A number of anti-SPAM systems use distributed checksums for detecting and eventually filtering SPAM messages. The idea is that a SPAM message is likely to be sent to a large number of recipients across the Internet; maintaining a central database with the checksum of the single messages passing to MTA servers allows you to compare them and check if they repeat a sufficient amount of time for classifying them as SPAM.
The checksum is usually not computed against the entire message, but rather on different parts every time using fuzzying and/or random algorithms because SPAM messages might be slightly different for every recipient, including a different name in the first greeting line for instance. For every message received, an MTA that implements a distributed check summing-based filter will connect to a specified server, send the checksum, get the response back, and evaluate the results.
Distributed checksums require careful whitelisting for all legitimate traffic that, for some reason, is sent to a large number of recipients, most notably mailing list traffic (especially on large announcement lists). It also increases network traffic on your end since every received message requires a lookup on a central server.
Several filters that implement this idea are available, most notably DCC, Razor, and Pyzor.
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