prowler

This repo hosts Prowler OSS (CLI and Local Server). Prowler is the world’s most widely used open-source cloud security platform that automates security and compliance across any cloud environment for Humans and AI Agents.

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Quick Overview

Prowler is an open-source security tool designed to perform AWS security best practices assessments, audits, incident response, continuous monitoring, hardening, and forensics readiness. It contains hundreds of controls covering CIS, PCI-DSS, ISO27001, GDPR, HIPAA, FFIEC, SOC2, AWS FTR, ENS, and custom security frameworks.

Pros

Comprehensive security assessment with 300+ controls across multiple compliance frameworks
Supports multi-account and multi-region scans
Integrates with various security tools and platforms (e.g., Amazon Security Hub, Slack, Jira)
Regularly updated to include the latest AWS services and security best practices

Cons

Primarily focused on AWS, limiting its use for multi-cloud environments
Can be resource-intensive when scanning large environments
Requires careful configuration to avoid false positives
Learning curve for customizing checks and interpreting results

Getting Started

To get started with Prowler, follow these steps:

Install Prowler:

pip install prowler

Configure AWS credentials:

aws configure

Run a basic scan:

prowler aws

For more advanced usage and customization options, refer to the official documentation at https://github.com/prowler-cloud/prowler.

Competitor Comparisons

trivy

37,228

Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more

Pros of Trivy

Broader scope: Scans containers, filesystems, and git repositories for vulnerabilities and misconfigurations
Faster scanning speed, especially for large container images
Supports multiple operating systems and package managers

Cons of Trivy

Less comprehensive cloud security checks compared to Prowler
Primarily focused on vulnerability scanning rather than compliance auditing
May require additional tools for complete cloud infrastructure assessment

Code Comparison

Trivy CLI command:

trivy image alpine:3.10

Prowler CLI command:

./prowler aws

Trivy focuses on scanning specific targets like container images, while Prowler is designed to perform comprehensive security assessments of AWS environments.

Trivy excels in vulnerability scanning across various platforms and artifacts, making it ideal for DevSecOps pipelines. Prowler, on the other hand, specializes in cloud security auditing and compliance checks, particularly for AWS environments.

Both tools are valuable in their respective domains, with Trivy offering broader vulnerability scanning capabilities and Prowler providing deeper cloud security insights.

checkov

8,936

Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.

Pros of Checkov

Supports multiple cloud providers and IaC tools (AWS, Azure, GCP, Terraform, CloudFormation, Kubernetes, etc.)
Offers a wide range of pre-built policies and custom policy creation
Integrates well with CI/CD pipelines and provides clear, actionable output

Cons of Checkov

May have a steeper learning curve for users new to IaC security scanning
Can produce false positives in some scenarios, requiring manual verification
Limited focus on runtime security checks compared to Prowler

Code Comparison

Checkov:

from checkov.common.models.enums import CheckResult, CheckCategories
from checkov.terraform.checks.resource.base_resource_check import BaseResourceCheck

class S3BucketVersioning(BaseResourceCheck):
    def __init__(self):
        name = "Ensure S3 bucket has versioning enabled"
        check_id = "CKV_AWS_21"

Prowler:

#!/usr/bin/env bash

# Prowler - the handy cloud security tool (https://github.com/prowler-cloud/prowler)

PROWLER_VERSION="${PROWLER_VERSION:-$(cat ${PROWLER_DIR}/VERSION)}"

Both tools aim to enhance cloud security, but Checkov focuses more on Infrastructure as Code (IaC) scanning across multiple providers, while Prowler specializes in AWS security assessments with some multi-cloud capabilities. Checkov's Python-based approach allows for more flexible policy creation, while Prowler's bash-based structure may be more familiar to system administrators and DevOps engineers.

gitleaks

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Pros of Gitleaks

Specialized in detecting secrets and sensitive information in git repositories
Supports scanning local repositories, GitHub organizations, and GitLab groups
Highly customizable with regex patterns and rules

Cons of Gitleaks

Limited to secret detection, lacking broader security assessment capabilities
May produce false positives, requiring manual review of results
Doesn't provide remediation suggestions or security best practices

Code Comparison

Gitleaks (Go):

func (d *Detector) Detect(src string) ([]DetectResult, error) {
    var results []DetectResult
    for _, r := range d.Rules {
        matches := r.Regexp.FindAllStringIndex(src, -1)
        for _, match := range matches {
            results = append(results, DetectResult{
                Rule:    r,
                Start:   match[0],
                End:     match[1],
                Secret:  src[match[0]:match[1]],
            })
        }
    }
    return results, nil
}

Prowler (Python):

def run_check(self, check):
    check_metadata = check.metadata()
    if self.audit_info.audit_session_name not in check_metadata.get("excluded_session_names", []):
        finding = check.execute()
        if finding:
            self.findings.append(finding)
    return self.findings

While both tools focus on security, Gitleaks specializes in secret detection within git repositories, whereas Prowler offers a broader range of cloud security assessments, particularly for AWS environments. Gitleaks is more focused and customizable for secret scanning, while Prowler provides a comprehensive security auditing solution for cloud infrastructures.

grype

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A vulnerability scanner for container images and filesystems

Pros of Grype

Focused specifically on vulnerability scanning for container images and filesystems
Faster scanning speed, especially for large container images
Supports a wide range of package ecosystems and vulnerability databases

Cons of Grype

Limited to vulnerability scanning, lacks broader security assessment capabilities
Does not provide cloud infrastructure security checks
Less comprehensive reporting and remediation guidance compared to Prowler

Code Comparison

Grype (scanning a container image):

grype alpine:latest

Prowler (running a security assessment):

./prowler aws

Summary

Grype is a specialized tool for vulnerability scanning in containers and filesystems, offering fast and focused scans across various package ecosystems. It excels in speed and specific vulnerability detection but lacks the broader security assessment capabilities of Prowler.

Prowler, on the other hand, provides a comprehensive security assessment for cloud environments, particularly AWS. It offers a wider range of checks, including compliance and best practices, but may not be as specialized or fast in container vulnerability scanning as Grype.

The choice between these tools depends on the specific security needs of your project: Grype for focused container vulnerability scanning, or Prowler for broader cloud security assessments.

conftest

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Write tests against structured configuration data using the Open Policy Agent Rego query language

Pros of Conftest

More flexible and general-purpose, can be used for various configuration files and policy types
Integrates well with other Open Policy Agent tools and ecosystem
Supports multiple input formats (YAML, JSON, INI, etc.)

Cons of Conftest

Requires learning Rego language for writing policies
Less out-of-the-box functionality for cloud security auditing
May require more setup and configuration for specific use cases

Code Comparison

Prowler (shell script):

./prowler -p custom-profile -r us-east-1

Conftest (policy testing):

conftest test deployment.yaml

Key Differences

Prowler is specifically designed for AWS security auditing, while Conftest is a general-purpose policy testing tool
Prowler provides pre-defined checks and reports, whereas Conftest requires custom policy definitions
Conftest offers more flexibility in terms of input formats and policy types, but may require more initial setup
Prowler is more user-friendly for AWS-specific security assessments, while Conftest has a steeper learning curve but broader applicability

Both tools serve different purposes and can be complementary in a comprehensive security and compliance strategy.

terrascan

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Detect compliance and security violations across Infrastructure as Code to mitigate risk before provisioning cloud native infrastructure.

Pros of Terrascan

Broader scope: Supports multiple IaC tools (Terraform, Kubernetes, Helm, Kustomize, Dockerfiles)
Policy-as-code approach with Rego language for custom rules
Integrates well with CI/CD pipelines and supports various output formats

Cons of Terrascan

Less focus on cloud-specific security checks compared to Prowler
Steeper learning curve for creating custom policies
May require more setup and configuration for comprehensive cloud security audits

Code Comparison

Terrascan (scanning a Terraform file):

terrascan scan -i terraform -f main.tf

Prowler (scanning AWS environment):

./prowler aws

Summary

Terrascan is a versatile IaC security scanner supporting multiple tools, while Prowler specializes in cloud security audits, particularly for AWS. Terrascan offers more flexibility in policy creation but may require more setup for cloud-specific checks. Prowler provides out-of-the-box cloud security audits but is more limited in scope to specific cloud providers.

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README

Prowler is the Open Cloud Security Platform trusted by thousands to automate security and compliance in any cloud environment. With thousands of ready-to-use checks and compliance frameworks, Prowler delivers real-time, customizable monitoring and seamless integrations, making cloud security simple, scalable, and cost-effective for organizations of any size.

The Agentic Cloud Defender

Try Prowler Cloud

Join our Prowler community!

Prowler Cloud demo

Description

Prowler is the worldâs most widely used Open-Source Cloud Security Platform that automates security and compliance across any cloud environment. With thousands of ready-to-use security checks, remediation guidance, and compliance frameworks, Prowler is built to âSecure ANY Cloud at AI Speedâ. Prowler delivers AI-driven, customizable, and easy-to-use assessments, dashboards, reports, and integrations, making cloud security simple, scalable, and cost-effective for organizations of any size.

Prowler includes hundreds of built-in controls to ensure compliance with standards and frameworks, including:

Prowler ThreatScore: Weighted risk prioritization scoring that helps you focus on the most critical security findings first
Industry Standards: CIS, NIST 800, NIST CSF, CISA, and MITRE ATT&CK
Regulatory Compliance and Governance: RBI, FedRAMP, PCI-DSS, and NIS2
Frameworks for Sensitive Data and Privacy: GDPR, HIPAA, and FFIEC
Frameworks for Organizational Governance and Quality Control: SOC2, GXP, and ISO 27001
Cloud-Specific Frameworks: AWS Foundational Technical Review (FTR), AWS Well-Architected Framework, and BSI C5
National Security Standards: ENS (Spanish National Security Scheme) and KISA ISMS-P (Korean)
Custom Security Frameworks: Tailored to your needs

Prowler Cloud & Prowler Local Server

Prowler Cloud and Prowler Local Server, its self-hosted open-source version, are web applications that simplify running Prowler across your cloud provider accounts. They provide a user-friendly interface to visualize the results and streamline your security assessments.

Prowler Cloud Risk Pipeline Threat Map

For more details, refer to the Prowler Local Server documentation

Prowler CLI

prowler <provider>

Prowler CLI Execution

Prowler Local Dashboard

prowler dashboard

Prowler Local Dashboard

Attack Paths

Attack Paths automatically extends every completed AWS scan with a graph that combines Cartography's cloud inventory with Prowler findings. The feature runs in the API worker after each scan.

Two graph backends are supported as the long-lived sink:

Neo4j (default; the Docker Compose files already ship a neo4j service).
Amazon Neptune (cloud-managed; opt-in).

Select the sink with ATTACK_PATHS_SINK_DATABASE (neo4j or neptune; default neo4j).

Note: Cartography ingestion always uses a temporary Neo4j database, regardless of the configured sink. The NEO4J_* variables below must remain set even when ATTACK_PATHS_SINK_DATABASE=neptune.

Neo4j sink

Variable	Description	Default
`NEO4J_HOST`	Hostname used by the API containers.	`neo4j`
`NEO4J_PORT`	Bolt port exposed by Neo4j.	`7687`
`NEO4J_USER` / `NEO4J_PASSWORD`	Credentials with rights to create per-tenant databases.	`neo4j` / `neo4j_password`

Neptune sink

Variable	Description	Default
`NEPTUNE_WRITER_ENDPOINT`	Bolt host for the Neptune writer instance. Required when sink is `neptune`.	empty
`NEPTUNE_READER_ENDPOINT`	Optional reader endpoint for read-only queries. Falls back to the writer when unset.	empty
`NEPTUNE_PORT`	Bolt port exposed by Neptune.	`8182`
`AWS_REGION`	Region the Neptune cluster lives in. Required when sink is `neptune`.	empty

Neptune authenticates with SigV4 using the standard boto3 credential chain. The worker's IAM role (or AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY) supplies the credentials. There is no Neptune password variable.

Every AWS provider scan will enqueue an Attack Paths ingestion job automatically. Other cloud providers will be added in future iterations.

Prowler at a Glance

[!Tip] For the most accurate and up-to-date information about checks, services, frameworks, and categories, visit Prowler Hub.

Provider	Checks	Services	Compliance Frameworks	Categories	Support	Interface
AWS	639	86	47	19	Official	UI, API, CLI
Azure	191	22	21	16	Official	UI, API, CLI
GCP	109	20	19	12	Official	UI, API, CLI
Kubernetes	92	7	8	11	Official	UI, API, CLI
GitHub	24	3	2	5	Official	UI, API, CLI
M365	143	10	6	10	Official	UI, API, CLI
OCI	52	14	5	10	Official	UI, API, CLI
Alibaba Cloud	63	9	6	9	Official	UI, API, CLI
Cloudflare	29	3	2	5	Official	UI, API, CLI
IaC	See `trivy` docs.	N/A	N/A	N/A	Official	UI, API, CLI
MongoDB Atlas	10	3	1	8	Official	UI, API, CLI
LLM	See `promptfoo` docs.	N/A	N/A	N/A	Official	CLI
Image	N/A	N/A	N/A	N/A	Official	UI, API, CLI
Google Workspace	65	11	4	6	Official	UI, API, CLI
OpenStack	34	5	1	9	Official	UI, API, CLI
Vercel	26	6	1	8	Official	UI, API, CLI
Okta	29	8	2	2	Official	UI, API, CLI
Linode Contact us	10	3	1	4	Unofficial	CLI
Huawei Cloud Contact us	25	10	1	6	Unofficial	CLI
E2E Networks Contact us	27	6	0	2	Unofficial	CLI
Scaleway Contact us	1	1	1	1	Unofficial	CLI
StackIT Contact us	8	2	1	3	Unofficial	CLI
NHN	6	2	2	0	Unofficial	CLI

[!Note] The numbers in the table are updated periodically.

[!Note] Use the following commands to list Prowler's available checks, services, compliance frameworks, and categories:

prowler <provider> --list-checks

prowler <provider> --list-services

prowler <provider> --list-compliance

prowler <provider> --list-categories

ð» Installation

Prowler Local Server

Prowler Local Server offers flexible installation methods tailored to various environments:

For detailed instructions on using Prowler Local Server, refer to the usage guide.

Docker Compose

Requirements

Docker Compose installed: https://docs.docker.com/compose/install/.

Commands

macOS/Linux:

VERSION=$(curl -s https://api.github.com/repos/prowler-cloud/prowler/releases/latest | jq -r .tag_name)
curl -sLO "https://raw.githubusercontent.com/prowler-cloud/prowler/refs/tags/${VERSION}/docker-compose.yml"
# Environment variables can be customized in the .env file. Using default values in production environments is not recommended.
curl -sLO "https://raw.githubusercontent.com/prowler-cloud/prowler/refs/tags/${VERSION}/.env"
docker compose up -d

Windows PowerShell:

$VERSION = (Invoke-RestMethod -Uri "https://api.github.com/repos/prowler-cloud/prowler/releases/latest").tag_name
Invoke-WebRequest -Uri "https://raw.githubusercontent.com/prowler-cloud/prowler/refs/tags/$VERSION/docker-compose.yml" -OutFile "docker-compose.yml"
# Environment variables can be customized in the .env file. Using default values in production environments is not recommended.
Invoke-WebRequest -Uri "https://raw.githubusercontent.com/prowler-cloud/prowler/refs/tags/$VERSION/.env" -OutFile ".env"
docker compose up -d

[!WARNING] ð For a secure setup, the API auto-generates a unique key pair, DJANGO_TOKEN_SIGNING_KEY and DJANGO_TOKEN_VERIFYING_KEY, and stores it in ~/.config/prowler-api (non-container) or the bound Docker volume in _data/api (container). Never commit or reuse static/default keys. To rotate keys, delete the stored key files and restart the API.

Once configured, access Prowler Local Server at http://localhost:3000. Sign up using your email and password to get started.

Common Issues with Docker Pull Installation

[!Note] If you want to use AWS role assumption (e.g., with the "Connect assuming IAM Role" option), you may need to mount your local .aws directory into the container as a volume (e.g., - "${HOME}/.aws:/home/prowler/.aws:ro"). There are several ways to configure credentials for Docker containers. See the Troubleshooting section for more details and examples.

You can find more information in the Troubleshooting section.

From GitHub

Requirements

git installed.
uv installed: uv installation.
pnpm installed: pnpm installation.
Docker Compose installed: https://docs.docker.com/compose/install/.

Commands to run the API

git clone https://github.com/prowler-cloud/prowler
cd prowler/api
uv sync
source .venv/bin/activate
set -a
source .env
docker compose up postgres valkey -d
cd src/backend
python manage.py migrate --database admin
gunicorn -c config/guniconf.py config.wsgi:application

After completing the setup, access the API documentation at http://localhost:8080/api/v1/docs.

Commands to run the API Worker

git clone https://github.com/prowler-cloud/prowler
cd prowler/api
uv sync
source .venv/bin/activate
set -a
source .env
cd src/backend
python -m celery -A config.celery worker -l info -E

Commands to run the API Scheduler

git clone https://github.com/prowler-cloud/prowler
cd prowler/api
uv sync
source .venv/bin/activate
set -a
source .env
cd src/backend
python -m celery -A config.celery beat -l info --scheduler django_celery_beat.schedulers:DatabaseScheduler

Commands to run the UI

git clone https://github.com/prowler-cloud/prowler
cd prowler/ui
pnpm install
pnpm run build
pnpm start

Once configured, access Prowler Local Server at http://localhost:3000. Sign up using your email and password to get started.

Pre-commit Hooks Setup

Some pre-commit hooks require tools installed on your system:

Install TruffleHog (secret scanning) â see the official installation options.
Install Hadolint (Dockerfile linting) â see the official installation options.

Prowler CLI

Pip package

Prowler CLI is available as a project in PyPI. Consequently, it can be installed using pip with Python >=3.10, <3.13:

pip install prowler
prowler -v

For further guidance, refer to https://docs.prowler.com

Containers

Available Versions of Prowler CLI

The following versions of Prowler CLI are available, depending on your requirements:

latest: Synchronizes with the master branch. Note that this version is not stable.
v4-latest: Synchronizes with the v4 branch. Note that this version is not stable.
v3-latest: Synchronizes with the v3 branch. Note that this version is not stable.
<x.y.z> (release): Stable releases corresponding to specific versions. See the complete list of Prowler releases.
stable: Always points to the latest release.
v4-stable: Always points to the latest release for v4.
v3-stable: Always points to the latest release for v3.

The container images are available here:

Prowler CLI:
- DockerHub
- AWS Public ECR
Prowler Local Server:
- DockerHub - Prowler UI
- DockerHub - Prowler API

From GitHub

Python >=3.10, <3.13 is required with uv:

git clone https://github.com/prowler-cloud/prowler
cd prowler
uv sync
source .venv/bin/activate
python prowler-cli.py -v

[!IMPORTANT] To clone Prowler on Windows, configure Git to support long file paths by running the following command: git config core.longpaths true.

ð¡ï¸ GitHub Action

The official Prowler GitHub Action runs Prowler scans in your GitHub workflows using the official prowlercloud/prowler Docker image. Scans run on any supported provider, with optional --push-to-cloud to send findings to Prowler Cloud and optional SARIF upload so findings show up in the repo's Security â Code scanning tab and as inline PR annotations.

name: Prowler IaC Scan
on:
  pull_request:

permissions:
  contents: read
  security-events: write
  actions: read

jobs:
  prowler:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - uses: prowler-cloud/prowler@5.25
        with:
          provider: iac
          output-formats: sarif json-ocsf
          upload-sarif: true
          flags: --severity critical high

Full configuration, per-provider authentication, and SARIF examples: Prowler GitHub Action tutorial. Marketplace listing: Prowler Security Scan.

âï¸ High level architecture

Prowler Local Server

Prowler Local Server is composed of four key components:

Prowler UI: A web-based interface, built with Next.js, providing a user-friendly experience for executing Prowler scans and visualizing results.
Prowler API: A backend service, developed with Django REST Framework, responsible for running Prowler scans and storing the generated results.
Prowler SDK: A Python SDK designed to extend the functionality of the Prowler CLI for advanced capabilities.
Prowler MCP Server: A Model Context Protocol server that provides AI tools for Lighthouse, the AI-powered security assistant. This is a critical dependency for Lighthouse functionality.

flowchart TB
    user([User / Security Team])
    cli([Prowler CLI])

    subgraph APP["Prowler Local Server"]
        ui["Prowler UI<br/>(Next.js)"]
        api["Prowler API<br/>(Django REST Framework)"]
        worker["API Worker<br/>(Celery)"]
        beat["API Scheduler<br/>(Celery Beat)"]
        mcp["Prowler MCP Server<br/>(Lighthouse AI tools)"]
    end

    sdk["Prowler SDK<br/>(Python)"]

    subgraph DATA["Data Layer"]
        pg[("PostgreSQL")]
        valkey[("Valkey / Redis")]
        neo4j[("Neo4j")]
    end

    providers["Providers"]

    user --> ui
    user --> cli
    ui -->|REST| api
    ui -->|MCP HTTP| mcp
    mcp -->|REST| api
    api --> pg
    api --> valkey
    beat -->|enqueue jobs| valkey
    valkey -->|dispatch| worker
    worker --> pg
    worker -->|Attack Paths| neo4j
    worker -->|invokes| sdk
    cli --> sdk

    sdk --> providers

Prowler CLI

Running Prowler

Prowler can be executed across various environments, offering flexibility to meet your needs. It can be run from:

Your own workstation
A Kubernetes Job
Google Compute Engine
Azure Virtual Machines (VMs)
Amazon EC2 instances
AWS Fargate or other container platforms
CloudShell

And many more environments.

Architecture

ð¤ AI Skills for Development

Prowler includes a comprehensive set of AI Skills that help AI coding assistants understand Prowler's codebase patterns and conventions.

What are AI Skills?

Skills are structured instructions that give AI assistants the context they need to write code that follows Prowler's standards. They include:

Coding patterns for each component (SDK, API, UI, MCP Server)
Testing conventions (pytest, Playwright)
Architecture guidelines (Clean Architecture, RLS patterns)
Framework-specific rules (React 19, Next.js 15, Django DRF, Tailwind 4)

Available Skills

Category	Skills
Generic	`typescript`, `react-19`, `nextjs-15`, `tailwind-4`, `playwright`, `pytest`, `django-drf`, `zod-4`, `zustand-5`, `ai-sdk-5`
Prowler	`prowler`, `prowler-api`, `prowler-ui`, `prowler-mcp`, `prowler-sdk-check`, `prowler-test-ui`, `prowler-test-api`, `prowler-test-sdk`, `prowler-compliance`, `prowler-provider`, `prowler-pr`, `prowler-docs`

Setup

./skills/setup.sh

This configures skills for AI coding assistants that follow the agentskills.io standard:

Tool	Configuration
Claude Code	`.claude/skills/` (symlink)
OpenCode	`.claude/skills/` (symlink)
Codex (OpenAI)	`.codex/skills/` (symlink)
GitHub Copilot	`.github/skills/` (symlink)
Gemini CLI	`.gemini/skills/` (symlink)

Note: Restart your AI coding assistant after running setup to load the skills. Gemini CLI requires experimental.skills enabled in settings.

ð Documentation

For installation instructions, usage details, tutorials, and the Developer Guide, visit https://docs.prowler.com/

ð License

Prowler is licensed under the Apache License 2.0.

A copy of the License is available at http://www.apache.org/licenses/LICENSE-2.0

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Quick Overview

Pros

Cons

Getting Started

Competitor Comparisons

Pros of Trivy

Cons of Trivy

Code Comparison

Pros of Checkov

Cons of Checkov

Code Comparison

Pros of Gitleaks

Cons of Gitleaks

Code Comparison

Pros of Grype

Cons of Grype

Code Comparison

Summary

Pros of Conftest

Cons of Conftest

Code Comparison

Key Differences

Pros of Terrascan

Cons of Terrascan

Code Comparison

Summary

Convert designs to code with AI

README

Description

Prowler Cloud & Prowler Local Server

Prowler CLI

Prowler Local Dashboard

Attack Paths

Neo4j sink

Neptune sink

Prowler at a Glance

ð» Installation

Prowler Local Server

Docker Compose

Requirements

Commands

Common Issues with Docker Pull Installation

From GitHub

Requirements

Commands to run the API

Commands to run the API Worker

Commands to run the API Scheduler

Commands to run the UI

Pre-commit Hooks Setup

Prowler CLI

Pip package

Containers

Available Versions of Prowler CLI

From GitHub

ð¡ï¸ GitHub Action

âï¸ High level architecture

Prowler Local Server

Prowler CLI

Running Prowler

ð¤ AI Skills for Development

What are AI Skills?

Available Skills

Setup

ð Documentation

ð License

Top Related Projects

Convert designs to code with AI

ð» Installation

ð¡ï¸ GitHub Action

âï¸ High level architecture

ð¤ AI Skills for Development

ð Documentation

ð License