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These units are available for abuse in reflected and amplified DDoS attacks. The susceptible gadgets themselves can also be leveraged towards the buyer in middleperson attacks. In this presentation Skip Duckwall, @passingthehash on twitter and Benjamin Delpy, @gentilkiwi on twitter and the creator of Mimikatz, will display just how completely compromised Kerberos can be less than real environment conditions. In this speak, I suggest an answer: an obfuscation-resilient ensemble similarity assessment method that addresses polymorphism, packing, and obfuscation by estimating code-sharing in many static and dynamic complex domains at once, such that it is extremely difficult for a malware author to defeat all of the estimation functions at the same time. A significant limitation of these existing approaches, however, is that they are both scalable but effortlessly defeated or that they are complicated but do not scale to thousands and thousands of malware samples. To make this algorithm scale, we use an approximate function counting method and a aspect-hashing trick drawn from the device-understanding area, allowing for the quickly characteristic extraction and quickly retrieval of sample «in close proximity to neighbors» even when managing hundreds of thousands of binaries. A final problem is that even the additional elaborate techniques described in the research literature have a tendency to only exploit just one «characteristic area,» be it malware instruction sequences, contact graph composition, application binary interface metadata, or dynamic API contact traces, leaving these procedures open up to defeat by intelligent adversaries.

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