dtrizna

using System;
using System.Reflection;
using Microsoft.CSharp;
using System.Diagnostics;
using System.Runtime.InteropServices;

public class Program
{
    public static void Main()
    {

dtrizna

using System;
using System.Reflection;
using Microsoft.CSharp;
using System.Diagnostics;
using System.Collections.Generic;
using System.Runtime.InteropServices;

public class Program
{
    static void Main(string[] args)

dtrizna

Kerberos cheatsheet

Bruteforcing

With kerbrute.py:

python kerbrute.py -domain <domain_name> -users <users_file> -passwords <passwords_file> -outputfile <output_file>

With Rubeus version with brute module:

dtrizna

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using System.IO;
using System.Diagnostics;

namespace donutTestSimpleDotNetApp

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import pandas as pd
import sys
from lxml import etree


def read_xml(FILENAME):
    parser = etree.XMLParser(recover=True)

    with open(FILENAME) as file:
        data = file.readlines()

dtrizna

dtrizna

import socket
import sys

listening_add = "192.168.56.1"
listening_port = 8888
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# bind socket obect to address and port and start to listen there
server.bind((listening_add, listening_port))
server.listen(5)
print("Listening on {}:{}".format(listening_add, listening_port))

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from sklearn.preprocessing import LabelEncoder
from tensorflow.keras.preprocessing.sequence import pad_sequences
from datetime import datetime
import numpy as np

MAX_TIMESTEPS = 128
# number of features (except PID itself)
N = len(newdf.columns) - 1

def groupby_transform(dataframe, column):

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from tensorflow import keras

METRICS = [
    keras.metrics.TruePositives(name='tp'),
    keras.metrics.FalsePositives(name='fp'),
    keras.metrics.TrueNegatives(name='tn'),
    keras.metrics.FalseNegatives(name='fn'), 
    # Precision: (TP) / (TP + FP)
    # what proportion of predicted Positives is truly Positive
    keras.metrics.Precision(name='precision'),

dtrizna

using System;
using System.Net;
using System.Linq;
using System.Text;
using System.Text.RegularExpressions;
using System.IO.Pipes;
using System.Reflection;
using System.Collections.Generic;
using System.Security.Cryptography;
using System.Runtime.InteropServices;