Tag Archives: Security

eCrime Summit in Prague 25-27 April 2012

These ecrime meetings are always interesting and useful. -jsq

Press release of 29 March:

Containing the Global Cybercrime Threat is Focus of Counter eCrime Operations Summit (CeCOS VI) in Prague, April 25-27

CeCOS VI, in Prague, Czech Republic, to focus on harmonizing operational issues, cybercrime data exchange, and industrial policies to strengthen and unify the global counter-ecrime effort.

CAMBRIDGE, Mass.—(BUSINESS WIRE)—The 6th annual Counter eCrime Operations Summit (CeCOS VI) will convene in Prague, Czech Republic, April 25-27, 2012, as the APWG gathers global leaders from the financial services, technology, government, law enforcement, communications sectors, and research centers to define common goals and harmonize resources to strengthen the global counter-cybercrime effort.

CeCOS VI Prague will review the development of response systems and resources available to counter-cybercrime managers and forensic professionals from around the world.

Specific goals of this high-level, multi-national conference are to identify common forensic needs, in terms of the data, tools, and communications protocols required to harmonize cybercrime response across borders and between private sector financial and industrial sector responders and public sector policy professionals and law enforcement.

Key presentations will include:

Continue reading →

What other ASNs were affected by botnet Ogee in February 2012?

Previously we determined that nine ASNs that showed spam surges in the U.S. and Canadian top 10 SpamRankings.net for February 2012 were infested by the botnet Ogee and that spam came from that botnet. What other ASNs were affected by Ogee in the same time period?

Let’s look at the top 10 ASNs infested by Ogee according to spam volume for 1 Feb 2012 to 12 Mar 2012:


Left Axis: Total Ogee volume (spam messages);
Right Axis: top 10 Ogee ASN volume (dotted curves)

It looks like Ogee is a new botnet, since all these top 10 ASNs came up from zero volume before 18 February 2012. The biggest initial peak in this graph is from AS 21788 NOC, #1 in the U.S. February top 10, and the biggest late surge is from AS 10439 CARINET, #8 in that same ranking. Right below CARINET is AS 32613 IWEB-AS, Canadian February #1. The rest of the 8 Ogee-infested from the U.S. top 10 previously described also are in there, except AS 7796 ATMLINK and AS 13768 PEER1.

New here are these three: Continue reading →

Did the February 2012 spam surge come from one botnet?

SpamRankings.net saw
AS 21788NOC
AS 27229WEBHOST-ASN1
AS 46475LIMESTONENETWORKS
AS 33055BCC-65-182-96-0-PHX
AS 15149EZZI-101-BGP
AS 13768PEER1
AS 10439CARINET
AS 7796ATMLINK
a huge surge in spam from some U.S. ASNs, mostly from ones that hadn’t even been in the top 10 before, with possible correlations in one ASN each from Peru and Canada. Did all this spam come from the same botnet?

Maybe not all, but most. Eight out of the U.S. top 10 for February show very close correlation with one botnet, Ogee. They are listed in the table on the right and shown in the chart below:


Left Axis: ASN volume (spam messages); Right Axis: Botnet volume (dotted curves)

The chart also shows some ASNs reacted quickly and stopped the spamming, while others got worse. It’s a busy chart, so let’s look at simpler charts for one example each of resilient and susceptible ASNs.

AS 21788 NOC was one of the first and worst affected by this spam surge: Continue reading →

Is January’s medical spam caused by botnets?

Remember those three spamming medical organizations PSBL saw and the spike from CSHS that SpamRankings.net found in CBL data? Digging into the underlying data, and graphing them all on the same chart, we see this:

Even though the three three-digit-spamming medicos spam oddly coherently, we don’t find any botnets for them. This may be because most of that spam was seen by PSBL, and our botnet assignments come from CBL. CBL didn’t see any spam from those ASNs, so it didn’t have anything to assign for botnets. Maybe they’re infested by the same botnet; maybe not; can’t tell.

But it was CBL that saw that big spam spike for AS 22328 CSHS. And CBL did assign a botnet to that: Lethic. For all but two days of CSHS spam shown, CBL assigned Lethic to the total amount of spam from CSHS for that day. That may be because all that CSHS spam is coming from a single computer.

Of course, CBL’s botnet assignments are not perfect, but infosec professionals tell me CBL is about as good as it gets for that, so there’s a good chance this botnet assignment is correct.

The good news is that all of the trio of three-digit spamming medicos decreased their spam and even went to zero during the period shown.

And CSHS spam peaked at the end of January and started back down in February.

Pretty soon there may be once again little or no spam from medical organizations to rank.

-jsq

CSHS is back in January 2012 SpamRankings.net

In SpamRankings.net, January PSBL data reveals three three-digit U.S. medical spamming organizations, plus CSHS, and CBL data confirms a big spam spike from CSHS.

The three with more than 100 spam messages for the month were

each accounting for about a third of the total spam volume seen from medical organizations by CBL in January 2012.

Cedars-Sinai Health Systems‘ AS 22328 CSHS came in only seventh in PSBL data, with only 10 spam messages. But in CBL data, CSHS came in first, with 2,873 messages. That’s not a lot, compared to, for example, Comcast, which CBL saw spamming more than two million messages during the same month. But what patients would prefer to see from medical organizations is zero spam messages, since spam is a sneeze for infosec disease, and who wants to think their hospital’s information security or radiology computers might be infected?

Chances are CSHS will notice and clean it up pretty quick. Those other three medical orgs may have some sort of more chronic problem….

-jsq

Global Crossing spam spike, November 2011

In the November SpamRankings.net from PSBL data, Global Crossing’s AS 3549 GBLX spiked on 17 November and a few days before, pushing it into fifth place.

Did this spam spike come from any particular botnet?


AS 3549 GBLX PSBL spam volume left axis, CBL botnet volume right axis
It looks like GBLX is infested with many botnets, but the spike on 17 Nov roughly corresponds with a cutwail botnet volume peak on 16 Nov. Given that the ASN volume spike is from PSBL data and the botnet volume peak is from CBL data, a day off is plausible, due to different collection and delivery times.

There’s also a peak for grum (green line near the bottom) on 17 Nov, and peaks for festi and n/a on 18 Nov, where n/a is CBL’s marker for spam they detected without having to look as far as determining which botnet they think sent it.

So the spam spike could be from cutwail. Or it could be because of a coincidence of several botnet peaks. Or it could be some other botnet that happened to do a spam campaign on that day. Given that the PSBL GBLX peak builds up on 16 Nov, I’d guess it came mostly from cutwail.

We could try to resolve this question by digging into the specific addresses the GBLX spam PSBL saw came from and see if they match addresses CBL assigned to botnets.

-jsq

How to leverage botnet takedowns

What is to be done when botnet takedowns don’t produce lasting benefits?

At the Telecommunications Policy and Research Conference in Arlington, VA in September, I gave a paper about Rustock Botnet and ASNs. Most of the paper is about effects of a specific takedown (March 2011) and a specific slowdown (December 2010) on specific botnets (Rustock, Lethic, Maazben, etc.) and specific ASNs (Korea Telecom’s AS 4766, India’s National Internet Backbone’s AS 9829, and many others).

The detailed drilldowns also motivate a higher level policy discussion.

Knock one down, two more pop up: Whack-a-mole is fun, but not a solution. Need many more takedowns, oor many more organizations playing. How do we get orgs to do that? …
There is extensive theoretical literature that indicates Continue reading →

You can help Stop-eCrime

Stop-eCrime aims to reduce electronic crime by increasing transparency of information and communications technologies.

Born out of 2010 meetings organized by the Anti-Phishing Working Group and the IEEE Standards Association, Stop-eCrime has already been working on ecrime event data exchange standards and protocols, as well as operational protocols for dealing with computers compromised by ecrime.

Now Stop-eCrime wants you to help tie these technical and operational levels together into an ecrime detection and response system coordinated among the public, business, academia, and government. There’s plenty of work to be done on technical standards and operational protocols (such as glossaries, metrics, and monetary effects), plus Stop-eCrime needs educational materials and marketing to explain incentives for everyone to participate in reducing ecrime.

Here are the details.

If you want to help, or if you have questions, contact:

https://mentor.ieee.org/stop-ecrime
Chair: Paul Laudanski <paul@laudanski.com>

-jsq

“botnet herders can add it to its spam-spewing botnet” —Fahmida Y. Rashid in eWeek.com

This reporter spits out a string of alliterative language that labels the problem that SpamRankings.net helps diagnose.

Fahmida Y. Rashid wrote in eWeek.com 8 June 2011, UT Researchers Launch SpamRankings to Flag Hospitals Hijacked by Spammers:

“Poor security measures are generally responsible for employee workstations getting compromised, either by spam or malicious Web content. Once the machine is compromised, the botnet herders can add it to its spam-spewing botnet to send out malware to even more people. The original employee or the organization rarely has any idea the machine has been hijacked for this purpose.”
That’s a pretty good explanation for why outbound spam is a proxy for poor infosec.

-jsq

Quis custodiet ipsos medici?

Internet security is in a position similar to that of safety in the medical industry. Many doctors have an opinion like this one, quoted by Kent Bottles:
“Only 33% of my patients with diabetes have glycated hemoglobin levels that are at goal. Only 44% have cholesterol levels at goal. A measly 26% have blood pressure at goal. All my grades are well below my institution’s targets.” And she says, “I don’t even bother checking the results anymore. I just quietly push the reports under my pile of unread journals, phone messages, insurance forms, and prior authorizations.”

Meanwhile, according to the CDC, 99,000 people die in the U.S. per year because of health-care associated infections. That is equivalent of an airliner crash every day. It’s three times the rate of deaths by automobile accidents.

The basic medical error problems observed by Dennis Quaid when his twin babies almost died due to repeated massive medically-administered overdoses and due to software problems such as ably analysed by Nancy Leveson for the infamous 1980s Therac-25 cancer-radiation device are not in any way unique to computing in medicine. The solutions to those problems are analogous to some of the solutions IT security needs: measurements plus six or seven layers of aggregation, analysis, and distribution.

As Gardiner Harris reported in the New York Times, August 20, 2010, another problem is that intravenous and feeding tubes are not distinguished by shape or color: Continue reading →