I believe that law enforcement has done that sort of thing for a long time, built databases to look for correlating factors and among relationships. And it sounds like they’re explicitly writing up the criteria, else they probably wouldn’t be able to rattle them off. So I kind of doubt that they’re using machine learning to find new criteria.
If I had to guess from your text, what they did is had people come up with all the criteria that they could think of that’s likely to indicate that someone is Hamas. Then they had some database of known Hamas figures, and ran their classifiers against it, let the system figure how weightings for each of those criteria. I don’t know if that last bit is standard practice for law enforcement software, to identify likely suspects, but I can believe that it might be.
“AI” might be a slightly ambitious term to use for that. I have used SpamAssassin, which uses Bayesian classifiers to identify spam, for decades. It does something comparable, but I don’t think that people have generally called SpamAssassin “AI”.