BucketLoot - An Automated S3-compatible Bucket Inspector

To know more about our Attack Surface Management platform, check out NVADR.

Sysreptor - Fully Customisable, Offensive Security Reporting Tool Designed For Pentesters, Red Teamers And Other Security-Related People Alike

Easy and customisable pentest report creator based on simple web technologies.

SysReptor is a fully customisable, offensive security reporting tool designed for pentesters, red teamers and other security-related people alike. You can create designs based on simple HTML and CSS, write your reports in user-friendly Markdown and convert them to PDF with just a single click, in the cloud or on-premise!

Your Benefits

SysReptor Cloud

You just want to start reporting and save yourself all the effort of setting up, configuring and maintaining a dedicated server? Then SysReptor Cloud is the right choice for you! Get to know SysReptor on our Playground and if you like it, you can get your personal Cloud instance here:



Sign up here

SysReptor Self-Hosted

You prefer self-hosting? That's fine! You will need:

• Ubuntu
• Latest Docker (with docker-compose-plugin)

You can then install SysReptor with via script:

curl -s https://docs.sysreptor.com/install.sh | bash

After successful installation, access your application at http://localhost:8000/.

Get detailed installation instructions at Installation.

Metlo - An Open-Source API Security Platform

Secure Your API.

Metlo is an open-source API security platform

With Metlo you can:

• Create an Inventory of all your API Endpoints and Sensitive Data.
• Detect common API vulnerabilities.
• Proactively test your APIs before they go into production.
• Detect API attacks in real time.

Metlo does this by scanning your API traffic using one of our connectors and then analyzing trace data.

There are three ways to get started with Metlo. Metlo Cloud, Metlo Self Hosted, and our Open Source product. We recommend Metlo Cloud for almost all users as it scales to 100s of millions of requests per month and all upgrades and migrations are managed for you.

You can get started with Melto Cloud right away without a credit card. Just make an account on https://app.metlo.com and follow the instructions in our docs here.

Although we highly recommend Metlo Cloud, if you're a large company or need an air-gapped system you can self host Metlo as well! Create an account on https://my.metlo.com and follow the instructions on our docs here to setup Metlo in your own Cloud environment.

If you want to deploy our Open Source product we have instructions for AWS, GCP, Azure and Docker.

You can also join our Discord community if you need help or just want to chat!

Features

• Endpoint Discovery - Metlo scans network traffic and creates an inventory of every single endpoint in your API.
• Sensitive Data Scannning - Each endpoint is scanned for PII data and given a risk score.
• Vulnerability Discovery - Get Alerts for issues like unauthenticated endpoints returning sensitive data, No HSTS headers, PII data in URL params, Open API Spec Diffs and more
• API Security Testing - Build security tests directly in Metlo. Autogenerate tests for OWASP Top 10 vulns like BOLA, Broken Authentication, SQL Injection and more.
• CI/CD Integration - Integrate with your CI/CD to find issues in development and staging.
• Attack Detection - Our ML Algorithms build a model for baseline API behavior. Any deviation from this baseline is surfaced to your security team as soon as possible.
• Attack Context - Metlo’s UI gives you full context around any attack to help quickly fix the vulnerability.

Testing

For tests that we can't autogenerate, our built in testing framework helps you get to 100% Security Coverage on your highest risk APIs. You can build tests in a yaml format to make sure your API is working as intendend.

For example the following test checks for broken authentication:

id: test-payment-processor-metlo.com-user-billing

meta:
  name: test-payment-processor.metlo.com/user/billing Test Auth
  severity: CRITICAL
  tags:
    - BROKEN_AUTHENTICATION

test:
  - request:
      method: POST
      url: https://test-payment-processor.metlo.com/user/billing
      headers:
        - name: Content-Type
          value: application/json
        - name: Authorization
          value: ...
      data: |-
        { "ccn": "...", "cc_exp": "...", "cc_code": "..." }
    assert:
      - key: resp.status
        value: 200
  - request:
      method: POST
      url: https://test-payment-processor.metlo.com/user/billing
      headers:
        - name: Content-Type
          value: application/json
      data: |-
        { "ccn": "...", "cc_exp": "...", "cc_code": "..." }
    assert:
      - key: resp.s   tatus
        value: [ 401, 403 ]

You can see more information on our docs.

Why Metlo?

Most businesses have adopted public facing APIs to power their websites and apps. This has dramatically increased the attack surface for your business. There’s been a 200% increase in API security breaches in just the last year with the APIs of companies like Uber, Meta, Experian and Just Dial leaking millions of records. It's obvious that tools are needed to help security teams make APIs more secure but there's no great solution on the market.

Some solutions require you to go through sales calls to even try the product while others have you to send all your API traffic to their own cloud. Metlo is the first Open Source API security platform that you can self host, and get started for free right away!

We're Hiring!

We would love for you to come help us make Metlo better. Come join us at Metlo!

Open-source vs. paid

This repo is entirely MIT licensed. Features like user management, user roles and attack protection require an enterprise license. Contact us for more information.

Development

Checkout our development guide for more info on how to develop Metlo locally.

DC-Sonar - Analyzing AD Domains For Security Risks Related To User Accounts

DC Sonar Community

Repositories

The project consists of repositories:

• dc-sonar-frontend
• dc-sonar-user-layer
• dc-sonar-workers-layer
• ntlm-scrutinizer

Disclaimer

It's only for education purposes.

Avoid using it on the production Active Directory (AD) domain.

Neither contributor incur any responsibility for any using it.

Social media

Check out our Red Team community Telegram channel

Description

Architecture

For the visual descriptions, open the diagram files using the diagrams.net tool.

The app consists of:

• The dc-sonar-frontend is the fronted part of the user web interface bases on:
  • Angular
  • Angular Material
• The dc-sonar-user-layer is the backend part of the web app bases on:
  • Python 3.10
  • Django
  • Django ORM
  • Django REST framework
  • Celery
  • RabbitMQ
  • PostgreSQL
• The dc-sonar-workers-layer is the logic layer that performs and runs analyzing processes which base on:
  • Python 3.10
  • SQLAlchemy
  • Alembic
  • APScheduler
  • RabbitMQ
  • PostgreSQL
• The ntlm-scrutinizer is the NTLM hashes performer with REST API based on:
• Python 3.10
• FastAPI
• hashcat
• impacket

Functionallity

The DC Sonar Community provides functionality for analyzing AD domains for security risks related to accounts:

• Register analyzing AD domain in the app

  

• See the statuses of domain analyzing processes

  

• Dump and brute NTLM hashes from set AD domains to list accounts with weak and vulnerable passwords

  

• Analyze AD domain accounts to list ones with never expire passwords

  

• Analyze AD domain accounts by their NTLM password hashes to determine accounts and domains where passwords repeat

  

Installation

Docker

In progress ...

Manually using dpkg

It is assumed that you have a clean Ubuntu Server 22.04 and account with the username "user".

The app will install to /home/user/dc-sonar.

The next releases maybe will have a more flexible installation.

Download dc_sonar_NNNN.N.NN-N_amd64.tar.gz from the last distributive to the server.

Create a folder for extracting files:

mkdir dc_sonar_NNNN.N.NN-N_amd64

Extract the downloaded archive:

tar -xvf dc_sonar_NNNN.N.NN-N_amd64.tar.gz -C dc_sonar_NNNN.N.NN-N_amd64

Go to the folder with the extracted files:

cd dc_sonar_NNNN.N.NN-N_amd64/

Install PostgreSQL:

sudo bash install_postgresql.sh

Install RabbitMQ:

sudo bash install_rabbitmq.sh

Install dependencies:

sudo bash install_dependencies.sh

It will ask for confirmation of adding the ppa:deadsnakes/ppa repository. Press Enter.

Install dc-sonar itself:

sudo dpkg -i dc_sonar_NNNN.N.NN-N_amd64.deb

It will ask for information for creating a Django admin user. Provide username, mail and password.

It will ask for information for creating a self-signed SSL certificate twice. Provide required information.

Open: https://localhost

Enter Django admin user credentials set during the installation process before.

Style guide

See the information in STYLE_GUIDE.md

Deployment for development

Docker

In progress ...

Manually using Windows host and Ubuntu Server guest

In this case, we will set up the environment for editing code on the Windows host while running Python code on the Ubuntu guest.

Set up the virtual machine

Create a virtual machine with 2 CPU, 2048 MB RAM, 10GB SSD using Ubuntu Server 22.04 iso in VirtualBox.

If Ubuntu installer asks for updating ubuntu installer before VM's installation - agree.

Choose to install OpenSSH Server.

VirtualBox Port Forwarding Rules:

Config Window

Download and install Python 3.10.5.

Create a folder for the DC Sonar project.

Go to the project folder using Git for Windows:

cd '{PATH_TO_FOLDER}'

Make Windows installation steps for dc-sonar-user-layer.

Make Windows installation steps for dc-sonar-workers-layer.

Make Windows installation steps for ntlm-scrutinizer.

Make Windows installation steps for dc-sonar-frontend.

Set shared folders

Make steps from "Open VirtualBox" to "Reboot VM", but add shared folders to VM VirtualBox with "Auto-mount", like in the picture below:

After reboot, run command:

sudo adduser $USER vboxsf

Perform logout and login for the using user account.

In /home/user directory, you can use mounted folders:

ls -l

Output:
total 12
drwxrwx--- 1 root vboxsf 4096 Jul 19 13:53 dc-sonar-user-layer
drwxrwx--- 1 root vboxsf 4096 Jul 19 10:11 dc-sonar-workers-layer
drwxrwx--- 1 root vboxsf 4096 Jul 19 14:25 ntlm-scrutinizer

Config Ubuntu Server

Config PostgreSQL

Install PostgreSQL on Ubuntu 20.04:

sudo apt update
sudo apt install postgresql postgresql-contrib
sudo systemctl start postgresql.service

Create the admin database account:

sudo -u postgres createuser --interactive

Output:
Enter name of role to add: admin
Shall the new role be a superuser? (y/n) y

Create the dc_sonar_workers_layer database account:

sudo -u postgres createuser --interactive

Output:
Enter name of role to add: dc_sonar_workers_layer
Shall the new role be a superuser? (y/n) n
Shall the new role be allowed to create databases? (y/n) n
Shall the new role be allowed to create more new roles? (y/n) n

Create the dc_sonar_user_layer database account:

sudo -u postgres createuser --interactive

Output:
Enter name of role to add: dc_sonar_user_layer
Shall the new role be a superuser? (y/n) n
Shall the new role be allowed to create databases? (y/n) n
Shall the new role be allowed to create more new roles? (y/n) n

Create the back_workers_db database:

sudo -u postgres createdb back_workers_db

Create the web_app_db database:

sudo -u postgres createdb web_app_db

Run the psql:

sudo -u postgres psql

Set a password for the admin account:

ALTER USER admin WITH PASSWORD '{YOUR_PASSWORD}';

Set a password for the dc_sonar_workers_layer account:

ALTER USER dc_sonar_workers_layer WITH PASSWORD '{YOUR_PASSWORD}';

Set a password for the dc_sonar_user_layer account:

ALTER USER dc_sonar_user_layer WITH PASSWORD '{YOUR_PASSWORD}';

Grant CRUD permissions for the dc_sonar_workers_layer account on the back_workers_db database:

\c back_workers_db
GRANT CONNECT ON DATABASE back_workers_db to dc_sonar_workers_layer;
GRANT USAGE ON SCHEMA public to dc_sonar_workers_layer;
GRANT ALL ON ALL TABLES IN SCHEMA public TO dc_sonar_workers_layer;
GRANT ALL ON ALL SEQUENCES IN SCHEMA public TO dc_sonar_workers_layer;
GRANT ALL ON ALL FUNCTIONS IN SCHEMA public TO dc_sonar_workers_layer;

Grant CRUD permissions for the dc_sonar_user_layer account on the web_app_db database:

\c web_app_db
GRANT CONNECT ON DATABASE web_app_db to dc_sonar_user_layer;
GRANT USAGE ON SCHEMA public to dc_sonar_user_layer;
GRANT ALL ON ALL TABLES IN SCHEMA public TO dc_sonar_user_layer;
GRANT ALL ON ALL SEQUENCES IN SCHEMA public TO dc_sonar_user_layer;
GRANT ALL ON ALL FUNCTIONS IN SCHEMA public TO dc_sonar_user_layer;

Exit of the psql:

\q

Open the pg_hba.conf file:

sudo nano /etc/postgresql/12/main/pg_hba.conf

Add the line for the connection to allow the connection from the host machine to PostgreSQL, save changes and close the file:

# IPv4 local connections:
host    all             all             127.0.0.1/32            md5
host    all             admin           0.0.0.0/0               md5

Open the postgresql.conf file:

sudo nano /etc/postgresql/12/main/postgresql.conf

Change specified below params, save changes and close the file:

listen_addresses = 'localhost,10.0.2.15'
shared_buffers = 512MB
work_mem = 5MB
maintenance_work_mem = 100MB
effective_cache_size = 1GB

Restart the PostgreSQL service:

sudo service postgresql restart

Check the PostgreSQL service status:

service postgresql status

Check the log file if it is needed:

tail -f /var/log/postgresql/postgresql-12-main.log

Now you can connect to created databases using admin account and client such as DBeaver from Windows.

Config RabbitMQ

Install RabbitMQ using the script.

Enable the management plugin:

sudo rabbitmq-plugins enable rabbitmq_management

Create the RabbitMQ admin account:

sudo rabbitmqctl add_user admin {YOUR_PASSWORD}

Tag the created user for full management UI and HTTP API access:

sudo rabbitmqctl set_user_tags admin administrator

Open management UI on http://localhost:15672/.

Install Python3.10

Ensure that your system is updated and the required packages installed:

sudo apt update && sudo apt upgrade -y

Install the required dependency for adding custom PPAs:

sudo apt install software-properties-common -y

Then proceed and add the deadsnakes PPA to the APT package manager sources list as below:

sudo add-apt-repository ppa:deadsnakes/ppa

Download Python 3.10:

sudo apt install python3.10=3.10.5-1+focal1

Install the dependencies:

sudo apt install python3.10-dev=3.10.5-1+focal1 libpq-dev=12.11-0ubuntu0.20.04.1 libsasl2-dev libldap2-dev libssl-dev

Install the venv module:

sudo apt-get install python3.10-venv

Check the version of installed python:

python3.10 --version

Output:
Python 3.10.5

Hosts

Add IP addresses of Domain Controllers to /etc/hosts

sudo nano /etc/hosts

Layers

Set venv

We have to create venv on a level above as VM VirtualBox doesn't allow us to make it in shared folders.

Go to the home directory where shared folders located:

cd /home/user

Make deploy steps for dc-sonar-user-layer on Ubuntu.

Make deploy steps for dc-sonar-workers-layer on Ubuntu.

Make deploy steps for ntlm-scrutinizer on Ubuntu.

Config modules

Make config steps for dc-sonar-user-layer on Ubuntu.

Make config steps for dc-sonar-workers-layer on Ubuntu.

Make config steps for ntlm-scrutinizer on Ubuntu.

Run

Make run steps for ntlm-scrutinizer on Ubuntu.

Make run steps for dc-sonar-user-layer on Ubuntu.

Make run steps for dc-sonar-workers-layer on Ubuntu.

Make run steps for dc-sonar-frontend on Windows.

Open https://localhost:8000/admin/ in a browser on the Windows host and agree with the self-signed certificate.

Open https://localhost:4200/ in the browser on the Windows host and login as created Django user.

EvilTree - A Remake Of The Classic "Tree" Command With The Additional Feature Of Searching For User Provided Keywords/Regex In Files, Highlighting Those That Contain Matche

A standalone python3 remake of the classic "tree" command with the additional feature of searching for user provided keywords/regex in files, highlighting those that contain matches. Created for two main reasons:

• While searching for secrets in files of nested directory structures, being able to visualize which files contain user provided keywords/regex patterns and where those files are located in the hierarchy of folders, provides a significant advantage.
• "tree" is an amazing tool for analyzing directory structures. It's really handy to have a standalone alternative of the command for post-exploitation enumeration as it is not pre-installed on every linux distro and is kind of limited on Windows (compared to the UNIX version).

Usage Examples

Example #1: Running a regex that essentially matches strings similar to: password = something against /var/www

Example #2: Using comma separated keywords instead of regex:

Further Options & Usage Tips

Notable features:

• Regex -x search actually returns a unique list of all matched patterns in a file. Be careful when combining it with -v (--verbose), try to be specific and limit the length of chars to match.
• You can search keywords/regex in binary files as well by providing option -b.
• You can use this tool as the classic "tree" command if you do not provide keywords -k and regex -x values. This is useful in case you have gained a limited shell on a machine and want to have "tree" with colored output to look around.
• There's a list variable filetype_blacklist in eviltree.py which can be used to exclude certain file extensions from content search. By default, it excludes the following: gz, zip, tar, rar, 7z, bz2, xz, deb, img, iso, vmdk, dll, ovf, ova.
• A quite useful feature is the -i (--interesting-only) option. It instructs eviltree to list only files with matching keywords/regex content, significantly reducing the output length:
  
  

Useful keywords/regex patterns

• Regex to look for passwords: -x ".{0,3}passw.{0,3}[=]{1}.{0,18}"
• Keywords to look for sensitive info: -k passw,db_,admin,account,user,token

MrKaplan - Tool Aimed To Help Red Teamers To Stay Hidden By Clearing Evidence Of Execution

MrKaplan is a tool aimed to help red teamers to stay hidden by clearing evidence of execution. It works by saving information such as the time it ran, snapshot of files and associate each evidence to the related user.

This tool is inspired by MoonWalk, a similar tool for Unix machines.

You can read more about it in the wiki page.

Features

• Stopping event logging.
• Clearing files artifacts.
• Clearing registry artifacts.
• Can run for multiple users.
• Can run as user and as admin (Highly recommended to run as admin).
• Can save timestamps of files.
• Can exclude certian operations and leave artifacts to blue teams.

Usage

• Before you start your operations on the computer, run MrKaplan with begin flag and whenever your finish run it again with end flag.
• DO NOT REMOVE MrKaplan registry key, otherwise MrKaplan will not be able to use the information.

IOCs

• Powershell process that access to the artifacts mentioned in the wiki page.

• Powershell importing weird base64 blob.

• Powershell process that performs Token Manipulation.

• MrKaplan's registry key: HKCU:\Software\MrKaplan.

Acknowledgements

• PowerSploit

• Phant0m

• ForensicArtifacts

Disclaimer

I'm not responsible in any way for any kind of damage that is done to your computer / program as cause of this project. I'm happily accept contribution, make a pull request and I will review it!