This project contains code which allows an inexperienced user to easily (one click) upload forensics evidence (such as some information about the system, a full disk image as well as the system's firmware, if supported) from a target device (that will boot on an external device containing the code) to Google Cloud Storage.

It supports configuring what artifacts to collect and which Cloud credentials to use.

This is not an officially supported Google product.

In the tools directory, the script remaster.sh help you with the process of:

• Creating a bootable USB disk image with the required dependencies
• Make sure the image will boot on EFI enabled systems, as well as install third-party input drivers for latest MacBook
• Create a GCS bucket to receive the evidence, as well as a Service Account with the proper roles & ACL.
• Make an icon on the system's Desktop with a clickable icon to start the acquisition process.

It needs as input :

• a Xubuntu 20.04 ISO (won't work with non-XUbuntu, untested with versions different than 20.04)
• the name of your GCP project
• the name of the GCS bucket (remember those need to be globally unique)

You need to have installed the Google Cloud SDK and have SetUp the environment and logged in. Then run:

bash tools/remaster.sh \
  --project some-forensics-project-XYZ \
  --bucket giftstick-uploads-XYZ
  --source_iso xubuntu-20.04-desktop-amd64.iso

First, the script needs credentials (for example, of a Service Account) that provide the following roles (see IAM roles):

• roles/storage.objectCreator, to be able to create (but not overwrite) new storage objects,
• (optional) roles/logging.logWriter for the StackDriver logging system.

These credentials needs to be downloaded and saved as a JSON file. For example, using a Service Account named [email protected], you can create a new key and save it as credentials.json:

gcloud iam service-accounts --project giftstick-project keys create \
        --iam-account "[email protected]" \
        credentials.json

Now pull the code and install dependencies

git clone https://github.com/google/GiftStick
cd GiftStick
pip3 install -r requirements.txt

Unfortunately, because of boto/boto#3699, some patches are required to work in a Python3 environment:

$ boto_dir=$(python -c "import boto; print(boto.__path__[0])")
$ patch -p0 "${boto_dir}/connection.py" config/patches/boto_pr3561_connection.py.patch
$ patch -p0 "${boto_dir}/s3/key.py" config/patches/boto_pr3561_key.py.patch

Once you have booted the system to acquire evidence from that newly created USB stick, and upload it to a GCS url gs://giftstick-bucket/forensics_evidence/ you can run the acquisition script this way:

cd auto_forensicate
sudo python auto_forensicate.py \
    --gs_keyfile=credentials.json \
    --logging stdout \
    --acquire all \
    gs://giftstick-bucket/forensics_evidence/

You'll then get the following hierarchy in your GCS bucket:

gs://giftstick-bucket/forensics_evidence/20181104-1543/SYSTEM_SERIAL/system_info.txt
gs://giftstick-bucket/forensics_evidence/20181104-1543/SYSTEM_SERIAL/stamp.json
gs://giftstick-bucket/forensics_evidence/20181104-1543/SYSTEM_SERIAL/Disks/
gs://giftstick-bucket/forensics_evidence/20181104-1543/SYSTEM_SERIAL/Disks/sda.hash
gs://giftstick-bucket/forensics_evidence/20181104-1543/SYSTEM_SERIAL/Disks/sda.image

The auto_acquisition scripts need Python3 and have been tested to work with 20.04 LTS version of Xubuntu. Previous versions should still work but are not actively supported.

The following packages should be installed in the system you're booting into:

• sudo apt install dcfldd python-pip zenity
• For Chipsec (optional) apt install python-dev libffi-dev build-essential gcc nasm

Currently the script uploads the following data:

• System information (output of dmidecode)
• For each block device that is most likely an internal disk:
  • all the bytes
  • hashes
  • the device's information (output of udevadm)
• The system's firmware, dumped with Chipsec

It also can upload a folder (for example a mounted filesystem) with --acquire directory. In this case, the script will build a .tar file, and upload it alongside a corresponding .timeline, which is a bodyfile compatible file generated with the find command (and stat, if run on MacOS).

Some answers to Frequenly Asked Questions can be found here