Microsoft has it
Detonating a bad rabbit: Windows Defender Antivirus and layered machine learning defenses
"Within a few seconds, the file was processed, and sample-analysis-based ML models returned their conclusions. In this case, a multi-class deep neural network (DNN) machine learning classifier correctly classified the Tibbar sample as malware, but with only an 81.6% probability score. In order to avoid false positives, cloud protection service was configured to require at least 90% probability to block the malware (these thresholds are continually evaluated and fine-tuned to find the right balance between blocking malware while avoiding the blocking of legitimate programs). In this case, the ransomware was allowed to run."
(Here we have the first user)
"In the meantime, while patient zero and eight other unfortunate victims (in Ukraine, Russia, Israel, and Bulgaria) contemplated whether to pay the ransom, the sample was being detonated and details of the system changes made by the ransomware recorded.
As soon as the detonation results were available, a multi-class deep neural network (DNN) classifier that used both static and dynamic features evaluated the results and classified the sample as malware with 90.7% confidence, high enough for the cloud to start blocking."
(And here Defender is able to protect subsequent users)