  StyleGAN is the open-sourced TensorFlow implementation made by NVIDIA. It has
revolutionized high quality facial image generation. However, this
democratization of Artificial Intelligence / Machine Learning (AI/ML)
algorithms has enabled hostile threat actors to establish cyber personas or
sock-puppet accounts in social media platforms. These ultra-realistic synthetic
faces. This report surveys the relevance of AI/ML with respect to Cyber &
Information Operations. The proliferation of AI/ML algorithms has led to a rise
in DeepFakes and inauthentic social media accounts. Threats are analyzed within
the Strategic and Operational Environments. Existing methods of identifying
synthetic faces exists, but they rely on human beings to visually scrutinize
each photo for inconsistencies. However, through use of the DLIB 68-landmark
pre-trained file, it is possible to analyze and detect synthetic faces by
exploiting repetitive behaviors in StyleGAN images. Project Blade Runner
encompasses two scripts necessary to counter StyleGAN images. Through
PapersPlease acting as the analyzer, it is possible to derive
indicators-of-attack (IOA) from scraped image samples. These IOAs can be fed
back into AmongUs acting as the detector to identify synthetic faces from live
operational samples. The opensource copy of Blade Runner may lack additional
unit tests and some functionality, but the open-source copy is a redacted
version, far leaner, better optimized, and a proof-of-concept for the
information security community. The desired end-state will be to incrementally
add automation to stay on-par with its closed-source predecessor.
