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Description:
bruteloops 1.0.1
BruteLoops
A dead simple library providing the foundational logic for
efficient password brute force attacks against authentication
interfaces.
Documentation
Documentation can be found here.
If you're looking for the old example modules...
See BFG.
The examples have been offloaded to a distinct project to
minimize code and packaging issues. Database and attack
capabilities have also been merged into a single binary.
Key Features
Protocol agnostic - If a callback can be written in Python,
BruteLoops can be used to attack it
SQLite support - All usernames, passwords, and credentials
are maintained in an SQLite database.
A companion utility (dbmanager.py) that creates and manages
input databases accompanies BruteLoops
Spray and Stuffing Attacks in One Tool - BruteLoops supports both
spray and stuffing attacks in the same attack logic and database, meaning
that you can configure a single database and run the attack without heavy
reconfiguration and confusion.
Guess scheduling - Each username in the SQLite database is configured
with a timestamp that is updated after each authentication event. This
means we can significantly reduce likelihood of locking accounts by
scheduling each authentication event with precision.
Fine-grained configurability to avoid lockout events - Microsoft's
lockout policies can be matched 1-to-1 using BruteLoop's parameters:
auth_threshold = Lockout Threshold
max_auth_jitter = Lockout Observation Window
Timestampes associated with each authentication event are tracked
in BruteLoops' SQLite database. Each username receives a distinct
timestamp to assure that authentication events are highly controlled.
Attack resumption - Stopping and resuming an attack is possible
without worrying about losing your place in the attack or locking accounts.
Multiprocessing - Speed up attacks using multiprocessing! By configuring
the parallel guess count, you're effectively telling BruteLoops how many
usernames to guess in parallel.
Logging - Each authentication event can optionally logged to disk.
This information can be useful during red teams by providing customers
with a detailed attack timeline that can be mapped back to logged events.
Breakers - Breakers behave like circuit breakers. An exception can
be raised x number of times before ending the attack loop. They can
reset after a given period of time as well, allowing for configurations
like "Exit after 6 ConnectionErrors occur".
Dependencies
BruteLoops requires Python3.7 or newer and
SQLAlchemy 1.3.0, the latter of
which can be obtained via pip and the requirements.txt file in
this repository: python3.7 -m pip install -r requirements.txt
Installation
git clone https://github.com/arch4ngel/bruteloops
cd bruteloops
python3 -m pip install -r requirements.txt
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Files:
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