Kerberoast with ACL abuse capabilities

Overview

targetedKerberoast

targetedKerberoast is a Python script that can, like many others (e.g. GetUserSPNs.py), print "kerberoast" hashes for user accounts that have a SPN set. This tool brings the following additional feature: for each user without SPNs, it tries to set one (abuse of a write permission on the servicePrincipalName attribute), print the "kerberoast" hash, and delete the temporary SPN set for that operation. This is called targeted Kerberoasting. This tool can be used against all users of a domain, or supplied in a list, or one user supplied in the CLI.

More information about this attack

Usage

This tool supports the following authentications

Among other things, pyWhisker supports multi-level verbosity, just append -v, -vv, ... to the command :)

usage: targetedKerberoast.py [-h] [-v] [-q] [-D TARGET_DOMAIN] [-U USERS_FILE] [--request-user username] [-o OUTPUT_FILE] [--use-ldaps] [--only-abuse] [--no-abuse] [--dc-ip ip address] [-d DOMAIN] [-u USER]
                             [-k] [--no-pass | -p PASSWORD | -H [LMHASH:]NTHASH | --aes-key hex key]

Queries target domain for SPNs that are running under a user account and operate targeted Kerberoasting

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         verbosity level (-v for verbose, -vv for debug)
  -q, --quiet           show no information at all
  -D TARGET_DOMAIN, --target-domain TARGET_DOMAIN
                        Domain to query/request if different than the domain of the user. Allows for Kerberoasting across trusts.
  -U USERS_FILE, --users-file USERS_FILE
                        File with user per line to test
  --request-user username
                        Requests TGS for the SPN associated to the user specified (just the username, no domain needed)
  -o OUTPUT_FILE, --output-file OUTPUT_FILE
                        Output filename to write ciphers in JtR/hashcat format
  --use-ldaps           Use LDAPS instead of LDAP
  --only-abuse          Ignore accounts that already have an SPN and focus on targeted Kerberoasting
  --no-abuse            Don't attempt targeted Kerberoasting

authentication & connection:
  --dc-ip ip address    IP Address of the domain controller or KDC (Key Distribution Center) for Kerberos. If omitted it will use the domain part (FQDN) specified in the identity parameter
  -d DOMAIN, --domain DOMAIN
                        (FQDN) domain to authenticate to
  -u USER, --user USER  user to authenticate with

secrets:
  -k, --kerberos        Use Kerberos authentication. Grabs credentials from .ccache file (KRB5CCNAME) based on target parameters. If valid credentials cannot be found, it will use the ones specified in the
                        command line
  --no-pass             don't ask for password (useful for -k)
  -p PASSWORD, --password PASSWORD
                        password to authenticate with
  -H [LMHASH:]NTHASH, --hashes [LMHASH:]NTHASH
                        NT/LM hashes, format is LMhash:NThash
  --aes-key hex key     AES key to use for Kerberos Authentication (128 or 256 bits)

Below is an example what the tool can do.

Credits and references

Credits to the whole team behind Impacket and its contributors.

Owner
Shutdown
Shutdown
Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

Francis R. Willett 305 Dec 22, 2022
Translates basic English sentences into the Huna language (hoo-NAH)

huna-translator The Huna Language Translates basic English sentences into the Huna language (hoo-NAH). The Huna constructed language was developed in

Miles Smith 0 Jan 20, 2022
A python project made to generate code using either OpenAI's codex or GPT-J (Although not as good as codex)

CodeJ A python project made to generate code using either OpenAI's codex or GPT-J (Although not as good as codex) Install requirements pip install -r

TheProtagonist 1 Dec 06, 2021
Dust model dichotomous performance analysis

Dust-model-dichotomous-performance-analysis Using a collated dataset of 90,000 dust point source observations from 9 drylands studies from around the

1 Dec 17, 2021
ADCS - Automatic Defect Classification System (ADCS) for SSMC

Table of Contents Table of Contents ADCS Overview Summary Operator's Guide Demo System Design System Logic Training Mode Production System Flow Folder

Tam Zher Min 2 Jun 24, 2022
Official code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].

PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat

Wasi Ahmad 138 Dec 30, 2022
Meta learning algorithms to train cross-lingual NLI (multi-task) models

Meta learning algorithms to train cross-lingual NLI (multi-task) models

M.Hassan Mojab 4 Nov 20, 2022
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

Antlr Project 13.6k Jan 05, 2023
Winner system (DAMO-NLP) of SemEval 2022 MultiCoNER shared task over 10 out of 13 tracks.

KB-NER: a Knowledge-based System for Multilingual Complex Named Entity Recognition The code is for the winner system (DAMO-NLP) of SemEval 2022 MultiC

116 Dec 27, 2022
Unofficial Python library for using the Polish Wordnet (plWordNet / Słowosieć)

Polish Wordnet Python library Simple, easy-to-use and reasonably fast library for using the Słowosieć (also known as PlWordNet) - a lexico-semantic da

Max Adamski 12 Dec 23, 2022
An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)

VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image captioning, speech translation

Facebook Research 409 Oct 28, 2022
Sequence modeling benchmarks and temporal convolutional networks

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

CMU Locus Lab 3.5k Jan 03, 2023
⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x using fastT5.

Reduce T5 model size by 3X and increase the inference speed up to 5X. Install Usage Details Functionalities Benchmarks Onnx model Quantized onnx model

Kiran R 399 Jan 05, 2023
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

Novetta 407 Jan 03, 2023
Code for "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022.

README Code for Two-stage Identifier: "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022. For details of the model a

Yongliang Shen 45 Nov 29, 2022
CoSENT、STS、SentenceBERT

CoSENT_Pytorch 比Sentence-BERT更有效的句向量方案

102 Dec 07, 2022
🤕 spelling exceptions builder for lazy people

🤕 spelling exceptions builder for lazy people

Vlad Bokov 3 May 12, 2022
This code is the implementation of Text Emotion Recognition (TER) with linguistic features

APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod

kenro515 1 Feb 08, 2022
Few-shot Natural Language Generation for Task-Oriented Dialog

Few-shot Natural Language Generation for Task-Oriented Dialog This repository contains the dataset, source code and trained model for the following pa

172 Dec 13, 2022