Evidence App

Description

This serverless web application is used by Sherlock's blue team to import evidence data, generate MD5 and SHA1 hashes of the uploaded files, and save the files in a safe location.

Application Diagram

Deployment

Terraform

1. Pre-requisites:

   • Terraform 1.2.2+

   • AWS Command Line Interface

   • Git

   • Command-line environment (e.g., Windows Terminal, Linux Terminal, macOS Terminal, AWS CloudShell)

2. Clone this repository to your local system/CloudShell and cd to the newly-cloned directory.

   git clone https://github.com/bluemountaincyber/evidence-app.git
   cd evidence-app

3. Use Terraform to initialize and deploy the included Infrastructure as Code (IaC). The deployment should take around 5 minutes.

   terraform init
   terraform apply # Answer 'yes' when prompted

CloudFormation

1. Pre-requisites:

   • AWS CLI Tools

   • jq

   • Git

   • Linux Command-line environment (e.g., Linux Terminal, macOS Terminal, AWS CloudShell)

2. Clone this repository to your local system/CloudShell and cd to the newly-cloned directory.

   git clone https://github.com/bluemountaincyber/evidence-app.git
   cd evidence-app

3. Use the provided cloudformation-deploy.sh script to deploy the CloudFormation template (cloudformation.yaml) and load the web content. The deployment should take around 5 minutes.

   ./cloudformation-deploy.sh

Using the Application

1. Navigate to the URL shown in your terminal at the end of the deployment (e.g., https://d16krrq07nhrmy.cloudfront.net).

2. When you arrive, you will find a table containing a sample evidence file name (EICAR.txt), MD5 hash (44d88612fea8a8f36de82e1278abb02f), and SHA1 hash (3395856ce81f2b7382dee72602f798b642f14140).

   

3. If you wish to add your own files to the evidence app, click the Choose File button, select your file to upload, and click the Submit button.

   • Upon upload the file will be stored in an Amazon S3 bucket in your account which begins with the prefix evidence-.

   • The metadata (file name, MD5 hash, and SHA1 hash) is generated and stored in an Amazon DynamoDB table called evidence.

Workbook Documentation

This section describes how to serve the SANS Workshop exercise content.

Pre-requisites

• Python 3.6+
• Python pip

Serving the Workbook

1. From a terminal on your local system, navigate to the workbook directory.

2. Create a virtual environment called .venv.

   python3 -m venv .venv

3. Activate the virtual environment.

   . .venv/bin/activate

4. Install required pip packages.

   pip3 install -r requirements.txt

5. Serve workbook with mkdocs.

   mkdocs serve

6. The workbook is now available at http://localhost:8000.

7. When finished with the workbook, type Ctrl-C in your terminal and then deactivate the virtual environment like so:

   deactivate

Workshop Slides

The workshop slides are available by opening the file at presentation/presentation.html in your web browser or by downloading and opening the presentation/presentation.pdf PDF file.