AST September 2018 'ASTORS' Showcase Edition Sep 2018 Final (9.18.18) | Page 39

Attacks
with a scan of the network tack paths, analyze attacks,
and automate
Volume begin
27
September 2018 Edition
from the infected endpoint to locate the incident response through 3rd party integra-
asset and services an attacker wants to tar- tions.
get.
Detection
By turning the environment into a virtual “hall
of mirrors,” deception disrupts an attacker’s re- The ThreatDefend platform is designed
ality and imposes increased cost as they are for the most sophisticated human and
forced to decipher what is real versus fake.
automated attackers and is unique in that
One small mistake will reveal the attacker’s it offers endpoint, network, data, appli-
presence and force them to start over or aban- cation, Active Directory, and database
don their efforts altogether.
deceptions to detect ever-changing attack
methods.
The ThreatDefend approach also addresses
the debate of whether deception is best suit- Both small and large organizations can benefit from
built-in machine-learning, which automates de-
ed at the endpoint or in network.
ployment and simplifies operations by auto-propos-
ing deception campaigns.
Simply put, you need both to catch all
threat vectors and their attempts of This maintains the highest levels of authenticity
reconnaissance or credential theft.
and provides an automated refresh of the decep-
tion environment in order to amplify deceptions
Additionally, ThreatDefend high-interac- based on user behavior, reset the attack surface
tion deception technology engages attack- on-demand, avoid fingerprinting, or simply reset
ers to gain threat intelligence, identify at- the attack surface after a compromise.
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