Dragonflyz 2.0.5

Package for Code Analysis across your scripts

Dragonflyz

• 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

dragonfly@bugeatery:~$ pip install Dragonflyz

Usage

>>> 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

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

>>> # 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

>>> from Dragonflyz import check_disks, get_database_size
>>> from pathlib import Path
>>> check_disks()
>>> get_database_size(Path("DATABASE LOCATION HERE"))

>>> 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

>>> 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!