
Security News
Open Source CAI Framework Handles Pen Testing Tasks up to 3,600ร Faster Than Humans
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600ร faster than humans.
This is a versatile, Python-based toolbox crafted with โค๏ธ by Steveflyer. It serves not only as a standalone repository of utilities but also as an essential package for other innovative projects under Steveflyer's belt.
Projects such as:
Gembox encapsulates a plethora of utilities streamlined for daily use, including:
Gembox's multiprocessing utilities are tailored for efficient, parallel execution of both synchronous and asynchronous tasks. Leveraging the power of Python's multiprocessing and asyncio modules, it provides a seamless way to distribute and execute tasks across multiple CPU cores.
The crown jewel of the multiprocessing utilities. ParallelExecutor
facilitates the parallel execution of tasks. Whether you're dealing with synchronous or asynchronous tasks, this class got you covered.
Features:
Usage:
tasks = [Task(function_name, params_dict), ...]
results = ParallelExecutor.run(tasks, n_workers=number_of_processes)
A robust wrapper for any task (function) that you wish to execute, be it asynchronous or synchronous. The Task class ensures that each task is handled appropriately based on its nature.
Features:
ParallelExecutor
for balanced task distribution.Usage:
With gembox
๐, you can parallel your codes really easy
# for example, you have a function:
def calc_something(input_df, threshold):
# do something
return output_df
Then, you can parallel it by:
import asyncio
from gembox.multiprocessing import Task, ParallelExecutor
input_df_list = [df1, df2, df3, df4, df5] # your input dataframes
tasks = [Task(calc_something, {'input_df': df, 'threshold': 0.5}) for df in input_df_list]
asyncio.run(ParallelExecutor.run(tasks, n_workers=5))
Super Easy, right? (โฟโ โฟโ )
This multiprocess utility ensures that your CPU cores are efficiently utilized, boosting the performance of your applications manifold.
Gembox's script utilities offer a set of practical scripts that simplify frequent tasks, encapsulating complex operations into a single command. Currently, we've introduced a script that offers a fresh perspective on directory listing, aptly named ls-py
.
Move over traditional directory listing; ls-py
is here to revolutionize the way you view your directory's contents!
Features:
ls-py
has got you covered.Usage:
ls-py [path] [options]
Examples:
ls-py
ls-py -r ..
ls-py -r -x .git .idea __pycache__
ls-py -r -e
Enhance your terminal experience with ls-py
on any platform, a modern directory listing for the modern developer.
To get started with Gembox, you can simply clone this repository or install it via pip (assuming it's available on PyPi).
pip install gembox
The required packages for Gembox are listed in requirements.txt. Ensure to install them for a smooth experience.
Feel free to fork, enhance, create PRs and spread the word. Any contributions, big or small, are welcomed with open arms!
If you find this project useful, please consider giving it a star on GitHub.
FAQs
This is the gembox toolbox for steve flyer. You can also find your hammers here.
We found that gembox demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.ย It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600ร faster than humans.
Security News
Deno 2.4 brings back bundling, improves dependency updates and telemetry, and makes the runtime more practical for real-world JavaScript projects.
Security News
CVEForecast.org uses machine learning to project a record-breaking surge in vulnerability disclosures in 2025.