JorianWoltjer

#!/usr/bin/python3
from blessed import Terminal
import subprocess
import shlex

term = Terminal()

def read_path():
    # Read input from drag
    full = ""

JorianWoltjer

# Environment Variables
export SCREENDIR=$HOME/.screen
export DISCORD_WEBHOOK="https://discord.com/api/webhooks/[...]/[...]"
export DISCORD_TOKEN="[...]"
export MANPAGER="sh -c 'col -bx | bat -l man -p'"  # highlight manpages with https://github.com/sharkdp/bat
export PROMPT_DIRTRIM=1  # truncate cwd in prompt to '...'
wt_duplicate() {  # Keep working directory when splitting panes in Windows Terminal
  echo -en '\e]9;9;"'
  wslpath -w "$PWD" | tr -d '\n'
  echo -en '"\x07'

JorianWoltjer

#SingleInstance Force

#IfWinActive, ahk_exe Adobe Premiere Pro.exe
  ^BS:: send, ^+{left}{delete}
#IfWinActive

#IfWinActive, ahk_exe AfterFX.exe
  ^BS:: send, ^+{left}{delete}
#IfWinActive

JorianWoltjer

Practical java.util.Random LCG attack using LLL reduction

An easy-to-use Python script to sync up with the state of a java.util.Random generator after supplying a few samples. The internal seed has 48 bits, and every sample you give to the program will give some amount of bits of information. Here is a table to get an idea of how many samples you should provide per amount of bits in your input number:

bits	bound	samples (±)
4	16	25
6	64	12
8	256	8
16	65536	4

JorianWoltjer

#!/usr/bin/env python3
import subprocess
import re
import sys

YSOSERIAL_PATH = "/tool/ysoserial/ysoserial-all.jar"  # https://github.com/frohoff/ysoserial/releases
JAVA_COMMAND = ["java"]  # May be eg. ["java", "-Xmx2g"] or a path to a java binary

def extract_missing(error):
    match = re.findall(r'java\.lang\.reflect\.InaccessibleObjectException: .*?: module (.*?) does not "opens (.*?)" to unnamed module @', error)

JorianWoltjer

import argparse
from pathlib import Path

parser = argparse.ArgumentParser()
parser.add_argument("input", type=Path, help="Input audio file (.mp3, .wav, .m4a, etc.)")
parser.add_argument("output", type=Path, help="Output text file (.txt)")
parser.add_argument("-m", "--model", choices=["small", "medium", "large"], default="medium", help="Model size")
args = parser.parse_args()

from faster_whisper import WhisperModel