Command-line Tools

Fish shell tool for managing Python virtual environments

VirtualFish VirtualFish is a Python virtual environment manager for the Fish shell. You can get started by reading the documentation. (It’s quite short… Promise!) You can also get help on #virtualfish on OFTC (ircs://irc.oftc.net:6697/#virtualfish), the same network as the Fish IRC channel. VirtualFish is currently maintained by Justin Mayer, and was originally created by Leigh Brenecki. A quickstart, for the impatient Fish version 3.1 or higher is required. python -m pip install virtualfish vf install Add VirtualFish to your prompt […]

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Python

Python Inner Functions

Python allows the declaration of functions inside of other functions. Inner functions, also known as nested functions, are defined within a function. This type of function has direct access to variables and names defined in the enclosing function in Python. Inner functions have many uses, most notably as closure factories and decorator functions. In this course, you’ll learn how to: Define inner functions Use inner functions as helper functions Build function closures Use captured variables in a closure Use captured […]

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Advanced, Classification, NLP, Project, Python, Structured Data, Supervised, Text

Automated Spam E-mail Detection Model(Using common NLP tasks)

Hope you all are doing Good !!! Welcome to my blog! Today we are going to understand about basics of NLP with the help of the Email Spam Detection dataset. We see some common NLP tasks that one can perform easily and how one can complete an end-to-end project. Whether you know NLP or not, this guide should help you as a ready reference. For the dataset used click on the above link or here. Let’s get started, Natural Language […]

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Games

Lint game data metafiles against GTA5.xsd for Rockstar’s game engine

rage-lint Lint RAGE (only GTA5 at the moment) meta/XML files for validity based off of the GTA5.xsd generated from game code. This script accepts a series of blobs, and validates all files against GTA5.xsd, allowing to check your metafilesagainst Rockstar’s own definitions. NOTE: This software is EXPERIMENTAL, there are likely XSD generation issues laying around Usage A rage-lint.exe file is provided in the releases tab. Compiling To use this script, first install the dependencies with pip install -r requirements.txt, then […]

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Bot

An easy to use image CAPTCHA soltion for pyTelegramBotAPI

pyTelegramBotCAPTCHA An easy to use and (hopefully useful) image CAPTCHA soltion for pyTelegramBotAPI. Installation: pip install pyTelegramBotCAPTCHA Do not forget to update the package from time to time by callingpip install pyTelegramBotCAPTCHA –upgrade Description: Do you have problems with userbots that spam your groups or add your group members to other chats? Then this package can help you to protect your groups and members! It’s very easy to integrate into your existing bot and also easy to customize the CAPTCHA […]

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Models

Unofficial implementation of PatchCore anomaly detection model

PatchCore anomaly detection Unofficial implementation of PatchCore(new SOTA) anomaly detection model Original Paper : Towards Total Recall in Industrial Anomaly Detection (Jun 2021)Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter Gehler https://arxiv.org/abs/2106.08265https://paperswithcode.com/sota/anomaly-detection-on-mvtec-ad notice(21/06/18) :This code is not yet verified. Any feedback is appreciated.updates(21/06/21) : I used sklearn’s SparseRandomProjection(ep=0.9) for random projection. I’m not confident with this. I think exact value of “b nearest patch-features” is not presented in the paper. I just set 9. (args.n_neighbors) In terms […]

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Tool

A tool search for SSRF using predefined settings in different parts of a request

Extended ssrf search This tool search for SSRF using predefined settings in different parts of a request (path, host, headers, post and get parameters). First step Rename example.app-settings.conf to app-settings.conf and adjust settings. The most important setting is the callback url. I recommend to use burp collaborator. Then you can add your urls to config/url-to-test.txt. Here the script accepts domains as well as urls with path and query parameters. If you like you can add your own cookies to config/cookie-jar.txt […]

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Discord

Check and write all account info + Check nitro on account

Check and write all account info + Check nitro on account Also check https://github.com/GuFFy12/Discord-Token-Parser (Parse discord tokens from any file, even if there is other shit in the file with them.) I have a great desire to remake this shit code, but I’m too lazy😔 JS EDITION: https://github.com/amfero/DiscordTokenChecker (I will contribute here (Py is 🤢)) TS EDITION: https://github.com/cattyngmd/DiscordTokenChecker-ts PY EDITION: https://github.com/GuFFy12/Discord-Token-Checker Output data: Token.rat Nitro: {Nitro or Classic or No} Billing: {Valid or Invalid or No} Username: lol#1337 Language: ru […]

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Authentication

An authentication bypass on polkit which allows unprivileged user to call privileged methods using DBus

Polkit-exploit – CVE-2021-3560 Privilege escalation with polkit – CVE-2021-3560 CVE-2021-3560 is an authentication bypass on polkit, which allows unprivileged user to call privileged methods using DBus, in this exploit we will call 2 privileged methods provided by accountsservice (CreateUser and SetPassword), which allows us to create a priviliged user then setting a password to it and at the end logging as the created user and then elevate to root. Ahmad Almorabea @almorabea http://almorabea.net [email protected]:~/Desktop$ python3 CVE-2021-3560.py ************** Exploit: Privilege escalation […]

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Machine Learning

A Differentiable Loss Function for Time-Series in CUDA

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch supported computation, CUDA-friendly, and feasible to use as a final loss. I can confirm that you can train a (sequential) model with this as a final loss! The following image shows training logs of a TTS model using the Soft-DTW Loss Function. There are some previous implementations: mblondel’s soft-dtw lyprince’s sdtw_pytorch Maghoumi’s pytorch-softdtw-cuda But they are […]

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