Metadata-Version: 2.1
Name: Dragonflyz
Version: 2.0.4
Summary: Package for Code Analysis across your scripts
Home-page: https://github.com/jacob-h-barrow/Dragonflyz
Author: Jacob H Barrow
Author-email: jacob.h.barrow@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dataclasses
Requires-Dist: matplotlib
Requires-Dist: panel

# Dragonflyz
[![Test Coverage](https://img.shields.io/badge/Test%20Coverage-100%25-success)](https://github.com/jacob-h-barrow/Penguin-Services)
[![Security](https://img.shields.io/badge/Secure-True-informational)](https://github.com/jacob-h-barrow/Penguin-Services)
[![Platform](https://img.shields.io/badge/Platform-Ubuntu%2020%2B-critical)](https://github.com/jacob-h-barrow/Penguin-Services)
[![Python Version](https://img.shields.io/badge/Python-3.8%2B-critical)](https://github.com/jacob-h-barrow/Penguin-Services)
[![MIT License](https://img.shields.io/badge/License-MIT-lightgrey)](https://github.com/jacob-h-barrow/Penguin-Services/blob/main/Penguin-Services.png)

![Dragonflyz](https://user-images.githubusercontent.com/112576275/190509615-30b150b8-d67d-47af-bdff-4ee10163826b.png)

- Created By Jacob H Barrow, Cybersploit LLC

## What Is Dragonflyz?
### This time it's not just about being fast = Dominic Torretto.
- This package is being designed to make the software development lifecycle fast, effective, and financially responsible.
- From cradle to end of life, let's focus on being agile while prioritizing cost!
- Using Dragonflyz, software engineers can minimize their carbon footprint while securing their code from hackers.

### Why The Name
- For catching bugs in Python

### Kill Chain Overview
- Cross examined with Lockheed's Cyber Kill Chain
- Loads more to follow, this was the first day investing some time
- Right now, the package focuses on project engagement and management overhead.
- Later, it will get more technical as the package explores each stage below! 

### Code Analysis
- Reconnaisance stage
- Refers to both static and dynamic analysis
- Static and dynamic type exploitation
- etc

### Modification
- Weaponization stage
- Identify the location, functionality, systems of system(s) effect(s), then modify
- Based on the analysis, where can it be weaponized?
- What location(s) provide the state of interest?
- How many location(s) need to be involved to change each functionality?
- What functionalities are necessary to weaponize the entire system, or systems of systems?
- etc.

### Access
- Delivery stage
- How will this be delivered to all customers, new and existing?
- What will be needed to get this update or modification in place?
  - For example, do we need to compromise the PKI server or modify the signature on the signed code,in order to upload as the original author.
- etc.

### Execute
- Exploit stage
- When will the code be run?
- What NTP server is being used to track the time of execution?
- What conditions/systems are required for the code to be triggered?
- etc.

### State Analysis
- Installation stage
- How is our software going to beat attestation algorithms in-place?
- What index profile will our system be given after being modified?
  - For example, will the protection profile change? Will the heuristic profile change?
- etc.

### Networking
- Command and control stage
- Is the current REST API going to be leveraged?
- Does the modification allow the software to communicate/interact with other cover channels?
- etc.

### Your Move
- Actions or objections stage
- Is this to collect information, weaken the protection profile for subsequent attack, or are we trying to damge the system/network?
- Is this automated? Do we need to supervise further compromise? Is it a zero click that gives us a singular piece of information?
- Are we planning to lay low with the modification? Ex. NSA's ECC PRNG 2011
- Do we use this modification to attack as many as possible, or do we focus on non-attribution/a single demographic? 

## Installation
``` console
dragonfly@bugeatery:~$ pip install Dragonflyz
```

## Usage
``` python
>>> from KillChain import sprint_gantt, project_gantt, map_job_ids, Date_Range_Generator
>>> 
>>> ### Sprint Gantt Example
>>> tasks_mins = {"john": {"jobs": [(40, 50), (0,0), (0,0), (0,0), (0,0), (0,0), (175,250)]}, "natilie": {"jobs": [(110, 10), (150, 10)]}, "sammy": {"jobs": [(10, 50), (100, 20), (130, 10)]}, "max": {"jobs": [(0,0), (0, 0), (0, 0), (160, 180), (205, 225)]}, "Trix": {"jobs": [(0,0), (0,0), (0,0), (0,0), (175, 200), (240, 250)]}}
>>> sprint_gantt(tasks_mins, project_length = 270, project_name = "Soaring Eagle")
>>> 
>>> ### Project Gantt Example
>>> people = {'John': {0: Date_Range_Generator(6,9,2022, count = 3), 1: Date_Range_Generator(12, 9, 2022, count = 4), 2: Date_Range_Generator(16, 9, 2022)}, 'Trix': {3: Date_Range_Generator(26, 9, 2022, count = 6)}, 'Roxy': {0: Date_Range_Generator(6,9,2022, count = 4), 2: Date_Range_Generator(16,9,2022, count = 11), 3: Date_Range_Generator(29,9,2022, count = 3)}}
>>> tasks = {'people': {}, 'jobIds': {0: ["Engagement", 'tab:orange'], 1: ["Contract", "tab:red"], 2: ["Work", "tab:blue"], 3: ["Reporting", "tab:green"]}}
>>> project_gantt(map_job_ids(tasks, people), project_name = "Strike Eagle", filename = "Project Resource Allocation Gantt_Strike Eagle.png")
```

## Experimental Usage
- Influenced by PowerAPI code
- Not prime time yet, and would recommend using joulehunter in the meantime
### Warning -> Code Must Be Run With Sudo
``` console
dragonfly@bugeatery:~$ sudo pip install Dragonflyz
dragonflyz@bugeatery:~$ echo "Try the panel web interface"
dragonflyz@bugeatery:~$ sudo panel serve TESTFILE.py --show --autoreload
```
### Warning -> Code Must Be Run With Sudo
``` python
>>> # TESTFILE.py
>>> from Dragonflyz import EnergyConsumed, totalEnergy
>>> @EnergyConsumed(panel = True) # Only if you want to serve it to panel, else it returns the results in json form
>>> def decoratedFun():
>>> 	pass
>>>
>>> @EnergyConsumed(panel = False)
>>> def decoratedFun2():
>>> 	pass
>>> # Experimental
>>> print(totalEnergy(decoratedFun2()))
```
### Used in Profile-Aware -> Online GUI
``` python
>>> from Dragonflyz import sensor_info, print_devices
>>> print_devices(sensor_info())
```
### Used in Profile-Aware -> Online GUI
#### CpuHandler won't work with PowerEdge devices -> commercial product coming soon
``` python
>>> from Dragonflyz import MemoryHandler, CpuHandler
>>> with MemoryHandler() as memory:
>>>     print(memory.basic_memory_info())
>>> with CpuHandler() as cpu:
>>>     print(cpu.get_json())
```

### Made By Cybersploit LLC
- Defend against the software cyber killchain!


