acido 0.13

Description:

acido 0.13

acido 0.13
Acido stands for Azure Container Instance Distributed Operations, with acido you can easily deploy container instances in Azure and distribute the workload of a particular task, for example, a port scanning task which has an input file with x hosts is splitted and distributed between y instances.
This tool is inspired by axiom where you can just spin up hundreds of instances to perform a distributed nmap/ffuf/screenshotting scan, and then delete them after they have finished.
Depending on your quota limit you may need to open a ticket to Azure to request container group limits increase.
Add an alias in .bashrc / .zshrc:
alias acido='python3 -m acido.cli'

Usage:
usage: acido [-h] [-c] [-f FLEET] [-im IMAGE_NAME] [-n NUM_INSTANCES] [-t TASK] [-e EXEC_CMD] [-i INPUT_FILE] [-w WAIT] [-s SELECT] [-l] [-r REMOVE] [-in]
[-sh SHELL] [-d DOWNLOAD_INPUT] [-o WRITE_TO_FILE]

optional arguments:
-h, --help show this help message and exit
-c, --config Start configuration of acido.
-f FLEET, --fleet FLEET
Create new fleet.
-im IMAGE_NAME, --image IMAGE_NAME
Deploy an specific image.
-n NUM_INSTANCES, --num-instances NUM_INSTANCES
Instances that the operation affect
-t TASK, --task TASK Execute command as an entrypoint in the fleet.
-e EXEC_CMD, --exec EXEC_CMD
Execute command on a running instance.
-i INPUT_FILE, --input-file INPUT_FILE
The name of the file to use on the task.
-w WAIT, --wait WAIT Set max timeout for the instance to finish.
-s SELECT, --select SELECT
Select instances matching name/regex.
-l, --list List all instances.
-r REMOVE, --rm REMOVE
Remove instances matching name/regex.
-in, --interactive Start interactive acido session.
-sh SHELL, --shell SHELL
Execute command and upload to blob.
-d DOWNLOAD_INPUT, --download DOWNLOAD_INPUT
Download file contents remotely from the acido blob.
-o WRITE_TO_FILE, --output WRITE_TO_FILE
Save the output of the machines in JSON format.
-rwd, --rm-when-done Remove the container groups after finish.

Example usage with nmap
In this example we are going to:

Create our base container image with acido (required) and nmap.
Create 20 containers.
Run a nmap scan using the 20 containers.

Step 1: Create the base image
Dockerfile (merabytes.azurecr.io/ubuntu:latest):
FROM ubuntu:20.04

RUN apt-get update && apt-get install python3 python3-pip python3-dev -y
RUN python3 -m pip install acido
RUN apt-get install nmap -y

CMD ["sleep", "infinity"]

This will install acido & nmap on our base docker image (merabytes.azurecr.io/ubuntu:latest).
To upload the image to the registry, as always go to the folder of your Dockerfile and:
docker login merabytes.azurecr.io
docker build -t ubuntu .
docker tag ubuntu merabytes.azurecr.io/ubuntu:latest
docker push merabytes.azurecr.io/ubuntu:latest

Step 2: Run the scan
$ cat file.txt
merabytes.com
uber.com
facebook.com
...

$ acido -f ubuntu \
-n 20 \
--image merabytes.azurecr.io/ubuntu:latest \
-t 'nmap -iL input -p 0-200' \
-i file.txt \
-o output

[+] Selecting I/O storage account (acido).
[+] Splitting into 20 files.
[+] Uploaded 20 targets lists.
[+] Successfully created new group/s: [ ubuntu-01 ubuntu-02 ]
[+] Successfully created new instance/s: [ ubuntu-01-01 ubuntu-01-02 ubuntu-01-03 ubuntu-01-04 ubuntu-01-05 ubuntu-01-06 ubuntu-01-07 ubuntu-01-08 ubuntu-01-09 ubuntu-01-10 ubuntu-02-01 ubuntu-02-02 ubuntu-02-03 ubuntu-02-04 ubuntu-02-05 ubuntu-02-06 ubuntu-02-07 ubuntu-02-08 ubuntu-02-09 ubuntu-02-10 ]
[+] Waiting 2 minutes until the machines get provisioned...
[+] Waiting for outputs...
[+] Executed command on ubuntu-02-01. Output: [
Starting Nmap 7.80 ( https://nmap.org ) at ...
...
]
[+] Executed command on ubuntu-02-02. Output: [
Starting Nmap 7.80 ( https://nmap.org ) at ...
...
]
...
[+] Saved container outputs at: output.json
[+] Saved merged outputs at: all_output.txt.

The result of doing this, is that acido automatically creates 2 container groups with 10 instances, splits the targets file into 20 chunks, uploads the chunks to the instances with the name "input", runs the command provided with -t and after finishing, saves the output to a JSON file.
Requirements
OS: Mac OS / Linux / Windows
Requirement 1: Login to Azure & Create an Azure Container Registry
$ az login
$ az acr create --resource-group Merabytes \
--name merabytes --sku Basic

Requirement 2: Install acido and configure your RG & Registry
pip install acido
python3 -m acido.cli -c
$ acido -c
[+] Selecting I/O storage account (acido).
[!] Please provide a Resource Group Name to deploy the ACIs: Merabytes
[!] Image Registry Server: merabytes.azurecr.io
[!] Image Registry Username: merabytes
[!] Image Registry Password: *********
$

Optional requirement (--exec): Install tmux & Patch Azure CLI
If you want to use --exec (similar to ssh) to execute commands on running containers having tmux installed and on PATH is mandatory.
Also, for the --exec command to work properly, you need to monkey-patch a bug inside az container exec command in the sys.stdout.write function.
File: /lib/python3.9/site-packages/azure/cli/command_modules/container/custom.py
Line: 684
def _cycle_exec_pipe(ws):
r, _, _ = select.select([ws.sock, sys.stdin], [], [])
if ws.sock in r:
data = ws.recv()
sys.stdout.write(data.decode() if isinstance(data, bytes) else data) # MODIFY THE LINE LIKE THIS
sys.stdout.flush()
if sys.stdin in r:
x = sys.stdin.read(1)
if not x:
return True
ws.send(x)
return True

Upcoming features

Add argument to specify docker image of the fleet
Add argument to execute scans through the Docker ENTRYPOINT (-t / --task)
Test on Windows
Add argument to retrieve ACI logs
Add argument to create the fleet with a Network Group (route the traffic from all instances to a single Public IP)
Get rid of monkey-patching of Azure CLI for --exec

Credits / Acknowledgements

Xavier Álvarez ([email protected])
Juan Ramón Higueras Pica ([email protected])