watson0x90

import asyncio
import os
import subprocess
import time
import sys
import shutil
import argparse
from kasa import Discover, Credentials

# ==========================================

watson0x90

import asyncio
import os
import subprocess
import time
import sys
import shutil
import argparse
import re
from kasa import Discover, Credentials

watson0x90

import asyncio
import os
import subprocess
import time
import sys
import shutil
import argparse
import re
from kasa import Discover, Credentials

watson0x90

import asyncio
import os
import subprocess
import time
import re
from kasa import Discover, Credentials

# --- CONFIGURATION ---
TARGET_VID = "0634"  # Crucial Vendor ID
TARGET_PID = "5603"  # Crucial Product ID

watson0x90

#!/bin/bash
# ----------------------------------------------------
# SNIPER ELITE: HARDENED LOOP (State Aware)
# ----------------------------------------------------

# TARGET CONFIGURATION
TARGET_VID="0634"
TARGET_PID="5603"

# RECOVERY FILES

watson0x90

function Get-UpdatableGroupsEnhanced {
    <#
        .SYNOPSIS
            Finds groups that can be updated by the current user and includes group type information.
            Author: Modified from original by Ryan Watson (Watson0x90)
            License: MIT
            Required Dependencies: None
            Optional Dependencies: None

        .DESCRIPTION

watson0x90

# Script Name: DataTransformationLoader.py
# Author: Ryan Watson
# Gist Github: https://gist.github.com/Watson0x90
# Created on: 2025-04-03
# Last Modified: 2025-04-03
# Description: Data transformation loader for hacker-themed visualization
# Purpose: This script is designed to create a hacker-themed data transformation visualization using the rich library.
# Version: 1.0.0
# License: MIT License
# Dependencies: rich

watson0x90

# This is a proof of concept for CVE-2020-5377, an arbitrary file read in Dell OpenManage Administrator
# Proof of concept written by: David Yesland @daveysec with Rhino Security Labs
# More information can be found here: 
# A patch for this issue can be found here: 
# https://www.dell.com/support/article/en-us/sln322304/dsa-2020-172-dell-emc-openmanage-server-administrator-omsa-path-traversal-vulnerability

from xml.sax.saxutils import escape
import http.server
import ssl
import sys

watson0x90

import socket
from concurrent.futures import ThreadPoolExecutor
import ipaddress
import argparse

def parse_ports(file_path):
    """
    Parses a file containing port numbers and ranges, expanding ranges into individual ports.
    """
    ports = set()  # Use a set to avoid duplicates

watson0x90

Neo4j Cypher Queries for Bloodhound Data

Introduction

You will use these queries within the Neo4j query dashboard and not from the Bloodhound interface. There are so many different ways to examine the data. The queries below are designed to help myself and others find unique things in the gathered Bloodhound data and make it useful.

Queries

User Descriptions where not null or empty

MATCH (u:User) 
WHERE u.description IS NOT NULL AND u.description <> "" AND u.description <> " "
return u.name, u.description