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DGA-generated domain detection using deep learning models

License: MIT License

Python 100.00%
deep-learning dga dga-detection dga-domains

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awesome-security 5l1v3r1 nkzhangheng qurikuduo trellixvulnteam bhavyagaur99 aeden2019

degas's Issues

run in docker by tensorFlow serving got errors

Hi there,
Thx for your degas project, I'm new bee with tensorflow, could you pls. help me about run degas in docker with tensorflow serving. Any reply is a big help.
When I run it in docker using:

docker run -p 8501:8501
--mount type=bind,source=/Users/myUserName/PycharmProjects/degas/models/degas,target=/models/degas
-e MODEL_NAME=degas -t tensorflow/serving:1.12.0

It works fine in my docker. Then I call RESTful API by post :

{
 "instances": [
   "www.google.com","234kd3ds9fkj3.com"
 ]
}

to :
http://localhost:8501/v1/models/degas:predict
I got the error response:

{
    "error": "Failed to process element: 0 of \'instances\' list. Error: Invalid argument: JSON Value: \"www.google.com\" Type: String is not of expected type: int32"
}

and even I POST this in request, got error response too:

{
 "inputs": [
   "www.google.com","234kd3ds9fkj3.com"
 ]
}

Edit:
I did a google more, then I change my input to:

{
    "inputs":[
        {
            "input_image": [0.2]
        }
    ]
}

And I got ERROR message as below:

{
    "error": "JSON Value: {\n    \"input_image\": [\n        0.2\n    ]\n} Type: Object is not of expected type: int32"
}

Edit:
I did a google more, then I change my input to:

{
    "inputs":[
        {
            "input_image": [1,2]
        }
    ]
}

And I got ERROR message as below:


{
    "error": "JSON Value: {\n    \"input_image\": [\n        1,\n        2\n    ]\n} Type: Object is not of expected type: int32"
}

Cloud you please point me out where is wrong with my operate?
THANKS A LOT.

/**************************************************************************/

EDIT:

Already OK now.

  1. specify tensorflow and other tensorflow packages to 1.11.0 (eg. tensorflow serving etc.)
  2. post json( predict for "www.google.com", "a2x43v89es01.com", "www.twitter.com" ):
{
 "instances": [[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,0,0,37,37,37,12,21,29,29,21,26,19,12
,17,29,27]
,[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,15,2,38,4,3,36,8,9,19,33,0,1,12
,17,29,27]
,[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,0,0,0,0,0,0,0,0,0,0,0,0,37,37,37,12,34,37,23,34,34,19,32,12
,17,29,27]]
}
  1. response of tensorflow serving will be:
{
    "predictions": [
        [
            4.54876e-11
        ],
        [
            0.723077
        ],
        [
            2.9277e-18
        ]
    ]
}

/**************************************************************************/

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