DBotPredictOutOfTheBoxV2

Details

ID	`DBotPredictOutOfTheBoxV2`
Language	python
From Version	5.5.0
Docker Image	`demisto/ml:1.0.0.6144857`
Tags	phishing ml

README

Predict phishing incidents using the out-of-the-box pre-trained model.

Script Data

Name	Description
Script Type	python3
Tags	phishing, ml
Cortex XSOAR Version	5.5.0

Inputs

Argument Name	Description
emailSubject	Subject of the email.
emailBody	Body of the email.
emailBodyHTML	HTML body of the email. Only use this field if the emailBody argument is empty.
topWordsLimit	Maximum number of positive/negative words to return for the model decision.
wordThreshold	Threshold to determine word importance (range 0-1). Default is 0.05.
minTextLength	Minimum number of characters for the prediction.
labelProbabilityThreshold	The label probability threshold. Default is 0.
confidenceThreshold	The confidence threshold. The model will provide predictions only if their confidence is above this threshold.
returnError	Whether to return an error when there is no prediction. Default is “true”.
setIncidentFields	Whether to set Cortex XSOAR out-of-the-box DBot fields.

Outputs

Path	Description	Type
DBotPredictPhishingWords.Label	The predicted label.	String
DBotPredictPhishingWords.Probability	The predicted probability (range 0-1).	Number
DBotPredictPhishingWords.PositiveWords	A list of words in the input text that supports the model decision.	Unknown
DBotPredictPhishingWords.NegativeWords	A list of words in the input text that do not support the model decision. These words better support a different classification class.	Unknown
DBotPredictPhishingWords.TextTokensHighlighted	The input text (after pre-processing) with the positive words that support the model decision.	String

Source

DBotPredictOutOfTheBoxV2.py DBotPredictOutOfTheBoxV2.yml

Download History Raw

args:
- description: Subject of the email.
  name: emailSubject
- description: Body of the email.
  name: emailBody
- description: HTML body of the email. Only use this field if the emailBody argument is empty.
  name: emailBodyHTML
- defaultValue: '20'
  description: 'Maximum number of positive/negative words to return for the model decision. '
  name: topWordsLimit
- defaultValue: '0.05'
  description: Threshold to determine word importance (range 0-1). Default is 0.05.
  name: wordThreshold
- defaultValue: '5'
  description: Minimum number of characters for the prediction.
  name: minTextLength
- defaultValue: '0.9'
  description: The label probability threshold. Default is 0.
  name: labelProbabilityThreshold
  deprecated: true
- description: The confidence threshold. The model will provide predictions only if their confidence is above this threshold.
  name: confidenceThreshold
- auto: PREDEFINED
  defaultValue: 'true'
  description: Whether to return an error when there is no prediction. Default is "true".
  name: returnError
  predefined:
  - 'true'
  - 'false'
- auto: PREDEFINED
  defaultValue: 'false'
  description: Whether to set Cortex XSOAR out-of-the-box DBot fields.
  name: setIncidentFields
  predefined:
  - 'true'
  - 'false'
commonfields:
  id: DBotPredictOutOfTheBoxV2
  version: -1
enabled: true
name: DBotPredictOutOfTheBoxV2
outputs:
- contextPath: DBotPredictPhishingWords.Label
  description: The predicted label.
  type: String
- contextPath: DBotPredictPhishingWords.Probability
  description: The predicted probability (range 0-1).
  type: Number
- contextPath: DBotPredictPhishingWords.PositiveWords
  description: A list of words in the input text that supports the model decision.
  type: Unknown
- contextPath: DBotPredictPhishingWords.NegativeWords
  description: A list of words in the input text that do not support the model decision. These words better support a different classification class.
  type: Unknown
- contextPath: DBotPredictPhishingWords.TextTokensHighlighted
  description: The input text (after pre-processing) with the positive words that support the model decision.
  type: String
script: '-'
subtype: python3
timeout: 60µs
type: python
dockerimage: demisto/ml:1.0.0.6144857
tests:
- DbotPredictOufOfTheBoxTestV2
- VerifyOOBV2Predictions-Test
tags:
- phishing
- ml
comment: Predict phishing incidents using the out-of-the-box pre-trained model.
fromversion: 5.5.0