Harvis is designed to automate your C2 Infrastructure.

Related tags

Text Data & NLPHarvis
Overview

Harvis

Harvis is designed to automate your C2 Infrastructure, currently using Mythic C2.

📌 What is it?

Harvis is a python tool to help you create multiple hauls for a specific operation during a red team engagement. It can automatically create your C2 machine, redirector machine, setup SSL, .htaccess configuration, firewall rules and more. Harvis also has the purpose of automating the job of the operator of identifying burned domains/redirectors that may be caught during the operation. After identifying the burned domains it provides the possibility of rotating the infrastructure, setting up different redirectors and atributing a different domain.

📌 How?

🔨 Harvis uses the Digital Ocean API to automate creation and deletion of droplets.

🔨 The Namecheap API is used to set DNS records to redirectors.

🔨 The API Void is used to constantly verify the state of the redirectors and check if anything is blacklisted.

Features

Harvis has several features to help you organize your available domains and redirector/C2 machines.

  • Namecheap Interaction - Harvis enables you to buy domains directly through the command line, as long as you have credits in your account.
  • Multiple Hauls - It is possible to create as many hauls as possible, each one having specific configurations.
  • Multiple C2 Profiles by Haul - Harvis allows you to create multiple C2 profiles by hauls: you could two HTTP listeners in one of the C2's and 3 in the other one, each of them listening on different ports.
  • Multiple Redirector Configuration - Each redirector can have a different .htaccess configuration, defined by the operator.
  • Customizable Firewall Rules - Harvis comes with default firewall rules for the redirectors and C2's, however, this feature is easily customizable.
  • Priority System - Each haul has a queue system, in a way that the new redirector will replace the blacklisted one with the domains in the queue.
  • Priority System - Automatically replace your droplets: Harvis identifies any blacklisted redirector and print the results to the operator. It allows the operator to create a temporary droplet to replace the blacklisted one. It does not configure the migration of any active agents, since the way the agent will be migrated/spawned to connect to the new domain might be a very personal decision in an engagement. After creating the temporary droplet, it allows you to migrate any active agents and kill the older redirector.
  • Priority System - If somehow the script crashes, all the information will be saved in the backup.py file. Restarting the script will recover all your infrastructure as it was.

Installation

git clone https://github.com/thiagomayllart/Harvis/
cd Harvis
pip3 install -r requirements

Running

python3 harvis.py

Configuring API Keys

Harvis can only be used with the proper API Keys from Digital Ocean, Namecheap, APIVoid.

These api keys should be added to the config.py file in the respective lines. Don't forget to setup your namecheap username in namecheap_username variable:

digital_ocean_token = ""
...
namecheap_key = ""
...
apivoid_key = ""
...
namecheap_username = ""
...

For more information regarding these API Keys, visit:

https://app.apivoid.com/ https://ap.www.namecheap.com/ https://cloud.digitalocean.com/

First Run

Before running the script, you should apply some modifications to the config file, which describes the configuration of your infrastructure:

  1. Modify the "names" variable.

This variable holds the names of each haul you want your infrastructure you have. Theses names should be applied in the next variables. You can have as many hauls you want. You can also specify which domain should already be configure to each haul. If you don't specify the domains, you will be asked to move domains to each haul in the first run. If you don't have any available domains in your namecheap API, you can buy it directly though Harvis. It is also possible to have more than one domain in each haul: the first one will be used in the redirector and the others will already be in the backup list for further infrastructure rotations. Example:

names = {"short":[],"long":[],"exploitation":[],"testing":[]}
names = {"short":["domain1.com"],"long":["domain2.com","domain3.com"],"exploitation":["domain4.com"],"testing":["domain5.com"]}
  1. Modify the "config_htaccess_dic" variable:

You can customize your htaccess rules for each haul in this variable. This variable is dictionary, so remember to add an htacces for each haul you added previously in the "names" variable like:

config_htaccess_dic = \
    {"short":"""
RewriteEngine On
RewriteCond %{REQUEST_URI} ^/({1})/?$ [NC]
RewriteRule ^.*$ https://{2}%{REQUEST_URI} [P]
RewriteRule ^.*$ http://{3}? [L,R=302]
""","long:"""
RewriteEngine On
RewriteCond %{REQUEST_URI} ^/({1})/?$ [NC]
RewriteRule ^.*$ https://{2}%{REQUEST_URI} [P]
RewriteRule ^.*$ http://{3}? [L,R=302]
""","exploitation":"""
RewriteEngine On
RewriteCond %{REQUEST_URI} ^/({1})/?$ [NC]
RewriteRule ^.*$ https://{2}%{REQUEST_URI} [P]
RewriteRule ^.*$ http://{3}? [L,R=302]
""","testing":"""
RewriteEngine On
RewriteCond %{REQUEST_URI} ^/({1})/?$ [NC]
RewriteRule ^.*$ https://{2}%{REQUEST_URI} [P]
RewriteRule ^.*$ http://{3}? [L,R=302]
"""
                       }

You can notice the presence of the fields: {1}, {2}, {3}. If you customize this variable, do not remove them. {1} are the parameters your Mythic agent will use to communicate to the C2 (it also allows customization). {2} is the IP address of your C2. {3} is the location the redirector will be redirecting (it also allows customization).

  1. Modify the "agent_profiles" variable:

This variable describes the HTTP parameters that your agent will use to communicate to your C2. Mythic allows setting these parameters during the creation of the agent, so, these values should match the ones you will be configurating the agent. The first one is the GET parameter and other one is the POST parameter. Also, remeber to once again add a configuration to each haul you created previously:

agent_profiles = {"short":{"URI":"data|index"},"long":{"URI":"q|id"}... ...
  1. Modify "domain_front_redirector" variable:

This variable holds the domain your redirectors will be redirecting anyone that tries to access. Add a configuration to each haul you created previously:

domain_front_redirector = {"short":"www.example.com","long":"www.example2.com"... ... ...

  1. Modify "c2_profiles" variable:

With the "c2_profiles" variable you can create different listener profiles for each Haul you created. The format is exactly the same as the JSON you may find when accessing Configuring a C2 Profile in Mythic. You can also have other profiles than HTTP, however, depending on the protocol used, it may be necessary to change firewall rules in the C2 or the redirector (further explained).

Example:


c2_profiles = {"short":[{"name":"HTTP","config":"""{
  "instances": [
  {
    "ServerHeaders": {
      "Server": "NetDNA-cache/2.2",
      "Cache-Control": "max-age=0, no-cache",
      "Pragma": "no-cache",
      "Connection": "keep-alive",
      "Content-Type": "application/javascript; charset=utf-8"
    },
    "port": 443,
    "key_path": "privkey.pem",
    "cert_path": "cert.pem",
    "debug": true
    }
  ]
}"""}],"long":[{"name":"HTTP","config":"""{
  "instances": [
  {
    "ServerHeaders": {
      "Server": "NetDNA-cache/2.2",
      "Cache-Control": "max-age=0, no-cache",
      "Pragma": "no-cache",
      "Connection": "keep-alive",
      "Content-Type": "application/javascript; charset=utf-8"
    },
    "port": 443,
    "key_path": "privkey.pem",
    "cert_path": "cert.pem",
    "debug": true
    }
  ]
}"""}] }
  1. Modify the "check_infra_state" variable:

This variable holds the value (in seconds) that will be used as the interval between each verification of blacklisted domains by APIVoid.

  1. Modify "ip_allowed_to_connect_c2":

Replace it with the IP you will be using as the proxy to connect to your Mythic C2 panel. You can use your public IP, but it is not recommended.

  1. Replace "username":

Replace it with the username you will be using during the engagement. This variable is used to tag each droplet created in digital ocean, making the distinction between the droplets of each operator easier. It also avoids that the tool erases the droplet of another user (in case you guys are using the same API Keys).

  1. Modify Firewall Rules (OPTIONAL):

If you want to modify the firewall rules for the C2/redirector, you will find them respectively at:

C2: C2_setup.py: function firewall_rules Redirector: redirect_setup.py: firewall_rules

Important

Harvis whitelists the IP of the machine you are deploying it as being able to access your Mythic C2 panel. It is highly recommended to use a VPC to deploy Harvis.

Owner
Thiago Mayllart
- Information Security Researcher / RedTeam
Thiago Mayllart
Text editor on python to convert english text to malayalam(Romanization/Transiteration).

Manglish Text Editor This is a simple transiteration (romanization ) program which is used to convert manglish to malayalam (converts njaan to ഞാൻ ).

Merin Rose Tom 1 May 11, 2022
kochat

Kochat 챗봇 빌더는 성에 안차고, 자신만의 딥러닝 챗봇 애플리케이션을 만드시고 싶으신가요? Kochat을 이용하면 손쉽게 자신만의 딥러닝 챗봇 애플리케이션을 빌드할 수 있습니다. # 1. 데이터셋 객체 생성 dataset = Dataset(ood=True) #

1 Oct 25, 2021
基于pytorch+bert的中文事件抽取

pytorch_bert_event_extraction 基于pytorch+bert的中文事件抽取,主要思想是QA(问答)。 要预先下载好chinese-roberta-wwm-ext模型,并在运行时指定模型的位置。

西西嘛呦 31 Nov 30, 2022
Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge. Proceedings of EMNLP 2021

AAGCN-ACSA EMNLP 2021 Introduction This repository was used in our paper: Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment An

Akuchi 36 Dec 18, 2022
Code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

Code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

1.1k Dec 27, 2022
Text-Based zombie apocalyptic decision-making game in Python

Inspiration We shared university first year game coursework.[to gauge previous experience and start brainstorming] Adapted a particular nuclear fallou

Amin Sabbagh 2 Feb 17, 2022
apple's universal binaries BUT MUCH WORSE (PRACTICAL SHITPOST) (NOT PRODUCTION READY)

hyperuniversality investment opportunity: what if we could run multiple architectures in a single file, again apple universal binaries, but worse how

luna 2 Oct 19, 2021
L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources.

L3Cube-MahaCorpus L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual

21 Dec 17, 2022
Th2En & Th2Zh: The large-scale datasets for Thai text cross-lingual summarization

Th2En & Th2Zh: The large-scale datasets for Thai text cross-lingual summarization 📥 Download Datasets 📥 Download Trained Models INTRODUCTION TH2ZH (

Nakhun Chumpolsathien 5 Jan 03, 2022
Develop open-source Python Arabic NLP libraries that the Arab world will easily use in all Natural Language Processing applications

Develop open-source Python Arabic NLP libraries that the Arab world will easily use in all Natural Language Processing applications

BADER ALABDAN 2 Oct 22, 2022
Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.

Demo Code for "Talking Head Anime from a Single Image 2: More Expressive" This repository contains demo programs for the Talking Head Anime

Pramook Khungurn 901 Jan 06, 2023
A notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository

We provide a notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository. The notebook also shows how to segment the corpus using BPE tokenizatio

Computation for Indian Language Technology (CFILT) 9 Oct 13, 2022
Resources for "Natural Language Processing" Coursera course.

Natural Language Processing course resources This github contains practical assignments for Natural Language Processing course by Higher School of Eco

Advanced Machine Learning specialisation by HSE 1.1k Jan 01, 2023
Coreference resolution for English, German and Polish, optimised for limited training data and easily extensible for further languages

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

msg systems ag 169 Dec 21, 2022
Text editor on python tkinter to convert english text to other languages with the help of ployglot.

Transliterator Text Editor This is a simple transliteration program which is used to convert english word to phonetically matching word in another lan

Merin Rose Tom 1 Jan 16, 2022
Natural Language Processing with transformers

we want to create a repo to illustrate usage of transformers in chinese

Datawhale 763 Dec 27, 2022
Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.

Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra. What is Lightning Tran

Pytorch Lightning 581 Dec 21, 2022
Python wrapper for Stanford CoreNLP tools v3.4.1

Python interface to Stanford Core NLP tools v3.4.1 This is a Python wrapper for Stanford University's NLP group's Java-based CoreNLP tools. It can eit

Dustin Smith 610 Sep 07, 2022
Mastering Transformers, published by Packt

Mastering Transformers This is the code repository for Mastering Transformers, published by Packt. Build state-of-the-art models from scratch with adv

Packt 195 Jan 01, 2023
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai

Amazon Web Services - Labs 124 Jan 03, 2023