Red Team tool for exfiltrating files from a target's Google Drive that you have access to, via Google's API.

Related tags

Deep LearningGD-Thief
Overview

GD-Thief

Red Team tool for exfiltrating files from a target's Google Drive that you(the attacker) has access to, via the Google Drive API. This includes includes all shared files, all files from shared drives, and all files from domain drives that the target has access to.

HOW TO

For an illustrated walkthrough, check out my blog post.

Create a new Google Cloud Platform (GCP) project

Steps to get the Google API Access Token needed for connecting to the API

  1. Create a burner Gmail/google account
  2. Login to said account
  3. Navigate to the Google Cloud Console
  4. Next to "Google Cloud Platform," click the "Select a project" Down arrow. A dialog listing current projects appears.
  5. Click New Project. The New Project screen appears.
  6. In the Project Name field, enter a descriptive name for your project.
  7. (Optional) To edit the Project ID, click Edit. The project ID can't be changed after the project is created, so choose an ID that meets your needs for the lifetime of the project.
  8. Click Create. The console navigates to the Dashboard page and your project is created within a few minutes.

Enable a Google Workspace API

  1. Next to "Google Cloud Platform," click the Down arrow and select the project you just created from the dropdown list.
  2. In the top-left corner, click Menu > APIs & Services.
  3. Click Enable APIs and Services. The "Welcome to API Library" page appears.
  4. In the search field, enter "Google Drive".
  5. Click the Google Drive API. The API page appears.
  6. Click Enable. The Overview page appears.

Configure OAuth Consent screen

  1. On the left side of the Overview page click Credentials. The credential page for your project appears.
  2. Click Configure Consent Screen. The "OAuth consent screen" screen appears.
  3. Click the External user type for your app.
  4. Click Create. A second "OAuth consent screen" screen appears.
  5. Fill out the form:
    • Enter an Application Name in the App name field
    • Enter your burner email address in the User support email field.
    • Enter your burner email address in the Developer contact information field.
  6. Click Save and Continue. The "Scopes" page appears.
  7. Click Add or Remove Scopes. The "Update selected scopes" page appears.
  8. Check all of the Google Drive scopes to use in the app. GD scopes cover 2 pages, so click the next page and ensure that you check them all.
  9. Click Update. A list of scopes for your app appears.
  10. Click Save and Continue. The "Edit app registration" page appears.
  11. Click Save and Continue. The "OAuth consent screen" appears.

Create a credential

  1. Click Create Credentials and select OAuth client ID. The "Create OAuth client ID" page appears.
  2. Click the Application type drop-down list and select Desktop Application.
  3. In the name field, type a name for the credential. This name is only shown in the Cloud Console.
  4. Click Create. The OAuth client created screen appears. This screen shows the Client ID and Client secret.
  5. Click OK. The newly created credential appears under "OAuth 2.0 Client IDs."
  6. Click the download button to the right of the newly-created OAuth 2.0 Client ID. This copies a client secret JSON file to your desktop. Note the location of this file.
  7. Rename the client secret JSON file to "credentials.json" and move it to the gd_thief/credentials directory.

Add the victim's Google account to the Application's Test Users

In order to be able to run this script against the victim, you will need to add their Google account to the Test Users list for the App you just created

  1. On the Left side of the screen click OAuth consent screen. You "OAuth Consent Screen" page appears.
  2. Under Test Users click the Add Users button.
  3. Enter the victim's Gmail address in the email address field.
  4. Click the save button.

First Time running gd_thief

Upon gaining access to a Target's Google account, you can run gd_thief

  1. The first time running gd_thief, the script opens a new window prompting you to authorize access to your data:
    1. If you are signed in to multiple Google accounts, you are asked to select one account to use for the authorization. Make sure you select the victim's Google account

Dependencies

Google API Libraries: pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib

Usage:

usage:
python3 gd_thief.py [-h] -m [{dlAll, dlDict[-d <DICTIONARY FILE PATH>]}
	[-t <THREAD COUNT>]

help:

This Module will connect to Google's API using an access token and exfiltrate files
from a target's Google Drive.  It will output exfiltrated files to the ./loot directory

arguments:
        -m [{dlAll, dlDict}],
                --mode [{dlAll, dlDict}]
                The mode of file download
                Can be "dlAll", "dlDict [-d <DICTIONARY FILE PATH>]", or... (More options to come)

optional arguments:
        -d <DICTIONARY FILE PATH>, --dict <DICTIONARY FILE PATH>
                        Path to the dictionary file. Mandatory with download mode"-m, --mode dlDict"
                        You can use the provided dictionary, per example: "-d ./dictionaries/secrets-keywords.txt"
        -t <THREAD COUNT>, --threads <THREAD COUNT>
                        Number of threads. (Too many could exceeed Google's rate limit threshold)

        -h, --help
                show this help message and exit

NOTES:

  • Setting the thread count too high will cause an HTTP 403 "Rate limit exceeded," indicating that the user has reached Google Drive API's maximum request rate.
    • The thread count limit vaires from machine to machine. I've set it to 250 on a Macbook Pro, while 250 was too high for my Windows 10 Desktop

REFERENCES:

TODO:

  1. Threading
  2. Error Checking
  3. Wordlist file content search and download
  4. File type download
  5. Snort Sensitive Data regex file content search and download
  6. Optical Character Recognition (OCR)

Special Thanks:

Thank you to my good friend Cedric Owens for helping me with the threading piece!

Owner
Antonio Piazza
Antonio Piazza
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"

Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr

43 Nov 21, 2022
Studying Python release adoptions by looking at PyPI downloads

Analysis of version adoptions on PyPI We get PyPI download statistics via Google's BigQuery using the pypinfo tool. Usage First you need to get an acc

Julien Palard 9 Nov 04, 2022
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021.

Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f

Bobo Xi 7 Nov 03, 2022
Machine learning, in numpy

numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install

David Bourgin 11.6k Dec 30, 2022
Generic Foreground Segmentation in Images

Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul

Suyog Jain 157 Nov 21, 2022
Iranian Cars Detection using Yolov5s, PyTorch

Iranian Cars Detection using Yolov5 Train 1- git clone https://github.com/ultralytics/yolov5 cd yolov5 pip install -r requirements.txt 2- Dataset ../

Nahid Ebrahimian 22 Dec 05, 2022
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search

CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search This repository is the official implementation of CAPITAL: Optimal Subgrou

Hengrui Cai 0 Oct 19, 2021
Phy-Q: A Benchmark for Physical Reasoning

Phy-Q: A Benchmark for Physical Reasoning Cheng Xue*, Vimukthini Pinto*, Chathura Gamage* Ekaterina Nikonova, Peng Zhang, Jochen Renz School of Comput

29 Dec 19, 2022
一套完整的微博舆情分析流程代码,包括微博爬虫、LDA主题分析和情感分析。

已经将项目的关键文件上传,包含微博爬虫、LDA主题分析和情感分析三个部分。 1.微博爬虫 实现微博评论爬取和微博用户信息爬取,一天大概十万条。 2.LDA主题分析 实现文档主题抽取,包括数据清洗及分词、主题数的确定(主题一致性和困惑度)和最优主题模型的选择(暴力搜索)。 3.情感分析 实现评论文本的

182 Jan 02, 2023
[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021

Pedestron Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection. We provide a list of detec

Irtiza Hasan 594 Jan 05, 2023
A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.

Torch-RecHub A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend. 安装 pip install torch-rechub 主要特性 scikit-learn风格易用

Mincai Lai 67 Jan 04, 2023
This is a clean and robust Pytorch implementation of DQN and Double DQN.

DQN/DDQN-Pytorch This is a clean and robust Pytorch implementation of DQN and Double DQN. Here is the training curve: All the experiments are trained

XinJingHao 15 Dec 27, 2022
Implementation of association rules mining algorithms (Apriori|FPGrowth) using python.

Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in

Pre 2 Nov 10, 2021
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.

CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma

Dong Chen 8 Jun 07, 2022
Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

openpifpaf Continuously tested on Linux, MacOS and Windows: New 2021 paper: OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Te

VITA lab at EPFL 50 Dec 29, 2022
Repository for paper "Non-intrusive speech intelligibility prediction from discrete latent representations"

Non-Intrusive Speech Intelligibility Prediction from Discrete Latent Representations Official repository for paper "Non-Intrusive Speech Intelligibili

Alex McKinney 5 Oct 25, 2022
The open-source and free to use Python package miseval was developed to establish a standardized medical image segmentation evaluation procedure

miseval: a metric library for Medical Image Segmentation EVALuation The open-source and free to use Python package miseval was developed to establish

59 Dec 10, 2022
This is a yolo3 implemented via tensorflow 2.7

YoloV3 - an object detection algorithm implemented via TF 2.x source code In this article I assume you've already familiar with basic computer vision

2 Jan 17, 2022
Unofficial implementation of Pix2SEQ

Unofficial-Pix2seq: A Language Modeling Framework for Object Detection Unofficial implementation of Pix2SEQ. Please use this code with causion. Many i

159 Dec 12, 2022
Deep Learning to Create StepMania SM FIles

StepCOVNet Running Audio to SM File Generator Currently only produces .txt files. Use SMDataTools to convert .txt to .sm python stepmania_note_generat

Chimezie Iwuanyanwu 8 Jan 08, 2023