ML.NET Anomaly detection of missing values or gaps in data. ex. missing montly invoices

Is your feature request related to a problem? Please describe. I am looking for an easy way to implement ML.NET (or another? solution for finding missing data/gaps in data. With current methods I am able to find spikes (upside/downside) but If there will be slight decreasing overtime to zero (zero or missing value won't be flagged as anomaly)

Few potential scenarios

1. Webservice receives requests and there's gaps indicating service was offline.
2. I am receiving many invoices but for example I am receiving 1 phone bill monthly. If i don't get it (missing in my data). I'd like to find that in months between 05.2022-07.2022 is a gap and invoice is missing (I know I can implement manual checking for each month but looking for more complex solution to avoid manually checking or selecting for seconds/minutes/months/years a period.
3. Same as above but more complex I am receiving 3-5 invoices and received none In some period of data (propably existing solutions can partially fit it)
4. I have invoices and each should have 3-10 positions but I have few with only 1 (potentially some integrations broken and data is missing)