Andrei Cotaie is a Security Engineer specialized in Incident Response. Currently working for Adobe’s Security Coordination Center, Andrei made the transition from the public to the private sector almost 7 years ago. A big fan of automation and machine learning enthusiast, Andrei spends most of his time involved in monitoring and threat hunting projects, always trying to identify the latest unconventional attacks.

Hunting for LoLs (a ML Living of the Land Classifier)

Living of the Land is not a brand-new concept. The knowledge and resources have been out there for several years now. And still, LoL is one of the preferred approaches when we are speaking about highly skilled attackers or security professionals. Two main reasons why:

1. Experts tend not to reinvent the wheel
2. Attackers like to keep a low profile/footprint (no random binaries/scripts on the disk)

The talk focuses on detecting attacker activity/Living of the Land commands using Machine Learning, for both Linux and Windows systems.

The presentation covers why it is hard to detect LoLs, the feature engineering used in our approach, comparison between different classifiers as well as hands-on experience using our library and integration into one of our previous open-source projects called One-Stop-Anomaly Shop (OSAS – https://github.com/adobe/OSAS). Additionally, we also discuss why OSAS and the LoL classifier are complementary solutions and how evading one will lead to being detected by the other.

This presentation is co-presented with Tiberiu Boros, Data Scientist / Machine Learning Engineer at Adobe.