There is another reason why the article got my attention; my manager, Steve Lipner, is one of the few people to have designed and built a TCSEC A1 assured system and lived to tell the tale. None were sold, but they built one!

The NSA-directed project, the Tokeneer ID Station (TIS), involved building a low-defect system that conforms "to the Common Criteria requirements for Evaluation Assurance Level 5 (EAL5)" in a "cost effective manner." I'm all for this, because building high-assurance solutions is not cheap.

There's a paper with more technical detail about the project that is worth a read.

In my opinion, the project is only a science project, an experiment, for the following reasons:

• It's tiny. Weighing in at a little under 10 KLOC.
• It's only a very small portion of a much larger solution which has not been developed using the same rigor. This bit of context makes the solution as a whole moot. Call me cynical, but my question is "can the entire solution be built with same rigor in a ‘cost effective manner'?" Perhaps it can, but that is not what is presented.
• It sits on top of many operating systems (Windows, Mac OS X and Linux) that are not EAL5 certified. So it would be a little like having an EAL5 certified CharMap application running on EAL4 Windows Vista.
• It's written in a subset of Ada called SPARK, and SPARK skills are not common in the marketplace. Interestingly, SPARK makes use of annotations to help drive the static analysis process. While not a total analog, we also recommend Microsoft development teams use annotations (SAL) to help drive the required static analysis process.
• The application has a large number of dependencies that are not part of the project:

In the SDL we call these files ‘giblets' because they are components needed for your application to operate, but they do not belong to your team. Some of the files look old and highly vulnerable, such as libpng-3.dll from 2001! OSVDB lists 23 vulnerabilities since 2002 in libpng!

In summary, the TIS project is very interesting to a small number of important but specialized customers, such as the NSA, for whom this kind of research is critical. I too found it interesting, but the process is far from a set of "secrets to writing secure code" and the tools are certainly not within reach of day-to-day applications and not applicable to developing complete solutions.

After Interop Las Vegas you may have seen our analysis of the data that we collected and delivered in our NOC view.  I thought I’d recreate the same data for NY and do a short comparison.

1) Like in Vegas, uptime for the network 100%.  This is no small feat considering that we introduced a new wrinkle in NY, taking down the primary NOC while the education portion of the show was still going on.  This was a forced failover to the backup systems, and it went flawlessly.  I’d like to give a little credit to EM7 on the 100% uptime as it caught a failover to battery power that allowed AC to be restored before a series of critical equipment would have gone down.

2) Again like Vegas, the average monitored device in the show network didn’t even hit 10% CPU utilization.  Still lots of computing overhead availabe in the show network.

3) The NY show network wasn’t nearly as busy as in Las Vegas, sustaining an average of only 27Mbps of usage (versus 56 Mbps) in Vegas.

4) Power consumption for the network and NOC in NY clocked in at 445kwh per day, about 25% less than the Las Vegas show.  This wasn’t because the equipment was any more power efficient, but instead because the show was smaller and therefore there was less network gear.

5) Finally, a stat we didn’t track too carefully in Las Vegas, but that I find interesting.  During show hours the wireless network average 1,100 users attached.  That’s a lot of people and a lot of wireless devices.

The good news is there was nothing too unexpected in the data, overall the smaller show led to a smaller number of tickets and smaller consumption of resources across the board.  We hope to have the opportunity to work with the InteropNet team again next year and take a look at this data year-over-year for each show.

After 26 days, and almost 350 million e-mail messages, only 28 sales resulted -- a conversion rate of well under 0.00001%. Of these, all but one were for male-enhancement products and the average purchase price was close to $100. Taken together, these conversions would have resulted in revenues of $2,731.88 -- a bit over $100 a day for the measurement period or $140 per day for periods when the campaign was active. However, our study interposed on only a small fraction of the overall Storm network -- we estimate roughly 1.5 percent based on the fraction of worker bots we proxy. Thus, the total daily revenue attributable to Storm's pharmacy campaign is likely closer to $7000 (or $9500 during periods of campaign activity). By the same logic, we estimate that Storm self-propagation campaigns can produce between 3500 and 8500 new bots per day.

Under the assumption that our measurements are representative over time (an admittedly dangerous assumption when dealing with such small samples), we can extrapolate that, were it sent continuously at the same rate, Storm-generated pharmaceutical spam would produce roughly 3.5 million dollars of revenue in a year. This number could be even higher if spam-advertised pharmacies experience repeat business. A bit less than "millions of dollars every day," but certainly a healthy enterprise.

Of course, the authors point out that it's dangerous to make these sorts of generalizations:

We would be the first to admit that these results represent a single data point and are not necessarily representative of spam as a whole. Different campaigns, using different tactics and marketing different products will undoubtedly produce different outcomes. Indeed, we caution strongly against researchers using the conversion rates we have measured for these Storm-based campaigns to justify assumptions in any other context.

Spam is all about economics. When sending junk mail costs a dollar in paper, list rental, and postage, a marketer needs a reasonable conversion rate to make the campaign worthwhile. When sending junk mail is almost free, a one in ten million conversion rate is acceptable.

News articles.