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Scary Storm figure

This study of the Storm worm (via) contains this rather terrifying factoid:

Figure 12 illustrates a time-volume graph of TCP packets, SMTP packets, spam messages, and smtp servers. Our analysis of this graph reveals the following findings. First, we find that except for the first 5 minutes almost all the TCP communication is dominated by spam. Second, we measured that hosts generate on average of 100 successful spam messages per five minutes, which translates to 1200 spam messages per hour or 28,800 messages per day. If we mutiply this by the estimated size for the Storm network (which we suspect varies between 1 million and 5 million, we derive that the total number of spam messages that could be generated by Storm is somewhere between 28 billion and 140 billon per day.

While such numbers might be mind-boggling they are inline with observed spam volumes in the Internet, e.g., overall volume of spam messages in the Internet per day in 2006 was estimated to be around 140 billion [2]; Spamhaus claims to have been blocking over 50 billion spam messages per day in October 2006 [10], and AOL was blocking 1.5 billion spam messages per day in its network in June 2006 [5]. These numbers suggest that Storm could be responsible for anywhere between 17% and 50% of all spam that is generated on the Internet.

28 to 140 billion messages per day. That is a lot of spam.

Minor nitpick with the paper — it notes that

Storm retrieves emails found in [certain] files and gathers information about possible hosts, users, and mailing lists that are referenced in these files. In particular, it looks for strings like “”, “”, “rating@”, “f-secur”, “news”, “update”, “anyone@”, “bugs@”, “contract@”, “feste”, “gold-certs@”, “help@”, “info@”, “nobody@”, “noone@”, “kasp”, “admin”, “icrosoft”, “support”, “ntivi”, “unix”, “bsd”, “linux”, “listserv”, “certific”, “sopho”, “@foo”, “@iana”, “free-av”, “@messagelab”, “winzip”, “google”, “winrar”, “samples” , “abuse”, “panda”, “cafee”, “spam”, “pgp”, “@avp.” , “noreply” , “local”, “root@”, and “postmaster@”.

I would postulate that those strings are a stoplist — that in fact the worm avoids sending spam to addresses containing those strings. The presence of “abuse” and “postmaster” in particular would suggest that.