Genetic Algorithms for Brute Forcing

Presented at Hackfest 2017, Nov. 4, 2017, 10 a.m. (Unknown duration).

Machine Learning algorithms have many applications in Cyber Security; while, most of these applications are directly related to defensive aspects such as intrusion detection and prevention, machine learning algorithms may be used to attack systems as effectively as it can be used to defend them.

This brief talk introduces a tool that leverages a basic machine learning solution-a genetic algorithm-as a way to brute force obfuscated or randomly generated URLs. Compared to some traditional methods (such as a naive brute force) this approach can have a high success rate.


Presenters:

  • Christopher Ellis
    Chris entered into the security space accidentally as a hobby first, and now works for a large company as part of a red team and penetration testing group. In his spare time, Chris builds security-related tooling and scripts that fall in a wide variety of spaces from data exfiltration and ransomware distribution to brute forcing and vulnerability scanning.

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