Machine Learning for Pentesting

Employ machine learning to take your penetration testing to the next level by unlocking information and access thought impenetrable before.

4 videos  //  18 minutes of training

Free training week — 1,400+ on-demand courses and hands-on labs

Course description

This course will take your penetration testing to the next level by enriching your toolkit with machine learning-based methods. You will learn how to perform neural network-assisted fuzzing, how to break CAPTCHA systems and how to deanonymize the browsing activity of Tor users. You will unlock information and access thought impenetrable before.

Course syllabus

OverviewDuration: 0:45

CAPTCHA BreakingDuration: 6:22

Neural Network Assisted FuzzingDuration: 4:26

Deanonymizing TorDuration: 6:24

Meet the author

Emmanuel Tsukerman

LinkedIn

Dr. Tsukerman graduated from Stanford University and UC Berkeley. In 2017, his machine-learning-based anti-ransomware product won Top 10 Ransomware Products by PC Magazine. In 2018, he designed a machine-learning-based malware detection system for Palo Alto Network's WildFire service (over 30,000 customers). In 2019, Dr. Tsukerman authored the Machine Learning for Cybersecurity Cookbook and launched the Infosec Skills Cybersecurity Data Science Learning Path.

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  • 190+ role-guided learning paths (e.g., Ethical Hacking, Threat Hunting)
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  • 190+ role-guided learning paths and assessments (e.g., Incident Response)
  • 100s of hands-on labs in cloud-hosted cyber ranges
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  • Custom certification practice exams (e.g., CISSP, CISA)
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