SQRRL threat hunting platform

DataWorks Summit/Hadoop Summit
Jul. 10, 2016
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
SQRRL threat hunting platform
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SQRRL threat hunting platform

Editor's Notes

  1. Identify Pain Point It is hard to find attackers moving from a beechhead machine to more interesting machines in a sea of login data Every Windows machine has tens to hundreds of logins a day normally Project datasets Use a subset of windows event login data most likely to contain attacker movement Constrain Output LMs will only be of certain login chain shapes Localized in time Identify Algorithms Use modern classifiers on projected log event set to identify logins that are more or less likely to be in a LM Use motif search algorithms to find patterns of logins that fit the output constraints Self-learning and feedback