler/blob/master/prowler/lib/check/models.py#L34-L56).
If you are developing Prowler, it's possible that you will encounter some situations where you have to inspect the code in depth to fix some unexpected issues during the execution. To do that, if you are using VSCode you can run the code using the integrated debugger. Please, refer to this [documentation](https://code.visualstudio.com/docs/editor/debugging) for guidance about the debugger in VSCode.
The following file is an example of the [debugging configuration](https://code.visualstudio.com/docs/editor/debugging#_launch-configurations) file that you can add to [Virtual Studio Code](https://code.visualstudio.com/).
This file should inside the *.vscode* folder and its name has to be *launch.json*:
We use `mkdocs` to build this Prowler documentation site so you can easily contribute back with new docs or improving them. To install all necessary dependencies use `poetry install --with docs`.
1. Install `mkdocs` with your favorite package manager.
2. Inside the `prowler` repository folder run `mkdocs serve` and point your browser to `http://localhost:8000` and you will see live changes to your local copy of this documentation site.
3. Make all needed changes to docs or add new documents. To do so just edit existing md files inside `prowler/docs` and if you are adding a new section or file please make sure you add it to `mkdocs.yaml` file in the root folder of the Prowler repo.
4. Once you are done with changes, please send a pull request to us for review and merge. Thank you in advance!
You can extend Prowler Open Source in many different ways, in most cases you will want to create your own checks and compliance security frameworks, here is where you can learn about how to get started with it. We also include how to create custom outputs, integrations and more.
## Get the code and install all dependencies
First of all, you need a version of Python 3.9 or higher and also pip installed to be able to install all dependencies required. Once that is satisfied go a head and clone the repo:
For isolation and avoid conflicts with other environments, we recommend usage of `poetry`:
```
pip install poetry
```
Then install all dependencies including the ones for developers:
```
poetry install --with dev
poetry shell
```
## Contributing with your code or fixes to Prowler
This repo has git pre-commit hooks managed via the [pre-commit](https://pre-commit.com/) tool. [Install](https://pre-commit.com/#install) it how ever you like, then in the root of this repo run:
```shell
pre-commit install
```
You should get an output like the following:
```shell
pre-commit installed at .git/hooks/pre-commit
```
Before we merge any of your pull requests we pass checks to the code, we use the following tools and automation to make sure the code is secure and dependencies up-to-dated:
???+ note
These should have been already installed if you ran `poetry install --with dev`
- [`bandit`](https://pypi.org/project/bandit/) for code security review.
- [`safety`](https://pypi.org/project/safety/) and [`dependabot`](https://github.com/features/security) for dependencies.
- [`hadolint`](https://github.com/hadolint/hadolint) and [`dockle`](https://github.com/goodwithtech/dockle) for our containers security.
- [`Snyk`](https://docs.snyk.io/integrations/snyk-container-integrations/container-security-with-docker-hub-integration) in Docker Hub.
- [`clair`](https://github.com/quay/clair) in Amazon ECR.
- [`vulture`](https://pypi.org/project/vulture/), [`flake8`](https://pypi.org/project/flake8/), [`black`](https://pypi.org/project/black/) and [`pylint`](https://pypi.org/project/pylint/) for formatting and best practices.
You can see all dependencies in file `pyproject.toml`.
## Pull Request Checklist
If you create or review a PR in https://github.com/prowler-cloud/prowler please follow this checklist:
- [ ] Make sure you've read the Prowler Developer Guide at https://docs.prowler.cloud/en/latest/developer-guide/introduction/
- [ ] Are we following the style guide, hence installed all the linters and formatters? Please check https://docs.prowler.cloud/en/latest/developer-guide/introduction/#contributing-with-your-code-or-fixes-to-prowler
- [ ] Are we increasing/decreasing the test coverage? Please, review if we need to include/modify tests for the new code.
- [ ] Are we modifying outputs? Please review it carefully.
- [ ] Do we need to modify the Prowler documentation to reflect the changes introduced?
- [ ] Are we introducing possible breaking changes? Are we modifying a core feature?
## Want some swag as appreciation for your contribution?
If you are like us and you love swag, we are happy to thank you for your contribution with some laptop stickers or whatever other swag we may have at that time. Please, tell us more details and your pull request link in our [Slack workspace here](https://join.slack.com/t/prowler-workspace/shared_invite/zt-1hix76xsl-2uq222JIXrC7Q8It~9ZNog). You can also reach out to Toni de la Fuente on Twitter [here](https://twitter.com/ToniBlyx), his DMs are open.
Here you can find how to create a new Provider in Prowler to give support for making all security checks needed and make your cloud safer!
## Introduction
Providers are the foundation on which Prowler is built, a simple definition for a cloud provider could be "third-party company that offers a platform where any IT resource you need is available at any time upon request". The most well-known cloud providers are Amazon Web Services, Azure from Microsoft and Google Cloud which are already supported by Prowler.
To create a new provider that is not supported now by Prowler and add your security checks you must create a new folder to store all the related files within it (services, checks, etc.). It must be store in route `prowler/providers/<new_provider_name>/`.
Inside that folder, you MUST create the following files and folders:
- A `lib` folder: to store all extra functions.
- A `services` folder: to store all [services](./services.md) to audit.
- An empty `__init__.py`: to make Python treat this service folder as a package.
- A `<new_provider_name>_provider.py`, containing all the provider's logic necessary to get authenticated in the provider, configurations and extra data useful for final report.
- A `models.py`, containing all the models necessary for the new provider.
## Provider
The structure for Prowler's providers is set up in such a way that they can be utilized through a generic service specific to each provider. This is achieved by passing the required parameters to the constructor, which in turn initializes all the necessary session values.
### Base Class
All the providers in Prowler inherits from the same [base class](https://github.com/prowler-cloud/prowler/blob/master/prowler/providers/common/provider.py). It is an [abstract base class](https://docs.python.org/3/library/abc.html) that defines the interface for all provider classes. The code of the class is the next:
```python title="Provider Base Class"
from abc import ABC, abstractmethod
from typing import Any
class Provider(ABC):
"""
The Provider class is an abstract base class that defines the interface for all provider classes in the auditing system.
Attributes:
type (property): The type of the provider.
identity (property): The identity of the provider for auditing.
session (property): The session of the provider for auditing.
audit_config (property): The audit configuration of the provider.
output_options (property): The output configuration of the provider for auditing.
Methods:
print_credentials(): Displays the provider's credentials used for auditing in the command-line interface.
setup_session(): Sets up the session for the provider.
get_output_mapping(): Returns the output mapping between the provider and the generic model.
validate_arguments(): Validates the arguments for the provider.
get_checks_to_execute_by_audit_resources(): Returns a set of checks based on the input resources to scan.
Note:
This is an abstract base class and should not be instantiated directly. Each provider should implement its own
version of the Provider class by inheriting from this base class and implementing the required methods and properties.
"""
@property
@abstractmethod
def type(self) -> str:
"""
type method stores the provider's type.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@property
@abstractmethod
def identity(self) -> str:
"""
identity method stores the provider's identity to audit.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@abstractmethod
def setup_session(self) -> Any:
"""
setup_session sets up the session for the provider.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@property
@abstractmethod
def session(self) -> str:
"""
session method stores the provider's session to audit.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@property
@abstractmethod
def audit_config(self) -> str:
"""
audit_config method stores the provider's audit configuration.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@abstractmethod
def print_credentials(self) -> None:
"""
print_credentials is used to display in the CLI the provider's credentials used to audit.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@property
@abstractmethod
def output_options(self) -> str:
"""
output_options method returns the provider's audit output configuration.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@output_options.setter
@abstractmethod
def output_options(self, value: str) -> Any:
"""
output_options.setter sets the provider's audit output configuration.
This method needs to be created in each provider.
"""
raise NotImplementedError()
@abstractmethod
def get_output_mapping(self) -> dict:
"""
get_output_mapping returns the output mapping between the provider and the generic model.
This method needs to be created in each provider.
"""
raise NotImplementedError()
def validate_arguments(self) -> None:
"""
validate_arguments validates the arguments for the provider.
This method can be overridden in each provider if needed.
If you want to create or contribute with your own security frameworks or add public ones to Prowler you need to make sure the checks are available if not you have to create your own. Then create a compliance file per provider like in `prowler/compliance/<provider>/` and name it as `<framework>_<version>_<provider>.json` then follow the following format to create yours.
## Compliance Framework
Each file version of a framework will have the following structure at high level with the case that each framework needs to be generally identified, one requirement can be also called one control but one requirement can be linked to multiple prowler checks.:
- `Framework`: string. Distinguish name of the framework, like CIS
- `Provider`: string. Provider where the framework applies, such as AWS, Azure, OCI,...
- `Version`: string. Version of the framework itself, like 1.4 for CIS.
- `Requirements`: array of objects. Include all requirements or controls with the mapping to Prowler.
- `Requirements_Id`: string. Unique identifier per each requirement in the specific framework
- `Requirements_Description`: string. Description as in the framework.
- `Requirements_Attributes`: array of objects. Includes all needed attributes per each requirement, like levels, sections, etc. Whatever helps to create a dedicated report with the result of the findings. Attributes would be taken as closely as possible from the framework's own terminology directly.
- `Requirements_Checks`: array. Prowler checks that are needed to prove this requirement. It can be one or multiple checks. In case of no automation possible this can be empty.
```
{
"Framework": "<framework>-<provider>",
"Version": "<version>",
"Requirements": [
{
"Id": "<unique-id>",
"Description": "Requirement full description",
"Checks": [
"Here is the prowler check or checks that is going to be executed"
],
"Attributes": [
{
<Add here your custom attributes.>
}
]
},
...
]
}
```
Finally, to have a proper output file for your reports, your framework data model has to be created in `prowler/lib/outputs/models.py` and also the CLI table output in `prowler/lib/outputs/compliance.py`. Also, you need to add a new conditional in `prowler/lib/outputs/file_descriptors.py` if you create a new CSV model.
Here you can find how to create a new service, or to complement an existing one, for a Prowler Provider.
## Introduction
In Prowler, a service is basically a solution that is offered by a cloud provider i.e. [ec2](https://aws.amazon.com/ec2/). Essentially it is a class that stores all the necessary stuff that we will need later in the checks to audit some aspects of our Cloud account.
To create a new service, you will need to create a folder inside the specific provider, i.e. `prowler/providers/<provider>/services/<new_service_name>/`.
Inside that folder, you MUST create the following files:
- An empty `__init__.py`: to make Python treat this service folder as a package.
- A `<new_service_name>_service.py`, containing all the service's logic and API calls.
- A `<new_service_name>_client_.py`, containing the initialization of the service's class we have just created so the checks's checks can use it.
## Service
The Prowler's service structure is the following and the way to initialise it is just by importing the service client in a check.
### Service Base Class
All the Prowler provider's services inherits from a base class depending on the provider used.
- [AWS Service Base Class](https://github.com/prowler-cloud/prowler/blob/master/prowler/providers/aws/lib/service/service.py)
- [GCP Service Base Class](https://github.com/prowler-cloud/prowler/blob/master/prowler/providers/azure/lib/service/service.py)
- [Azure Service Base Class](https://github.com/prowler-cloud/prowler/blob/master/prowler/providers/gcp/lib/service/service.py)
- [Kubernetes Service Base Class](https://github.com/prowler-cloud/prowler/blob/master/prowler/providers/kubernetes/lib/service/service.py)
Each class is used to initialize the credentials and the API's clients to be used in the service. If some threading is used it must be coded there.
### Service Class
Due to the complexity and differences of each provider API we are going to use an example service to guide you in how can it be created.
The following is the `<new_service_name>_service.py` file:
```python title="Service Class"
from datetime import datetime
from typing import Optional
# The following is just for the AWS provider
from botocore.client import ClientError
# To use the Pydantic's BaseModel
from pydantic import BaseModel
# Prowler logging library
from prowler.lib.logger import logger
# Prowler resource filter, only for the AWS provider
from prowler.lib.scan_filters.scan_filters import is_resource_filtered
# Provider parent class
from prowler.providers.<provider>.lib.service.service import ServiceParentClass
# Create a class for the Service
################## <Service>
class <Service>(ServiceParentClass):
def __init__(self, provider):
# Call Service Parent Class __init__
# We use the __class__.__name__ to get it automatically
# from the Service Class name but you can pass a custom
# string if the provider's API service name is different
super().__init__(__class__.__name__, provider)
#Create an empty dictionary of items to be gathered,
To avoid fake findings, when Prowler can't retrieve the items, because an Access Denied or similar error, we set that items value as `None`.
####Service Models
Service models are classes that are used in the service to design all that we need to store in each class object extrated from API calls. We use the Pydantic's [BaseModel](https://docs.pydantic.dev/latest/api/base_model/#pydantic.BaseModel) to take advantage of the data validation.
```python title="Service Model"
# In each service class we have to create some classes using
# the Pydantic's Basemodel for the resources we want to audit.
class <Item>(BaseModel):
"""<Item> holds a <Service> <Item>"""
arn: str
"""<Items>[].arn"""
name: str
"""<Items>[].name"""
region: str
"""<Items>[].region"""
public: bool
"""<Items>[].public"""
# We can create Optional attributes set to None by default
tags: Optional[list]
"""<Items>[].tags"""
```
#### Service Objects
In the service each group of resources should be created as a Python [dictionary](https://docs.python.org/3/tutorial/datastructures.html#dictionaries). This is because we are performing lookups all the time and the Python dictionary lookup has [O(1) complexity](https://en.wikipedia.org/wiki/Big_O_notation#Orders_of_common_functions).
We MUST set as the dictionary key a unique ID, like the resource Unique ID or ARN.
Each Prowler service requires a service client to use the service in the checks.
The following is the `<new_service_name>_client.py` containing the initialization of the service's class we have just created so the service's checks can use them:
```python
from prowler.providers.common.common import get_global_provider
from prowler.providers.<provider>.services.<new_service_name>.<new_service_name>_service import <Service>
It is really important to check if the current Prowler's permissions for each provider are enough to implement a new service. If we need to include more please refer to the following documentaion and update it:
When creating tests for some provider's checks we follow these guidelines trying to cover as much test scenarios as possible:
1. Create a test without resource to generate 0 findings, because Prowler will generate 0 findings if a service does not contain the resources the check is looking for audit.
2. Create test to generate both a `PASS` and a `FAIL` result.
3. Create tests with more than 1 resource to evaluate how the check behaves and if the number of findings is right.
## How to run Prowler tests
To run the Prowler test suite you need to install the testing dependencies already included in the `pyproject.toml` file. If you didn't install it yet please read the developer guide introduction [here](./introduction.md#get-the-code-and-install-all-dependencies).
Then in the project's root path execute `pytest -n auto -vvv -s -x` or use the `Makefile` with `make test`.
Other commands to run tests:
- Run tests for a provider: `pytest -n auto -vvv -s -x tests/providers/<provider>/services`
- Run tests for a provider service: `pytest -n auto -vvv -s -x tests/providers/<provider>/services/<service>`
- Run tests for a provider check: `pytest -n auto -vvv -s -x tests/providers/<provider>/services/<service>/<check>`
???+ note
Refer to the [pytest documentation](https://docs.pytest.org/en/7.1.x/getting-started.html) documentation for more information.
## AWS
For the AWS provider we have ways to test a Prowler check based on the following criteria:
???+ note
We use and contribute to the [Moto](https://github.com/getmoto/moto) library which allows us to easily mock out tests based on AWS infrastructure. **It's awesome!**
- AWS API calls covered by [Moto](https://github.com/getmoto/moto):
- Service tests with `@mock_<service>`
- Checks tests with `@mock_<service>`
- AWS API calls not covered by Moto:
- Service test with `mock_make_api_call`
- Checks tests with [MagicMock](https://docs.python.org/3/library/unittest.mock.html#unittest.mock.MagicMock)
- AWS API calls partially covered by Moto:
- Service test with `@mock_<service>` and `mock_make_api_call`
- Checks tests with `@mock_<service>` and `mock_make_api_call`
In the following section we are going to explain all of the above scenarios with examples. The main difference between those scenarios comes from if the [Moto](https://github.com/getmoto/moto) library covers the AWS API calls made by the service. You can check the covered API calls [here](https://github.com/getmoto/moto/blob/master/IMPLEMENTATION_COVERAGE.md).
### Checks
For the AWS tests examples we are going to use the tests for the `iam_password_policy_uppercase` check.
This section is going to be divided based on the API coverage of the [Moto](https://github.com/getmoto/moto) library.
#### API calls covered
If the [Moto](https://github.com/getmoto/moto) library covers the API calls we want to test, we can use the `@mock_<service>` decorator. This will mocked out all the API calls made to AWS keeping the state within the code decorated, in this case the test function.
```python
# We need to import the unittest.mock to allow us to patch some objects
# not to use shared ones between test, hence to isolate the test
from unittest import mock
# Boto3 client and session to call the AWS APIs
from boto3 import client, session
# Moto decorator for the IAM service we want to mock
from moto import mock_iam
# Constants used
AWS_ACCOUNT_NUMBER = "123456789012"
AWS_REGION = "us-east-1"
# We always name the test classes like Test_<check_name>
class Test_iam_password_policy_uppercase:
# We include the Moto decorator for the service we want to use
# You can include more than one if two or more services are
# involved in test
@mock_iam
# We name the tests with test_<service>_<check_name>_<test_action>
If the IAM service for the check's we want to test is not covered by Moto, we have to inject the objects in the service client using [MagicMock](https://docs.python.org/3/library/unittest.mock.html#unittest.mock.MagicMock). As we have pointed above, we cannot instantiate the service since it will make real calls to the AWS APIs.
???+ note
The following example uses the IAM GetAccountPasswordPolicy which is covered by Moto but this is only for demonstration purposes.
The following code shows how to use MagicMock to create the service objects.
```python
# We need to import the unittest.mock to allow us to patch some objects
# not to use shared ones between test, hence to isolate the test
from unittest import mock
# Constants used
AWS_ACCOUNT_NUMBER = "123456789012"
AWS_REGION = "us-east-1"
# We always name the test classes like Test_<check_name>
class Test_iam_password_policy_uppercase:
# We name the tests with test_<service>_<check_name>_<test_action>
# In this scenario we have to mock also the IAM service and the iam_client from the check to enforce # that the iam_client used is the one created within this check because patch != import, and if you # execute tests in parallel some objects can be already initialised hence the check won't be isolated.
# In this case we don't use the Moto decorator, we use the mocked IAM client for both objects
As it can be seen in the above scenarios, the check execution should always be into the context of mocked/patched objects. This way we ensure it reviews only the objects created under the scope the test.
#### API calls partially covered
If the API calls we want to use in the service are partially covered by the Moto decorator we have to create our own mocked API calls to use it in combination.
To do so, you need to mock the `botocore.client.BaseClient._make_api_call` function, which is the Boto3 function in charge of making the real API call to the AWS APIs, using `mock.patch <https://docs.python.org/3/library/unittest.mock.html#patch>`:
# Check the previous section to see the check test since is the same
```
Note that this does not use Moto, to keep it simple, but if you use any `moto`-decorators in addition to the patch, the call to `orig(self, operation_name, kwarg)` will be intercepted by Moto.
???+ note
The above code comes from here https://docs.getmoto.org/en/latest/docs/services/patching_other_services.html
#### Mocking more than one service
Since we are mocking the provider, it can be customized setting multiple attributes to the provider:
If the test your are creating belongs to a check that uses more than one provider service, you should mock each of the services used. For example, the check `cloudtrail_logs_s3_bucket_access_logging_enabled` requires the CloudTrail and the S3 client, hence the service's mock part of the test will be as follows:
As you can see in the above code, it is required to mock the AWS audit info and both services used.
#### Patching vs. Importing
This is an important topic within the Prowler check's unit testing. Due to the dynamic nature of the check's load, the process of importing the service client from a check is the following:
1. `<check>.py`:
```python
from prowler.providers.<provider>.services.<service>.<service>_client import <service>_client
```
2. `<service>_client.py`:
```python
from prowler.providers.common.common import get_global_provider
from prowler.providers.<provider>.services.<service>.<service>_service import <SERVICE>
<service>_client = <SERVICE>(mocked_provider)
```
Due to the above import path it's not the same to patch the following objects because if you run a bunch of tests, either in parallel or not, some clients can be already instantiated by another check, hence your test execution will be using another test's service instance:
- `<service>_client` imported at `<check>.py`
- `<service>_client` initialised at `<service>_client.py`
- `<SERVICE>` imported at `<service>_client.py`
A useful read about this topic can be found in the following article: https://stackoverflow.com/questions/8658043/how-to-mock-an-import
#### Different ways to mock the service client
##### Mocking the service client at the service client level
Mocking a service client using the following code ...
Once the needed attributes are set for the mocked provider, you can use the mocked provider:
will cause that the service will be initialised twice:
1. When the `<SERVICE>(set_mocked_aws_provider([<region>]))` is mocked out using `mock.patch` to have the object ready for the patching.
2. At the `<service>_client.py` when we are patching it since the `mock.patch` needs to go to that object an initialise it, hence the `<SERVICE>(set_mocked_aws_provider([<region>]))` will be called again.
Then, when we import the `<service>_client.py` at `<check>.py`, since we are mocking where the object is used, Python will use the mocked one.
In the [next section](./unit-testing.md#mocking-the-service-and-the-service-client-at-the-service-client-level) you will see an improved version to mock objects.
##### Mocking the service and the service client at the service client level
Mocking a service client using the following code ...
```python title="Mocking the service and the service_client"
will cause that the service will be initialised once, just when the `set_mocked_aws_provider([<region>])` is mocked out using `mock.patch`.
Then, at the check_level when Python tries to import the client with `from prowler.providers.<provider>.services.<service>.<service>_client`, since it is already mocked out, the execution will continue using the `service_client` without getting into the `<service>_client.py`.
### Services
For testing the AWS services we have to follow the same logic as with the AWS checks, we have to check if the AWS API calls made by the service are covered by Moto and we have to test the service `__init__` to verify that the information is being correctly retrieved.
The service tests could act as *Integration Tests* since we test how the service retrieves the information from the provider, but since Moto or the custom mock objects mocks that calls this test will fall into *Unit Tests*.
Please refer to the [AWS checks tests](./unit-testing.md#checks) for more information on how to create tests and check the existing services tests [here](https://github.com/prowler-cloud/prowler/tree/master/tests/providers/aws/services).
## GCP
### Checks
For the GCP Provider we don't have any library to mock out the API calls we use. So in this scenario we inject the objects in the service client using [MagicMock](https://docs.python.org/3/library/unittest.mock.html#unittest.mock.MagicMock).
The following code shows how to use MagicMock to create the service objects for a GCP check test. It is a real example adapted for informative purposes.
```python
from re import search
from unittest import mock
# Import some constant values needed in every check
from tests.providers.gcp.gcp_fixtures import GCP_PROJECT_ID, set_mocked_gcp_provider
# We are going to create a test for the compute_project_os_login_enabled check
class Test_compute_project_os_login_enabled:
def test_one_compliant_project(self):
# Import the service resource model to create the mocked object
from prowler.providers.gcp.services.compute.compute_service import Project
# Create the custom Project object to be tested
project = Project(
id=GCP_PROJECT_ID,
enable_oslogin=True,
)
# Mocked client with MagicMock
compute_client = mock.MagicMock
compute_client.project_ids = [GCP_PROJECT_ID]
compute_client.projects = [project]
# In this scenario we have to mock the app_client from the check to enforce that the compute_client used is the one created above
# And also is mocked the return value of get_global_provider function to return our GCP mocked provider defined in fixtures
from prowler.providers.gcp.services.compute.compute_project_os_login_enabled.compute_project_os_login_enabled import (
compute_project_os_login_enabled,
)
check = compute_project_os_login_enabled()
result = check.execute()
assert len(result) == 1
assert result[0].status == "FAIL"
assert search(
f"Project {project.id} does not have OS Login enabled",
result[0].status_extended,
)
assert result[0].resource_id == project.id
assert result[0].location == "global"
assert result[0].project_id == GCP_PROJECT_ID
```
### Services
For testing Google Cloud Services, we have to follow the same logic as with the Google Cloud checks. We still mocking all API calls, but in this case, every API call to set up an attribute is defined in [fixtures file](https://github.com/prowler-cloud/prowler/blob/master/tests/providers/gcp/gcp_fixtures.py) in `mock_api_client` function. Remember that EVERY method of a service must be tested.
The following code shows a real example of a testing class, but it has more comments than usual for educational purposes.
```python title="BigQuery Service Test"
# We need to import the unittest.mock.patch to allow us to patch some objects
# not to use shared ones between test, hence to isolate the test
from unittest.mock import patch
# Import the class needed from the service file
from prowler.providers.gcp.services.bigquery.bigquery_service import BigQuery
# Necessary constans and functions from fixtures file
from tests.providers.gcp.gcp_fixtures import (
GCP_PROJECT_ID,
mock_api_client,
mock_is_api_active,
set_mocked_gcp_provider,
)
class TestBigQueryService:
# Only method needed to test full service
def test_service(self):
# In this case we are mocking the __is_api_active__ to ensure our mocked project is used
Now in the fixture file we have to mock this call in our `MagicMock` client in the function `mock_api_client`. The best way to mock
is following the actual format, add one function where the client is passed to be changed, the format of this function name must be
`mock_api_<endpoint>_calls` (*endpoint* refers to the first attribute pointed after *client*).
In the example of BigQuery the function is called `mock_api_dataset_calls`. And inside of this function we found an assignation to
be used in the `__get_datasets__` method in BigQuery class:
```python
# Mocking datasets
dataset1_id = str(uuid4())
dataset2_id = str(uuid4())
client.datasets().list().execute.return_value = {
"datasets": [
{
"datasetReference": {
"datasetId": "unique_dataset1_name",
"projectId": GCP_PROJECT_ID,
},
"id": dataset1_id,
"location": "US",
},
{
"datasetReference": {
"datasetId": "unique_dataset2_name",
"projectId": GCP_PROJECT_ID,
},
"id": dataset2_id,
"location": "EU",
},
]
}
```
## Azure
### Checks
For the Azure Provider we don't have any library to mock out the API calls we use. So in this scenario we inject the objects in the service client using [MagicMock](https://docs.python.org/3/library/unittest.mock.html#unittest.mock.MagicMock).
The following code shows how to use MagicMock to create the service objects for a Azure check test. It is a real example adapted for informative purposes.
For testing Azure services, we have to follow the same logic as with the Azure checks. We still mock all the API calls, but in this case, every method that uses an API call to set up an attribute is mocked with the [patch](https://docs.python.org/3/library/unittest.mock.html#unittest.mock.patch) decorator at the beginning of the class. Remember that every method of a service MUST be tested.
The following code shows a real example of a testing class, but it has more comments than usual for educational purposes.
```python title="AppInsights Service Test"
# We need to import the unittest.mock.patch to allow us to patch some objects
# not to use shared ones between test, hence to isolate the test
from unittest.mock import patch
# Import the models needed from the service file
from prowler.providers.azure.services.appinsights.appinsights_service import (
AppInsights,
Component,
)
# Import some constans values needed in almost every check
from tests.providers.azure.azure_fixtures import (
AZURE_SUBSCRIPTION_ID,
set_mocked_azure_provider,
)
# Function to mock the service function __get_components__, this function task is to return a possible value that real function could returns
def mock_appinsights_get_components(_):
return {
AZURE_SUBSCRIPTION_ID: {
"app_id-1": Component(
resource_id="/subscriptions/resource_id",
resource_name="AppInsightsTest",
location="westeurope",
)
}
}
# Patch decorator to use the mocked function instead the function with the real API call
Prowler has been written in Python using the [AWS SDK (Boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html#) and [Azure SDK](https://learn.microsoft.com/en-us/python/api/overview/azure/?view=azure-python).
Prowler has been written in Python using the [AWS SDK (Boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html#), [Azure SDK](https://azure.github.io/azure-sdk-for-python/) and [GCP API Python Client](https://github.com/googleapis/google-api-python-client/).
## AWS
Since Prowler uses AWS Credentials under the hood, you can follow any authentication method as described [here](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-quickstart.html#cli-configure-quickstart-precedence).
### AWS Authentication
### Authentication
Make sure you have properly configured your AWS-CLI with a valid Access Key and Region or declare AWS variables properly (or instance profile/role):
Those credentials must be associated to a user or role with proper permissions to do all checks. To make sure, add the following AWS managed policies to the user or role being used:
> Moreover, some read-only additional permissions are needed for several checks, make sure you attach also the custom policy [prowler-additions-policy.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-additions-policy.json) to the role you are using.
???+ note
Moreover, some read-only additional permissions are needed for several checks, make sure you attach also the custom policy [prowler-additions-policy.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-additions-policy.json) to the role you are using. If you want Prowler to send findings to [AWS Security Hub](https://aws.amazon.com/security-hub), make sure you also attach the custom policy [prowler-security-hub.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-security-hub.json).
> If you want Prowler to send findings to [AWS Security Hub](https://aws.amazon.com/security-hub), make sure you also attach the custom policy [prowler-security-hub.json](https://github.com/prowler-cloud/prowler/blob/master/permissions/prowler-security-hub.json).
### Multi-Factor Authentication
If your IAM entity enforces MFA you can use `--mfa` and Prowler will ask you to input the following values to get a new session:
- ARN of your MFA device
- TOTP (Time-Based One-Time Password)
## Azure
Prowler for azure supports the following authentication types:
Prowler for Azure supports the following authentication types:
- Service principal authentication by environment variables (Enterprise Application)
If you try to execute Prowler with the `--sp-env-auth` flag and those variables are empty or not exported, the execution is going to fail.
### AZ CLI / Browser / Managed Identity authentication
The other three cases does not need additional configuration, `--az-cli-auth` and `--managed-identity-auth` are automated options,`--browser-auth`needs the user to authenticate using the default browser to start the scan.
The other three cases does not need additional configuration, `--az-cli-auth` and `--managed-identity-auth` are automated options. To use`--browser-auth` the user needs to authenticate against Azure using the default browser to start the scan, also `tenant-id` is required.
### Permissions
To use each one you need to pass the proper flag to the execution. Prowler fro Azure handles two types of permission scopes, which are:
To use each one you need to pass the proper flag to the execution. Prowler for Azure handles two types of permission scopes, which are:
- **Azure Active Directory permissions**: Used to retrieve metadata from the identity assumed by Prowler and future AAD checks (not mandatory to have access to execute the tool)
- **Microsoft Entra ID permissions**: Used to retrieve metadata from the identity assumed by Prowler (not mandatory to have access to execute the tool).
- **Subscription scope permissions**: Required to launch the checks against your resources, mandatory to launch the tool.
#### Azure Active Directory scope
#### Microsoft Entra ID scope
Azure Active Directory (AAD) permissions required by the tool are the following:
Microsoft Entra ID (AAD earlier) permissions required by the tool are the following:
- `Directory.Read.All`
- `Policy.Read.All`
- `UserAuthenticationMethod.Read.All`
The best way to assign it is through the azure web console:
The best way to assign it is through the Azure web console:
1. Access to Microsoft Entra ID
2. In the left menu bar, go to "App registrations"
3. Once there, in the menu bar click on "+ New registration" to register a new application
4. Fill the "Name, select the "Supported account types" and click on "Register. You will be redirected to the applications page.

4. Select the new application
5. In the left menu bar, select "API permissions"
6. Then click on "+ Add a permission" and select "Microsoft Graph"
7. Once in the "Microsoft Graph" view, select "Application permissions"
8. Finally, search for "Directory", "Policy" and "UserAuthenticationMethod" select the following permissions:
Regarding the subscription scope, Prowler by default scans all the subscriptions that is able to list, so it is required to add the following RBAC builtin roles per subscription to the entity that is going to be assumed by the tool:
Regarding the subscription scope, Prowler by default scans all the subscriptions that is able to list, so it is required to add the following RBAC builtin roles per subscription to the entity that is going to be assumed by the tool:
- `Security Reader`
- `Reader`
To assign this roles, follow the instructions:
1. Access your subscription, then select your subscription.
2. Select "Access control (IAM)".
3. In the overview, select "Roles"

4. Click on "+ Add" and select "Add role assignment"
5. In the search bar, type `Security Reader`, select it and click on "Next"
6. In the Members tab, click on "+ Select members" and add the members you want to assign this role.
7. Click on "Review + assign" to apply the new role.
*Repeat these steps for `Reader` role*
## Google Cloud
### Authentication
Prowler will follow the same credentials search as [Google authentication libraries](https://cloud.google.com/docs/authentication/application-default-credentials#search_order):
2. [User credentials set up by using the Google Cloud CLI](https://cloud.google.com/docs/authentication/application-default-credentials#personal)
3. [The attached service account, returned by the metadata server](https://cloud.google.com/docs/authentication/application-default-credentials#attached-sa)
Those credentials must be associated to a user or service account with proper permissions to do all checks. To make sure, add the `Viewer` role to the member associated with the credentials.
???+ note
By default, `prowler` will scan all accessible GCP Projects, use flag `--project-ids` to specify the projects to be scanned.
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