Awesome
An artificial neural network and API to detect Windows malware, based on Ergo and LIEF.
Installation
cd /path/to/ergo-pe-av
sudo pip3 install -r requirements.txt
Use as an API
ergo serve /path/to/ergo-pe-av --classes "clean, malware"
From the client, to scan a file that the server can access too:
curl "http://localhost:8080/?x=/path/to/file.exe"
# or
curl --data "x=/path/to/file.exe" "http://localhost:8080/"
To upload the whole file:
curl -F "x=@/path/to/file.exe" "http://localhost:8080/"
To encode a file to a vector of raw features:
curl -F "x=@/path/to/file.exe" "http://localhost:8080/encode"
To scan a vector of raw features:
curl --data "x=0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.847058823529,......" "http://localhost:8080/"
Model Statistics
The dataset is made of ~200000 samples divided in two subfolders:
classes/pe-malicious
with 100000 malware samples from VirusTotalclasses/pe-clean
with 100000 clean samples
The dataset.csv
training file has been generated with:
ergo encode ergo-pe-av /media/evilsocket/4TB/datapath-pe/classes --filter "*.exe"
Training | ROC/AUC |
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Training | Validation | Testing |
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License
Made with ♥ by the dev team and it is released under the GPL 3 license.