Grepmarx | A Source Code Static Analysis Platform For AppSec Enthusiasts

Grepmarx

Grepmarx - Application Security Platform

Grepmarx is a web application providing a single platform to quickly understand, analyze and identify vulnerabilities in possibly large and unknown code bases.

Features

SAST (Static Analysis Security Testing) capabilities:

  • Multiple languages support: C/C++, C#, Go, HTML, Java, Kotlin, JavaScript, TypeScript, OCaml, PHP, Python, Ruby, Bash, Rust, Scala, Solidity, Terraform, Swift
  • Multiple frameworks support: Spring, Laravel, Symfony, Django, Flask, Node.js, jQuery, Express, Angular…
  • 1600+ existing analysis rules
  • Easily extend analysis rules using Semgrep syntax: https://semgrep.dev/editor
  • Manage rules in rule packs to tailor code scanning

SCA (Software Composition Analysis) capabilities:

  • Multiple package-dependency formats support: NPM, Maven, Gradle, Composer, pip, Gopkg, Gem, Cargo, NuPkg, CSProj, PubSpec, Cabal, Mix, Conan, Clojure, Docker, GitHub Actions, Jenkins HPI, Kubernetes
  • SBOM (Software Bill-of-Materials) generation (CycloneDX compliant)

Extra

  • Analysis workbench designed to efficiently browse scan results
  • Scan code that doesn’t compile
  • Comprehensive LOC (Lines of Code) counter
  • Inspector: automatic application features discovery
  • … and a Dark Mode

Screenshots

Scan customization Analysis workbench Rule pack edition
Scan customization Analysis workbench Rule pack edition

Execution

Grepmarx is provided with a configuration to be executed in Docker and Gunicorn.

Docker execution


Make sure you have docker-composer installed on the system, and the docker daemon is running. The application can then be easily executed in a docker container. The steps:

Get the code

$ git clone https://github.com/Orange-Cyberdefense/grepmarx.git $ cd grepmarx

Start the app in Docker

$ sudo docker-compose pull && sudo docker-compose build && sudo docker-compose up -d

Visit http://localhost:5000 in your browser. The app should be up & running.

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Gunicorn


Gunicorn ‘Green Unicorn’ is a Python WSGI HTTP Server for UNIX. A supervisor configuration file is provided to start it along with the required Celery worker (used for security scans queuing).

Install using pip

$ pip install gunicorn supervisor

Start the app using gunicorn binary

$ supervisord -c supervisord.conf

Visit http://localhost:8001 in your browser. The app should be up & running.

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Build from sources

Get the code

$ git clone https://github.com/Orange-Cyberdefense/grepmarx.git $ cd grepmarx

Install virtualenv modules

$ virtualenv env $ source env/bin/activate

Install Python modules

$ # SQLite Database (Development) $ pip3 install -r requirements.txt $ # OR with PostgreSQL connector (Production) $ # pip install -r requirements-pgsql.txt

Install additionnal requirements

Dependency scan (cdxgen / depscan) requirements $ sudo apt install npm openjdk-17-jdk maven gradle golang composer $ sudo npm install -g @cyclonedx/cdxgen $ pip install appthreat-depscan

A Redis server is required to queue security scans. Install the redis package with your favorite distro package manager, then:

$ redis-server

Set the FLASK_APP environment variable

$ export FLASK_APP=run.py $ # Set up the DEBUG environment $ # export FLASK_ENV=development

Start the celery worker process

$ celery -A app.celery_worker.celery worker --pool=prefork --loglevel=info --detach

Start the application (development mode)

$ # --host=0.0.0.0 - expose the app on all network interfaces (default 127.0.0.1) $ # --port=5000 - specify the app port (default 5000) $ flask run --host=0.0.0.0 --port=5000

Access grepmarx in browser: http://127.0.0.1:5000/

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Credits & Links

GitHub:

3 Likes