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
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:
- Create database file
- Import BloodHound files
- Domains
- GPOs
- OUs
- Groups
- Computers
- Users
- Import NTDS file
- 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: Change clientCompanyName 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
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