Title is sensationalist, while the news really ain't a big deal IHMO. Adversarial attacks against Neural Networks, or any other heuristics for that matter, are widely recognized in the industry.
Frameworks/papers aiming at benchmarking and fine tuning networks against those attacks even exist (e.g. github.com/QData/TextAttack in the case of NLP).
The tools will simply be adapted. Either to a/ identify the statistical anomalies/artifacts introduced by the manipulation process, or b/ ignore the manipulation through further training or further data normalization.
Frameworks/papers aiming at benchmarking and fine tuning networks against those attacks even exist (e.g. github.com/QData/TextAttack in the case of NLP).
The tools will simply be adapted. Either to a/ identify the statistical anomalies/artifacts introduced by the manipulation process, or b/ ignore the manipulation through further training or further data normalization.