Tag Archives: BSNL-NIB

Why no kelihos rampage in PSBL October 2012 SpamRankings.net?

Why do the PSBL Volume October 2012 SpamRankings.net rankings from PSBL data not look much like the October 2012 rankings from CBL data in SpamRankings.net? Apparently because PSBL does not use the heuristic that CBL uses that catches the few IP addresses that are spewing hundreds of thousands or millions of spam messages a day. Is this lack of correspondence between the CBL and PSBL rankings a problem?

What would be the point of having multiple rankings if they always showed the same results? CBL Volume October 2012 SpamRankings.net But these are very different results: none of the CBL top 10 show up in the PSBL top 10! How can both the PSBL and CBL rankings be correct?

  1. First, “correct” for such rankings does not mean completely accurate and it does not mean completely precise: no blocklist will ever detect every spam message emitted by every IP address. Suppose even mighty NSA (No Such Agency) were to copy every bit that passed over every major ISP in the U.S. Even that would miss some bits emitted by for example an ISP in Vietnam that spammed an ISP in India. And what heuristics would mighty NSA use to detect all the spam from all those bits? Would those heuristics happen to include the same one CBL is using to detect the Kelihos rampage? Would they include some further heuristic of which CBL has not yet thought that would detect some other rampage? Quite possibly yes and yes. Any rankings of anything on the Internet are always approximate records of hints and whispers of a constantly-shifting reality that can never be completely pinned down.
  2. Second, correct for rankings means comparable among the ASNs ranked, so that they can be ranked. In that sense, yes, both the PSBL and CBL rankings are correct: they merely show different aspects of the spam symptom of defective infosec for the ranked ASNs.
  3. Third, any systematically ranked symptom of poor infosec is important. Does any organization want any of its hosts to be spewing hundreds of thousands of spam messages a day, as in those ASNs in the CBL top 10? Does any organization want any of its hosts to be spewing enough spam in aggregate to turn up in the PSBL top 10? Probably not.
Besides, actually the CBL data does corroborate the PSBL data, when viewed in another set of rankings. Continue reading →

Data storage issues in SpamRankings.net

Data storage issues led to loss of some incoming data for the September 2012 SpamRankings.net. Interestingly, the results seem almost normal anyway. Here is a speculation on why that can be.

Look just under any rankings chart for September 2012 and you’ll see this notice:

CBL dropouts 8,11 September 2012 were on our end.
PSBL data is unusable 4-15 Sep 2012 due to problems on our end.
September 2012 World All SpamRankings.net from CBL Volume
1 (2) AS 9829 BSNL-NIB India IN
2 (1) AS 25019 SAUDINETSTC-AS Saudi Arabia SA
3 (5) AS 6147 SAA Peru PE
4 (3) AS 8386 KOCNET Turkey TR
5 (4) AS 7643 VNPT-AS-VN Vietnam VN
6 (-) AS 9050 ROMTELECOM Romania RO

The source of the problem was embarassingly simple and easily fixed: not enough inodes. The CBL and PSBL data were affected differently because they arrive differently. We pick up from CBL daily a text summary table with a line per IP address. We get from PSBL an NNTP feed of spam messages, each in its own file, that we boil down to a summary. So for CBL, we either got the whole file (most days of the month), or we didn’t store it at all (8 and 11 September). For PSBL, for each incoming message, we either stored it or we didn’t. Which is why there are some days with PSBL data between 4 and 15 Sep, but the volume is lower than usual. The notice below the chart is dire because we prefer to be conservative about these things.

Yet the PSBL rankings show AS 9829 BSNL-NIB #1 worldwide just like Continue reading →