Graph Theory: Analyzing Social Networks

Social networking applications are among the most popular websites that are used on the Internet. Facebook.com and myspace.com are both in the top 20 most visited pages on the internet. According to Alexa, 17% of global internet users visit facebook.com on a daily basis.

How can attackers use the abundant amounts of information that is available on these websites to aid in their attacks?

One method is by analyzing a victims social network using network analysis.

Network analysis is a way to infer information from the social connections that someone makes. An attacker could use a social applications data set to:

• identify positive and negative relationships
• identify their victims mood
• identify individuals that are most influential in a group

By assigning people and organizations to nodes and linking nodes based on relationships, attackers can begin to infer information from these social graphs.

Who is the Most Influential?
It is beneficial for an attacker to know who is the most influential person in their victim's social network. Constructing a malicious instant message or email that requires user intervention (think Reflective Cross-Site Scripting) will have a higher success rate, if it is sent from the victim's most influential friend.

In order to analyze the victim's social network from an influential perspective, the attacker begins by constructing a graph with the victim in the center and each of the victim's friends as node off of the victim.

In this example, Sam is the attacker's target. Sam has five friends, Alice, Bart, Charlie, Dave, and Ed. This would create a star graph that would look like this.

The next step is for the attacker to analyze the connections between Sam's friends. The attacker identifies that Alice communicates with Bart on a regular basis, so a link is made between Alice and Bart.

It is also easier for the attacker to understand who is the most influential by assigning a value to each vertice. Alice and Bart's vertice would change from 0 to 1, since they know one of Sam's friends. In this example, we have made the vertice larger and assigned it a number. Once the social network is analyzed the attacker will have a graph similiar to this.

Since Ed knows 3 of Sam's friends, it can be infered that Ed is the most influential in Sam's network. If an attacker wanted to send a malicious instant message or email to Sam, the attacker would have the highest rate of success if the malicious message was from Ed.

This is a simple example. In reality, social networks are vastly more complicated. However, with the use of certain API's an attacker could use network analysis to his benefit.

Quantifying XSS - Why Merchants Won't Fix Their Cross-Site Scripting Vulnerabilities

From previous articles, you should be aware that Cross-Site Scripting (XSS) is an issue that is not going away any time soon.

Unlike it's buzzword predecessor, SQL injection, Cross-Site Scripting is a difficult vulnerability to quantify. What is the risk of not remediating a Cross-Site Scripting vulnerability in your web application?

If you have recently gone through a web application assessment, the report most likely indicates the risk factor of having XSS is high. But, what evidence does the report writer have to support this statement?

Basic security teaches us that risk can be quantified as:

Risk = (Probability of the event occurring) x (The impact if the event occurs)

To support the consultants statement, we would need to identify the probability of an attacker using a Cross-Site Scripting vulnerability as an attack vector and what the impact is, if the user is exploited.

Impact
It is important to realize that XSS is a means, not an end. XSS is simply a transportation mechanism. It is used to facilitate the actual attack which could be system compromise or stealing a users session. The only limitation on XSS is that it operates in a browser enviroment.

Do to the numerous things an attacker can do with XSS, it is hard to quantify an impact for all XSS vulnerabilities. Since XSS has different severities in regards to impact, an orginization should always choose the impact that is most severe. In other words, the worst-case-scenario.

If a user is exploited through an XSS attack, an orginzation can assume the attacker is doing the most damaging thing imaginable. Therefore, if a user is compromised from XSS, the impact is high.

Probability of the Attack Occuring
We have now identified that the impact of Cross-Site Scripting is high. But, what about the probability of it actually occuring?

It is difficult to find evidence of people using Cross-Site Scripting as an an attack vector? There are cases where XSS was used, in conjunction with SQL injection, to insert an offsite iframe into a web page in order to attempt a traditional overflow. Should these attacks be included into the equation for probability of it happening? Since it can be argued that these attacks used SQL injection, and not XSS for propigation, these attacks need to be excluded.

The only evidence I can find is Verizon's 2009 Data Breach Investigation Report. That docuement however, doesn't go into much detail about the specifics of the XSS attack.

Due to the lack of overwhelming evidence, XSS currently is not a common attack method. The probability of a Cross-Site Scripting attack occuring is low.

Cost-Benefit Justification of Fixing Cross-Site Scripting
Since it is difficult to quantify the cost of having an XSS, it is just as difficult to do a cost-benefit analysis on fixing XSS vulnerabilities.

Why should merchants spend money on remediating their XSS vulnerabilities when there is no supporting evidence of attacks occuring?

Until more web applications are compromised through XSS vectors and there is more evidence to support this happening, not much security budget will go towards remediating Cross-Site Scripting vulnerabilities.

What Motivates Hackers? Why, Money of Course.

Attackers are motivated by multiple factors. Previously, "experts" believed most attackers were social outcasts who were writing malicious software out of their parent's basement. These attackers were not driven by any particular motive. They were more driven by the problem-solving aspect. They wanted to know if they could do it. This idea that attackers are socially inept kids based in the United States is quickly becoming inaccurate.

Most security articles are focused on the means of the attack. They don't address what attackers are actually after.

The four motivating factors for attackers that have been identified are:

1. Financial Gain
   
2. Notoriety
3. Political
4. Vengeance

Financial Gain
Hacking, Malware, and Worm Creation is a money making opportunity. Worms, such as Conficker, are being tied to organized crime based in Soviet republics.

The tightly managed criminal organizations behind such scams—often based in Russia and former Soviet republics—treat malware like a business. They buy advanced code on the Internet’s black market, customize it, then sell or rent the resulting botnet to the highest bidders. They extend the worm’s life span as long as possible by investing in updates—maintenance by another name. This assembly line–style approach to crime works: of all the viruses that Symantec has tracked over the past 20 years, 60 percent of them have been introduced in the past 12 months.

This shouldn't be suprising. If criminals have no problem killing another human and taking their wallet, why would they have problems stealing massive amounts of money electronically?

However, organized criminals aren't the only attackers driven by financial gain. There is also evidence of financially driven attackers being petty criminals. These are the types that don't have a great understanding of what they are doing. They can be found on websites specifically setup for trading credit card numbers or other Personally Identifiable Information (PII). Some researchers, such as Rios and Dhanjani, have done research into this subgroup.

Notoriety

There is still evidence of hacking for notoriety. Most of these attackers are the "13-19" year old kids described above. The reason these individuals attack systems is driven by their want to become famous.

A recent example is the Mikeyy worm created by Michael Mooney of StalkDaily. This sub-group usually will justify their attacks by stating, "I wanted to bring awareness to the problem." This is a constructed answer but demonstrates their want to become famous. They are clearly stating, they were the ones who wanted to bring awareness to the issue. These attackers typically have a Robin Hood type mentality of bringing knowledge to the uninformed.

Political
These attackers are politically focused or driven by political means. This group includes "hacktivists" and foreign nationals driven to cause damage to an enemy country. Examples of these attacks are the Titan Rain and more recently Power Grid hacking.

Political motivation is frightening. Many countries will not deter attackers from hacking a foreign country. In addition, law enforcement has a hard time tracking down or arresting these type of attackers due to the lack of cooperation of foreign countries.

Vengeance

These attackers are the most dangerous. They will attack people who have somehow made them upset. Their driving factor is causing as much pain as possible for their victim.

These attacks typcially target an ex-girlfriend or a celebrity. These are the electronic equivalent of breaking someone's windshield. There is nothing that can really be done to prevent it other than to stop using the internet.