Detecting Targeted Attacks With SPuNge

Over the last number of years there has been a noticeable rise in the number of reported targeted attacks, which are also commonly referred to as advanced persistent threats (APTs). Notable examples of said attacks include the Red October campaign or the IXESHE APT.

What sets a targeted attack apart from a widespread attack is purely the motivation behind the attackers and their victims. The actual tools used are largely irrelevant; the tools are identical, but the motivations of the attackers and the targeted victims set a targeted attack apart. For example, a Remote Access Tool (RAT) that infects users across 50 countries would be considered a widespread attack – while the same attack against two nuclear power plants against no one else is an example of a targeted attack. The tool is identical but the motivation of the attackers and their chosen targets set the attacks apart.

One thing that clear about targeted attacks is that they are difficult to detect, and not much research has been conducted so far in detecting these attacks.

Our paper discusses a new system we’ve called SPuNge that processes threat information gathered via feedback provided by the Smart Protection Network to detect potential targeted attacks for further investigation.

We use a combination of clustering and correlation techniques to identify groups of machines that share a similar behavior with the respect to the malicious resources they access and the industry in which they operate (e.g. oil & gas).

The techniques we adopt include a text-based hierarchical clustering aimed at finding clusters of similar malicious URLs, i.e. having common patterns in hostnames, paths or query strings. We correlate them with information on the users machine, such as their IP address, to identify groups of customers affected by the same threat. Finally, we automatically correlate these groups with both the industry and the geographical information to discover potential targeted attacks.

We used SPuNge to examine existing feedback from more than 20 million Trend Micro customers to see if the system was effective and useful in identifying threats. The tests were able to show that SPuNge is a powerful and useful tool in assisting cybercrime investigation.

The methodology of SPuNge is described in the paper Targeted Attacks Detection with SPuNge. In addition, we discussed this topic at PST2013, the eleventh International Conference on Privacy, Security and Trust which was recently held in Tarragona, Catalonia.

Post from: Trendlabs Security Intelligence Blog – by Trend Micro

Detecting Targeted Attacks With SPuNge