What is DarkOwl Vision? 

The provider that Ontic has partnered with to provide Dark Web data to the Platform

Hackishness is defined as:  

The rating of how likely content could be used for criminal activity.

How is Hackishness used in DarkOwl Vision?

A ‘Hackishness’ rating is assigned to every piece of content collected by DarkOwl Vision, at the time of indexing. It is based on a matching learning algorithm that considers many different variables, such as patterns, metadata, terms, and more; no single element is responsible for the final score.

The Hackishness Algorithm            

The algorithm defines a set of feature vectors with over 100 independent decision variables, see the table below for examples. The algorithm is probabilistic and takes into account both the presence and the absence of these variables.        

The rating scale is from 0.01 (1%) to 1.0 (100%).

Examples of Future Vectors

Examples of Decision Variables 


Title, Domain, URL, Languages 


Social Security Number, Prose, Credentials, MD5

Attribute Metrics

Number of Credit Cards or Email Addresses 

Positive and Negative Terms 

Hack, Dox, 0 day 

Case Studies Where Hackishness Has Been Used:

  • Username or Email + Password: Hackishness AND emailDomain

  • People Selling Items (Credit Cards, Drugs, etc): Hackishness AND “credit cards”

  • Database Dumps: Hackishness AND “data found”

  • Large Volume Dumps (Credit Cards, Emails): Hackishness AND ccCount

  • Pages Containing PII: Hackishness AND “dox”

  • Government or Military Email Leaks: Hackishness AND emailDomain