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kitploitKitPloitKITPLOIT:723452985773513807
HistoryDec 24, 2023 - 11:30 a.m.

KnowsMore - A Swiss Army Knife Tool For Pentesting Microsoft Active Directory (NTLM Hashes, BloodHound, NTDS And DCSync)

2023-12-2411:30:00
www.kitploit.com
23
pentesting
microsoft active directory
python
ntlm hashes
bloodhound
password analysis
user searching
credentials export
weak passwords
statistics

7.5 High

AI Score

Confidence

Low

KnowsMore officially supports Python 3.8+.

Main features

  • Import NTLM Hashes from .ntds output txt file (generated by CrackMapExec or secretsdump.py)
  • Import NTLM Hashes from NTDS.dit and SYSTEM
  • Import Cracked NTLM hashes from hashcat output file
  • Import BloodHound ZIP or JSON file
  • BloodHound importer (import JSON to Neo4J without BloodHound UI)
  • Analyse the quality of password (length , lower case, upper case, digit, special and latin)
  • Analyse similarity of password with company and user name
  • Search for users, passwords and hashes
  • Export all cracked credentials direct to BloodHound Neo4j Database as ‘owned object’
  • Other amazing features…

Getting stats

knowsmore --stats

This command will produce several statistics about the passwords like the output bellow

weak passwords by company name similarity ±------±-------------±--------±---------------------±------+ | top | password | score | company_similarity | qty | |-------±-------------±--------±---------------------±------| | 1 | company123 | 7024 | 80 | 1111 | | 2 | Company123 | 5209 | 80 | 824 | | 3 | company | 3674 | 100 | 553 | | 4 | Company@10 | 2080 | 80 | 329 | | 5 | company10 | 1722 | 86 | 268 | | 6 | Company@2022 | 1242 | 71 | 202 | | 7 | Company@2024 | 1015 | 71 | 165 | | 8 | Company2022 | 978 | 75 | 157 | | 9 | Company10 | 745 | 86 | 116 | | 10 | Company21 | 707 | 86 | 110 | ±------±-------------±--------±---------------------±------+ " dir=“auto”>

KnowsMore v0.1.4 by Helvio Junior  
Active Directory, BloodHound, NTDS hashes and Password Cracks correlation tool  
https://github.com/helviojunior/knowsmore  
      
 [+] Startup parameters  
     command line: knowsmore --stats   
     module: stats  
     database file: knowsmore.db  
    
 [+] start time 2023-01-11 03:59:20  
[?] General Statistics  
+-------+----------------+-------+  
|   top | description    |   qty |  
|-------+----------------+-------|  
|     1 | Total Users    | 95369 |  
|     2 | Unique Hashes  | 74299 |  
|     3 | Cracked Hashes | 23177 |  
|     4 | Cracked Users  | 35078 |  
+-------+----------------+-------+  
  
 [?] General Top 10 passwords  
+-------+-------------+-------+  
|   top | password    |   qty |  
|-------+-------------+-------|  
|     1 | password    |  1111 |  
|     2 | 123456      |   824 |  
|     3 | 123456789   |   815 |  
|     4 | guest       |      553 |  
|     5 | qwerty      |   329 |  
|     6 | 12345678    |   277 |  
|     7 | 111111      |   268 |  
|     8 | 12345       |   202 |  
|     9 | secret      |   170 |  
|    10 | sec4us      |   165 |  
+-------+-------------+-------+  
  
 [?] Top 10 weak passwords by company name similarity  
+-------+--------------+---------+----------------------+-------+  
|   top | password     |   score |   company_similarity |   qty |  
|-------+--------------+---------+----------------------+-------|  
|     1 | company123   |    7024 |                   80 |  1111 |  
|     2 | Company123   |    5209 |                   80 |   824 |  
|     3 | company      |    3674 |                  100 |   553 |  
|     4 | Company@10   |    2080 |                   80 |   329 |  
|     5 | company10    |    1722 |                   86 |   268 |  
|     6 | Company@2022 |    1242 |                   71 |   202 |  
|     7 | Company@2024 |    1015 |                      71 |   165 |  
|     8 | Company2022  |     978 |                   75 |   157 |  
|     9 | Company10    |     745 |                   86 |   116 |  
|    10 | Company21    |     707 |                   86 |   110 |  
+-------+--------------+---------+----------------------+-------+  

Installation

Simple

pip3 install --upgrade knowsmore

Note: If you face problem with dependency version Check the Virtual ENV file

Execution Flow

There is no an obligation order to import data, but to get better correlation data we suggest the following execution flow:

  1. Create database file
  2. Import BloodHound files
    1. Domains
    2. GPOs
    3. OUs
    4. Groups
    5. Computers
    6. Users
  3. Import NTDS file
  4. Import cracked hashes

Create database file

All data are stored in a SQLite Database

knowsmore --create-db

Importing BloodHound files

We can import all full BloodHound files into KnowsMore, correlate data, and sync it to Neo4J BloodHound Database. So you can use only KnowsMore to import JSON files directly into Neo4j database instead of use extremely slow BloodHound User Interface

# Bloodhound ZIP File  
knowsmore --bloodhound --import-data ~/Desktop/client.zip  
  
# Bloodhound JSON File  
knowsmore --bloodhound --import-data ~/Desktop/20220912105336_users.json

Note: The KnowsMore is capable to import BloodHound ZIP File and JSON files, but we recommend to use ZIP file, because the KnowsMore will automatically order the files to better data correlation.

Sync data to Neo4j BloodHound database

# Bloodhound ZIP File  
knowsmore --bloodhound --sync 10.10.10.10:7687 -d neo4j -u neo4j -p 12345678

Note: The KnowsMore implementation of bloodhount-importer was inpired from Fox-It BloodHound Import implementation. We implemented several changes to save all data in KnowsMore SQLite database and after that do an incremental sync to Neo4J database. With this strategy we have several benefits such as at least 10x faster them original BloodHound User interface.

Importing NTDS file

Option 1

Note: Import hashes and clear-text passwords directly from NTDS.dit and SYSTEM registry

knowsmore --secrets-dump -target LOCAL -ntds ~/Desktop/ntds.dit -system ~/Desktop/SYSTEM

Option 2

Note: First use the secretsdump to extract ntds hashes with the command bellow

secretsdump.py -ntds ntds.dit -system system.reg -hashes lmhash:ntlmhash LOCAL -outputfile ~/Desktop/client_name

After that import

knowsmore --ntlm-hash --import-ntds ~/Desktop/client_name.ntds

Generating a custom wordlist

knowsmore --word-list -o "~/Desktop/Wordlist/my_custom_wordlist.txt" --batch --name company_name

Importing cracked hashes

Cracking hashes

First extract all hashes to a txt file

# Extract NTLM hashes to file  
nowsmore --ntlm-hash --export-hashes "~/Desktop/ntlm_hash.txt"  
  
# Or, extract NTLM hashes from NTDS file  
cat ~/Desktop/client_name.ntds | cut -d ':' -f4 > ntlm_hashes.txt

In order to crack the hashes, I usually use hashcat with the command bellow

# Wordlist attack  
hashcat -m 1000 -a 0 -O -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" "~/Desktop/Wordlist/*"  
  
# Mask attack  
hashcat -m 1000 -a 3 -O --increment --increment-min 4 -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" ?a?a?a?a?a?a?a?a

importing hashcat output file

knowsmore --ntlm-hash --company clientCompanyName --import-cracked ~/Desktop/cracked.txt

Note: ChangeclientCompanyName to name of your company

Wipe sensitive data

As the passwords and his hashes are extremely sensitive data, there is a module to replace the clear text passwords and respective hashes.

Note: This command will keep all generated statistics and imported user data.

knowsmore --wipe

BloodHound Mark as owned

One User

During the assessment you can find (in a several ways) users password, so you can add this to the Knowsmore database

knowsmore --user-pass --username administrator --password Sec4US@2023  
  
# or adding the company name  
  
knowsmore --user-pass --username administrator --password Sec4US@2023 --company sec4us

Integrate all credentials cracked to Neo4j Bloodhound database

knowsmore --bloodhound --mark-owned 10.10.10.10 -d neo4j -u neo4j -p 123456

To remote connection make sure that Neo4j database server is accepting remote connection. Change the line bellow at the config file /etc/neo4j/neo4j.conf and restart the service.

server.bolt.listen_address=0.0.0.0:7687

Download Knowsmore

7.5 High

AI Score

Confidence

Low