One of my roles at McAfee Avert Labs is to take a step back from the day-to-day attacks, and look at the bigger picture. To review threat trends and forecast what’s to come. Some threats such as Web Feed Attacks and IM are more easily defined and quantified. Other threats are a little more abstract after you scratch the surface.
In recent years the infamous “targeted attack” has gained much media attention. We often heard about a “segment” of users being hit, such as Myspace or Facebook users. I recall snickering the first time I heard a report stating that “home users” were the most targeted of all. I suppose next we’ll hear that Internet users are the most targeted.
So what does the word targeted in targeted attack really mean? One could argue that anyone hit with an attack that was sent to him or her specifically (as in: the email message containing the virus was sent to your address) was a victim of a targeted attack, but that definition is way too broad, as the vast majority of all attacks would then be considered targeted. I pondered the definition of targeted attacks for a bit, trying to think of a simple yet concrete definition. I landed on the work discrimination. For me the key aspect of any targeted attack is that it must discriminate, otherwise the attack is either random, or one of opportunity.
Consider Tom, a man who walks into a grocery store, and stops by the tomatoes. He gets the impulse to pick up a few of the mushy ones and hurls them at shoppers. Was this a targeted attack? I’m sure the headlines would read “XYZ Mart Shoppers Targeted by Tomato Mad Man,” but were they really? Those hit were simply in the wrong place at the wrong time; casualties of a random attack. Tom did not discriminate; he aimed for whoever was in proximity (if he aimed at all). If there happened to be five grandmothers nearby, this would still not have been a grandmother-targeted attack.
To bring this back to computer security, spammers often use massive address lists during campaigns. When spammers want to reach as many addresses as possible, they cast a wide net, sending messages to each address on the list–no discrimination, no targeted attack.
Consider a scenario in which an attacker discovers a flaw in Facebook. He may exploit that flaw to reach as many users as possible. Again, “Facebook users” were not targeted here, as there was no discrimination. The Facebook bug simply provided an opportunity.
Here’s a real-world example of a targeted attack. Select U.S. government contractors were sent email messages that contained exploited PowerPoint documents that install a remote-access Trojan on victims’ systems. Here “select U.S. government contractors” were singled out; not “government contractors,” not “email users,” not “PowerPoint users,” and not “Microsoft” (maker of PowerPoint).
In my Facebook example one could argue that the Facebook company itself was targeted; someone had to discover and exploit a flaw in that scenario to get to the user base. However, in my targeted U.S. government contractors example, few would consider Microsoft the target of that attack. The PowerPoint vulnerability was simply the means to an end, providing an opportunity.
Let’s look at another type of attack.
Some publicized targeted attacks used personal information. Potential victims may receive an email message containing not only their names, but also places of business, and possibly their titles, addresses, or phone numbers. Does that make these attacks targeted? Not necessarily. Yes, these are context-aware or personalized attacks; but without discrimination, these should not be considered targeted.
Other attacks rely on applications typically used by a segment of the population, such as music or video players, or social-networking sites. Does this mean that segment is targeted? Those users may be at a greater risk of being attacked, but that does not make them targeted. Accordingly, malicious fake video codecs and the like do not necessarily target home users!
In an effort to keep this blog from getting too long, here’s a short list of why attackers might keep an attack targeted:
- To keep a low profile for the malicious code (an effort to evade/delay malcode detection by flying under the radar)
- To keep a low profile for the entity behind the attack (an effort to evade prosecution)
- To minimize “casualties of war” (most attackers don’t really care if innocent bystanders get infected, but some small segment likely does).
Asking the questions why and how the XYZ attack was limited can help determine if the attack was indeed targeted.
What’s Really the Target?
Another litmus test when attempting to validate a targeted attack is to ask: What is really the target? If the answer is any and every username and password the attackers can get their hands on, then the attack is probably not targeted. We often hear about a bank being targeted in a massive phishing attack. Although such an attack may have been geared toward users of a single bank, one must ask Why? Imagine, how effective would a single phishing campaign be if a spammed email message listed dozens of banking sites and asked users to click the link for their banks? And if the attacker must limit the phishing messages to a single bank, one could consider this to be a process of elimination, and elimination does not equal discrimination.
I can appreciate the challenge the media face when writing the headline for an attack that affects only a segment of users. It’s just unfortunate that the term targeted is so overused that estimates of the problem can greatly vary.