Prowler Sdk Check logo

Prowler Sdk Check

OrganizationPopular
prowler-cloud
prowler-sdk-check

Creates Prowler security checks following SDK architecture patterns. Trigger: When creating or updating a Prowler SDK security check (implementation + metadata) for any provider (AWS, Azure, GCP, K8s, GitHub, etc.).

Overview

Publisherprowler-cloud
Repositoryprowler
Skill nameprowler-sdk-check
Stars
14.8K
Forks
2.4K
Bundled files
7
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by prowler-cloud on GitHub. Read the source before you install it.

Installation

Install the Prowler Sdk Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/prowler-cloud/prowler.git /tmp/prowler
mkdir -p .claude/skills
cp -r /tmp/prowler/skills/prowler-sdk-check .claude/skills/prowler-sdk-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prowler Sdk Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Prowler Sdk Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Prowler Sdk Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Check Structure

text
prowler/providers/{provider}/services/{service}/{check_name}/
├── __init__.py
├── {check_name}.py
└── {check_name}.metadata.json

Step-by-Step Creation Process

1. Prerequisites

  • Verify check doesn't exist: Search prowler/providers/{provider}/services/{service}/
  • Ensure provider and service exist - create them first if not
  • Confirm service has required methods - may need to add/modify service methods to get data

2. Create Check Files

bash
mkdir -p prowler/providers/{provider}/services/{service}/{check_name}
touch prowler/providers/{provider}/services/{service}/{check_name}/__init__.py
touch prowler/providers/{provider}/services/{service}/{check_name}/{check_name}.py
touch prowler/providers/{provider}/services/{service}/{check_name}/{check_name}.metadata.json

3. Implement Check Logic

python
from prowler.lib.check.models import Check, Check_Report_{Provider}
from prowler.providers.{provider}.services.{service}.{service}_client import {service}_client

class {check_name}(Check):
    """Ensure that {resource} meets {security_requirement}."""
    def execute(self) -> list[Check_Report_{Provider}]:
        """Execute the check logic.

        Returns:
            A list of reports containing the result of the check.
        """
        findings = []
        for resource in {service}_client.{resources}:
            report = Check_Report_{Provider}(metadata=self.metadata(), resource=resource)
            report.status = "PASS" if resource.is_compliant else "FAIL"
            report.status_extended = f"Resource {resource.name} compliance status."
            findings.append(report)
        return findings

4. Create Metadata File

See complete schema below and assets/ folder for complete templates. For detailed field documentation, see references/metadata-docs.md.

5. Verify Check Detection

bash
uv run python prowler-cli.py {provider} --list-checks | grep {check_name}

6. Run Check Locally

bash
uv run python prowler-cli.py {provider} --log-level ERROR --verbose --check {check_name}

7. Create Tests

See prowler-test-sdk skill for test patterns (PASS, FAIL, no resources, error handling).


Check Naming Convention

text
{service}_{resource}_{security_control}

Examples:

  • ec2_instance_public_ip_disabled
  • s3_bucket_encryption_enabled
  • iam_user_mfa_enabled

Metadata Schema (COMPLETE)

json
{
  "Provider": "aws",
  "CheckID": "{check_name}",
  "CheckTitle": "Human-readable title",
  "CheckType": [
    "Software and Configuration Checks/AWS Security Best Practices",
    "Software and Configuration Checks/Industry and Regulatory Standards/AWS Foundational Security Best Practices"
  ],
  "ServiceName": "{service}",
  "SubServiceName": "",
  "ResourceIdTemplate": "",
  "Severity": "low|medium|high|critical",
  "ResourceType": "AwsEc2Instance|Other",
  "ResourceGroup": "security|compute|storage|network",
  "Description": "**Bold resource name**. Detailed explanation of what this check evaluates and why it matters.",
  "Risk": "What happens if non-compliant. Explain attack vectors, data exposure risks, compliance impact.",
  "RelatedUrl": "",
  "AdditionalURLs": [
    "https://docs.aws.amazon.com/..."
  ],
  "Remediation": {
    "Code": {
      "CLI": "aws {service} {command} --option value",
      "NativeIaC": "```yaml\nResources:\n  Resource:\n    Type: AWS::{Service}::{Resource}\n    Properties:\n      Key: value  # This line fixes the issue\n```",
      "Other": "1. Console steps\n2. Step by step",
      "Terraform": "```hcl\nresource \"aws_{service}_{resource}\" \"example\" {\n  key = \"value\"  # This line fixes the issue\n}\n```"
    },
    "Recommendation": {
      "Text": "Detailed recommendation for remediation.",
      "Url": "https://hub.prowler.com/check/{check_name}"
    }
  },
  "Categories": [
    "identity-access",
    "encryption",
    "logging",
    "forensics-ready",
    "internet-exposed",
    "trust-boundaries"
  ],
  "DependsOn": [],
  "RelatedTo": [],
  "Notes": ""
}

Required Fields

FieldDescription
ProviderProvider name: aws, azure, gcp, kubernetes, github, m365
CheckIDMust match class name and folder name
CheckTitleHuman-readable title
Severitylow, medium, high, critical
ServiceNameService being checked
DescriptionWhat the check evaluates
RiskSecurity impact of non-compliance
Remediation.Code.CLICLI fix command
Remediation.Recommendation.TextHow to fix

Severity Guidelines

SeverityWhen to Use
criticalDirect data exposure, RCE, privilege escalation
highSignificant security risk, compliance violation
mediumDefense-in-depth, best practice
lowInformational, minor hardening

Check Report Statuses

StatusWhen to Use
PASSResource is compliant
FAILResource is non-compliant
MANUALRequires human verification, or the data needed to evaluate the resource could not be retrieved

Permission / availability errors are NOT findings

Never set FAIL because an API call failed (missing permission or scope, API not enabled, feature not licensed, data unavailable). That is a scan-configuration problem, not a security issue, and it surfaces as a misleading high-severity finding.

  • Service: log the error and expose it distinctly from an empty result (None instead of [], an *_error attribute, or a *_lookup_failed set). Only treat real access errors this way; a 404/not-found usually means "not configured" and IS a legitimate FAIL, and a definitively disabled API is a legitimate FAIL when the API's activation is itself the audited control (e.g. GCP Access Approval).
  • Check: emit ONE tenant/account/project/subscription-level MANUAL finding (not one per resource) whose status_extended says the check cannot be evaluated and names the required permission/API/license.
  • Do not touch report.check_metadata.Severity to hide it.
python
if <service>_client.<data> is None:
    report = CheckReport<Provider>(metadata=self.metadata(), resource={})
    report.resource_name = "<Tenant-level resource>"
    report.resource_id = "<stable-id>"
    report.status = "MANUAL"
    report.status_extended = "Cannot evaluate <requirement>: <data> could not be retrieved. Verify that <permission> is granted to the scanning identity."
    return [report]

Common Patterns

AWS Check with Regional Resources

python
from prowler.lib.check.models import Check, Check_Report_AWS
from prowler.providers.aws.services.s3.s3_client import s3_client

class s3_bucket_encryption_enabled(Check):
    def execute(self) -> list[Check_Report_AWS]:
        findings = []
        for bucket in s3_client.buckets.values():
            report = Check_Report_AWS(metadata=self.metadata(), resource=bucket)
            if bucket.encryption:
                report.status = "PASS"
                report.status_extended = f"S3 bucket {bucket.name} has encryption enabled."
            else:
                report.status = "FAIL"
                report.status_extended = f"S3 bucket {bucket.name} does not have encryption enabled."
            findings.append(report)
        return findings

Check with Multiple Conditions

python
from prowler.lib.check.models import Check, Check_Report_AWS
from prowler.providers.aws.services.ec2.ec2_client import ec2_client

class ec2_instance_hardened(Check):
    def execute(self) -> list[Check_Report_AWS]:
        findings = []
        for instance in ec2_client.instances:
            report = Check_Report_AWS(metadata=self.metadata(), resource=instance)

            issues = []
            if instance.public_ip:
                issues.append("has public IP")
            if not instance.metadata_options.http_tokens == "required":
                issues.append("IMDSv2 not enforced")

            if issues:
                report.status = "FAIL"
                report.status_extended = f"Instance {instance.id} {', '.join(issues)}."
            else:
                report.status = "PASS"
                report.status_extended = f"Instance {instance.id} is properly hardened."

            findings.append(report)
        return findings

Commands

bash
# Verify detection
uv run python prowler-cli.py {provider} --list-checks | grep {check_name}

# Run check
uv run python prowler-cli.py {provider} --log-level ERROR --verbose --check {check_name}

# Run with specific profile/credentials
uv run python prowler-cli.py aws --profile myprofile --check {check_name}

# Run multiple checks
uv run python prowler-cli.py {provider} --check {check1} {check2} {check3}

Resources

  • Templates: See assets/ for complete check and metadata templates (AWS, Azure, GCP)
  • Documentation: See references/metadata-docs.md for official Prowler Developer Guide links

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Prowler Sdk Check AI skill do?

Creates Prowler security checks following SDK architecture patterns. Trigger: When creating or updating a Prowler SDK security check (implementation + metadata) for any provider (AWS, Azure, GCP, K8s, GitHub, etc.).

Why use Prowler Sdk Check on TypingMind?

Because you install it once and use it with any model. Prowler Sdk Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Prowler Sdk Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prowler-cloud/prowler/tree/master/skills/prowler-sdk-check. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Prowler Sdk Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Prowler Sdk Check?

As many as you like. As long as a model supports skills, you can use Prowler Sdk Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prowler Sdk Check AI skill free?

Yes. It is published on GitHub by prowler-cloud under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇