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IaC Scan Runner CLI

Project description

IaC Scan Runner

Service that checks your IaC for issues and vulnerabilities.

GitHub Workflow Status Docker Image Version (latest by date) PyPI Test PyPI

Aspect Information
Tool name IaC Scan Runner
Docker image xscanner/runner
PyPI package iac-scan-runner
Documentation docs
Contact us xopera@xlab.si

Table of Contents

Purpose and description

The IaC Scan Runner is a REST API service used to scan IaC (Infrastructure as Code) package and perform various code checks in order to find possible vulnerabilities and improvements. Explore the docs for more info.

Running

This section explains how to run the REST API.

Run with Docker

You can run the REST API using a public xscanner/runner Docker image as follows:

# run IaC Scan Runner REST API in a Docker container and 
# navigate to localhost:8080/swagger or localhost:8080/redoc
$ docker run --name iac-scan-runner -p 8080:80 xscanner/runner

Or you can build the image locally and run it as follows:

# build Docker container (it will take some time) 
$ docker build -t iac-scan-runner .
# run IaC Scan Runner REST API in a Docker container and 
# navigate to localhost:8080/swagger or localhost:8080/redoc
$ docker run --name iac-scan-runner -p 8080:80 iac-scan-runner

Run from CLI

To run using the IaC Scan Runner CLI:

# install the CLI
$ python3 -m venv .venv && . .venv/bin/activate
(.venv) $ pip install iac-scan-runner
# print OpenAPI specification
(.venv) $ iac-scan-runner openapi
# install prerequisites
(.venv) $ iac-scan-runner install
# run IaC Scan Runner REST API
(.venv) $ iac-scan-runner run

Run from source

To run locally from source:

# install prerequisites
$ python3 -m venv .venv && . .venv/bin/activate
(.venv) $ pip install -r requirements.txt
(.venv) $ ./install-checks.sh
# run IaC Scan Runner REST API (add --reload flag to apply code changes on the way)
(.venv) $ uvicorn src.iac_scan_runner.api:app

License

This work is licensed under the Apache License 2.0.

Contact

You can contact the xOpera team by sending an email to xopera@xlab.si.

Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101000162 (PIACERE).

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