Ryan Permeh, Cylance:
"The Cylance engine is not an antivirus engine. Unlike AV, it doesn’t have a bias toward letting everything run. The technology doesn't assume a file is good until it’s evaluated. Our approach is to measure and decide on each and every file individually, and if it doesn't fit into our model of good, it leans towards bad.
"Without a bunch of data to base a decision on, and without any real patterns of goodness to identify it as such, the engine leaned heavily on the structural bits that are odd and drew a line towards bad in this case.
"When we train models, we train on hundreds of millions of good and hundreds of millions of bad files (samples). We look at several million potential data points (features) in each file...
"...In general, a piece of code can become "bad" by doing things that lean towards bad. But it can also lean towards bad by not doing things that lean towards good. So in the most basic example provided (hello world in debug build):
"The sample was small. It didn't show any bad, but it didn't show any good either; One function programs are almost always malware; Debug builds are statistically weird; Using mingw rather than visual studio is statistically weird. The output binary is 'odd.'