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Ashley Madison Compromise

Last month Brian Krebs reported that the Ashley Madison database was compromised. Ashley Madison is a dating site that targets married folks who are looking to have affairs. Needless to say, there is a lot of risk for users if their data is found on the released data. Today what is supposedly the Ashley Madison data was released.
The release of this data can have some significant impacts on the site members. Of course there’s the problem of credit card numbers being stolen, but that’s something most of us have to deal with on a regular basis. But there can also be significant relationship repercussions if/when a spouse discovers that their partner has registered on a site to have affairs.
When I first heard of the compromise I wondered if they had my data. You see, they have one of my spamtraps on their unsubscribe list. It just so happened that I visited an unsubscribe link, hosted by Ashley Madison (http://unsub.ashleymadison.com/?ref=2). This was during the time when I decided to unsubscribe from all the spam coming into one of my spamtraps. Is my email address going to be a part of this data dump? If my email address is there, what name do they have associated with it? This is the trap that gets mail addressed to multiple other people. Maybe it’s my email address but their name. Are they at risk for relationship problems or legal problems due to my attempt to unsubscribe?
Of course, Ashley Madison had no incentive to make sure their data was correct. In fact, they were sued for faking data to entice paying members. How much of the released data is false and will there be real harm due to that?
I expect in the next few days someone (or multiple someones) will put up a website where those of us who are curious can search the data. I just hope that people realize how much of the data is likely to be false. Even Arstechnica cautions readers from jumping to conclusions.

TXTing

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On Friday I talked a bit about the history behind TXT records, their uses and abuses.
But what’s in a TXT record? How is it used? When and where should you use them?
Here’s what you get if you query for the TXT records for exacttarget.com from a unix or OS X command line with dig exacttarget.com txt

A brief history of TXT Records

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When the Domain Name System was designed thirty years ago the concept behind it was pretty simple. It’s mostly just a distributed database that lets you map hostname / query-type pairs to values.
If you want to know the IP address of cnn.com, you look up {cnn.com, A} and get back a couple of IP addresses. If you want to know where to send mail for aol.com users, you look up {aol.com, MX} and you get a set of four hostname / preference pairs back. If you want to know the hostname for the IP address 206.190.36.45 you look up {45.36.190.206.in-addr.arpa, PTR} and get a hostname back.
There’s a well-defined meaning to each of those query types – A is for IP addresses, MX is for mailservers, PTR is for hostnames – and that was always the intent for how DNS should work.
When DNS was first standardized, though, there was one query type that didn’t really have any semantic meaning:

Pattern matching primates

Why do we see faces where there are none? Paradolia
Why do we look at random noise and see patterns? Patternicity
Why do we think we have discovered what’s causing filtering if we change one thing and email gets through?
It’s all because we’re pattern matching primates, or as Michael Shermer puts it “people believe weird things because of our evolved need to believe nonweird things.”
Our brains are amazing and complex and filter a lot of information so we don’t have to think of it. Our brains also fill in a lot of holes. We’re primed at seeing patterns, even when there’s no real pattern. Our brains can, and do, lie to us all the time. For me, some of the important part of my Ph.D. work was learning to NOT trust what I thought I saw, and rather to effectively observe and test. Testing means setting up experiments in different ways to make it easier to not draw false conclusions.
Humans are also prone to confirmation bias: where we assign more weight to things that agree with our preconceived notions.
Take the email marketer who makes a number of changes to a campaign. They change some of the recipient targeting, they add in a couple URLs, they restructure the mail to change the text to image ratio and they add the word free to the subject line. The mail gets filtered to the bulk folder and they immediately jump to the word free as the proximate cause of the filtering. They changed a lot of things but they focus on the word free.
Then they remove the word free from the subject line and all of a sudden the emails are delivering. Clearly the filter in question is blocking mail with free in the subject line.
Well, no. Not really. Filters are bigger and more complex than any of us can really understand. I remember a couple years ago, when a few of my close friends were working at AOL on their filter team. A couple times they related stories where the filters were doing things that not even the developers really understood.
That was a good 5 or 6 years ago, and filters have only gotten more complex and more autonomous. Google uses an artificial neural network as their spam filter. I don’t really believe that anything this complex just looks at free in the subject line and filters based on that.
It may be that one thing used to be responsible for filtering, but those days are long gone. Modern email filters evaluate dozens or hundreds of factors. There’s rarely one thing that causes mail to go to the bulk folder. So many variables are evaluated by filters that there’s really no way to pinpoint the EXACT thing that caused a filter to trigger. In fact, it’s usually not one thing. It could be any number of things all adding up to mean this may not be mail that should go to the inbox.
There are, of course, some filters that are one factor. Filters that listen to p=reject requests can and do discard mail that fails authentication. Virus filters will often discard mail if they detect a virus in the mail. Filters that use blocklists will discard mail simply due to a listing on the blocklist.
Those filters address the easy mail. They leave the hard decisions to the more complex filters. Most of those filters are a lot more accurate than we are at matching patterns. Us pattern matching primates want to see patterns and so we find them.

Phishing costs company $46 million

Brian Krebs posted about a tech firm that lost $46M dollars due to fraud. The company reported in its SEC filings that the money was lost when someone impersonated an employee and directed the finance department to transfer money to outside accounts.
This is becoming more common. In some cases, DMARC authentication may stop this kind of fraud. But DMARC has a lot of deployment challenges and can cause real mail to fail delivery. In other cases, criminals are using lookalike domains and they can be authenticated and pass DMARC.
This isn’t really a bulk mail issue. And it’s certainly not a deliverability issue. But it is a security issue and I think it’s important that folks are aware of this kind of online crime. Coincidentally, as I’m writing this, I’m chatting online with a compliance person at a cloud hosting company who is brainstorming policies to block phishing URLs on their site. Email is a major vector for abuse and those of us who manage sending need to be a part of the solution.

More Yahoo! Challenges

A lot of people are reporting they’re not getting confirmation emails when signing up for the new Y! FBL program. This is causing problems with folks attempting to transfer domains to the new FBL.
Will update when I hear anything.

Continuous Testing

HubSpot recently posted an blog article comparing which was better for engagement, plain text emails or HTML emails. In a survey they sent out in 2014, 64% of the responses said they preferred the HTML and image-based emails. It seems pretty straight forward, recipients say they want HTML emails over text based emails but through their A/B testing, the text versions had a higher open rate.
They also reported:

Monitoring Your Mail Stream

One of the most important things for any mail sender to do is monitor their mail stream. There are a number of things that every mailer should pay attention to. Some are things to monitor during delivery, some are things to monitor after delivery. All of these things tell senders important information about how their mail is being received by their recipients and the ISPs.

July 2015: The Month in Email

Once again, we reviewed some of the ways brands are trying (or might try) to improve engagement with customers. LinkedIn, who frequently top lists of unwanted-but-legitimate email, announced that they’ll be sending less mail. Josh wrote about giving subscribers options for both the type and frequency of messages, and about setting expectations for new subscribers. In each case, it’s about respecting that customers really want to engage with brands in the email channel, but don’t want the permission they’ve granted to be abused. I also wrote a brief post following up on our June discussion on purchased lists, and as you’d predict, I continue to discourage companies from mailing to these recipients.

Ongoing Yahoo delays

I’ve been hearing from folks over the last few days that they’re seeing an uptick in deferrals from Yahoo! The deferrals are not uniform. ESPs report they’re seeing some, but not all, customers affected. Other ESPs aren’t seeing any changes.
It’s not just you. But it would be very worthwhile to dig into engagement and other stats. It’s possible this is a new normal at Yahoo! and they’re tightening filters to catch mail that doesn’t fit their standards but was previously difficult to filter.