Lyft Cartography Docker Container

I have been meaning to look at Cartography since I saw their talk at BSidesSF last year and I finally had a chance to start looking at it today. One of the first things I noticed was that is was not containerized so I built a quick container for it and decided to document my progress here.

Prerequisites

• AWS CLI (Installed and configured)
• Docker 18.0+

Build The Cartography Container

• Create a local cartography directory.
• Create a Dockerfile and copy this into it:

# syntax = docker/dockerfile:experimental
FROM ubuntu:latest
# Install Python
RUN apt-get update \
  && apt-get install -y python3-pip python3-dev wget apt-utils \
  && cd /usr/local/bin \
  && ln -s /usr/bin/python3 python \
  && pip3 install --upgrade pip
RUN pip install awscli \
    &&  pip install cartography

• In your terminal open the cartography directory.
• Build the container using: DOCKER_BUILDKIT=1 docker build -t cartography .

Run Neo4J Container

docker container run \
  -e NEO4J_AUTH=none \
  -v neo4j-data:/data \
  -p 7474:7474 \
  -p 7687:7687 \
  -d \
  neo4j:3.5.12

Run Cartography Container

docker run --rm -v $HOME/.aws:/root/.aws --net=host cartography cartography --neo4j-uri bolt://127.0.0.1:7687

This step will take a few minutes depending on the size of your environment.

Accessing The Interface

Once the container is done building you can access the web interface at http://127.0.0.1:7474/browser/

Closing Thoughts & ToDo List

• Lyft provides some sample quires here
• I am looking forward to setting this up for multi-cloud environments
• Need to investigate authentication for Neo4J