Challenge 1: ExploAIt

The goal is to produce a tool which can be pointed at a victim machine, and will use AI to exploit the victim machine completely automatically and without the need for human intervention.

Teams will be provided with a series of virtual machines with known vulnerabilities as testing data. Expected output consists of the development of a fully automatic penetration test tool using Machine Learning.  The HITB testing VMs will be released the first week of July.

Team Name Team Country Organization / Affiliation

CCT

India

Cochin University of Science and Technology

nFlag

United Arab Emirates
New York University Abu Dhabi

360SA

China
Huazhong University Of Science and Technology

Attaq

United Arab Emirates
New York University Abu Dhabi

074m4K053n

Japan

NITOyC

Deep(P)en

The Netherlands
Eindhoven University of Technology

RedMind

United Arab Emirates
Etisalat / State University of New York

tAIchi

United Arab Emirates
New York University Abu Dhabi

FullHunt

United Arab Emirates
Fullhunt.io

Challenge 2: MalwAIre

The goal of this contest is to use reinforcement learning and generative adversarial networks to modify existing malware to defeat virus detection agents. Teams will receive as input, decompiled code of known malware. A successful entry will use AI to modify this code so that it still functions as malware and can successfully avoid detection by antivirus scanners.

Team Name Team Country Organization / Affiliation

L32 Ph3UX R0u932

Russian Federation

Tomsk State University

sploit00n

Russian Federation

National Research Nuclear University MEPhI

Malology

Canada

Absolute Software

Wakanda

United States of America

City University New York (CUNY)

CalCam

United States of America
University of California, Berkeley

CloudSEK-ML

India
CloudSEK

Dirichlet's Principle

UAE / Canada / USA
American Univ of Sharjah / U. Toronto / Harvard

SynVag

Greece
Georgia Institute of Technology

GoForWin

China
Qihoo360