As we resume our tour of advanced use cases for Network Security Analysis, it’s time to consider malware analysis. Of course most successful attacks involve some kind of malware at some point during the attack. If only just to maintain a presence on the compromised device, some kind of bad stuff is injected. And once the bad stuff is on a device, it’s very very hard to get rid of it – and even harder to be sure. Most folks (including us) recommend you just re-image the device, as opposed to trying to clean the malware.

This makes it even more important to detect malware as quickly as possible and (hopefully) block it before a user does something stupid to compromise their device. There are many ways to detect malware, depending on the attack vector, but a lot of what we see today is snuck through port 80 as web traffic. Sure, dimwit users occasionally open a PDF or ZIP file from someone they don’t know, but more often it’s a drive-by download, which means it comes in with all the other web traffic.

So we have an opportunity to detect this malware when it enters the network. Let’s examine two situations, one with a purpose-built device to protect against web malware, and another where we’re analyzing malware directly on the network analysis platform.

Detecting Malware at the Perimeter

As we’ve been saying throughout this series, extending data collection and capture beyond logs is essential to detecting modern attacks. One advantage of capturing the full network packet stream at the ingress point of your network is that you can check for known malware and alert as they enter the network. This approach is better than nothing but it has two main issues:

  1. Malware sample accuracy: This approach requires accurate and comprehensive malware samples already loaded into the device to detect the attack. We all know that approach doesn’t work well with endpoint anti-virus and is completely useless against zero-day attacks, and this approach has the same trouble.
  2. No blocking: Additionally, once you detect something on the analysis platform, your options to remediate are pretty limited. Alerting on malware entering the network is useful, but blocking it is much better.

Alternatively, a new class of network security device has emerged to deal with this kind of sneaky malware, by exploding the malware as it enters the network to understand the behavior of inbound sessions. Again, given the prevalence of unknown zero-day attacks, the ability to classify known bad behavior and see how a packet stream actually behaves can be very helpful. Of course no device is foolproof, but these devices can provide earlier warning of impending problems than traditional perimeter network security controls.

Using these devices you can also block the offending traffic at the perimeter if it is detected in time, reducing the likelihood of device compromise. But you can’t guarantee you will catch all malware, so you must figure out the extent of t he compromise. There is also a more reactive approach: analyzing outbound traffic to pinpoint known command and control behavior and targets, which usually indicating a compromised device. At this point the device is already pwned, so you need to contain the damage.

Either way, you must figure out exactly what happened and whether you need to sound the alarm.

Containing the Damage

Based on the analysis on the perimeter, we know both the target device and the originating network address. With our trusty analysis platform we can then figure out the extent of the damage. Let’s walk through the steps:

  1. Evaluate the device: First you need to figure out if the device is compromised. Your endpoint protection suite might not be able to catch an advanced attack, so search your analysis platform (and logging system) to find any configuration changes made on the device, and look for any strange behavior – typically through network flow analysis. If the device is still clean all the better. But we will assume it’s not.
  2. Profile the malware: Now you know the device is compromised, you need to figure out how. Sure you could just wipe it, but that eliminates the best opportunity to profile the attack. The network traffic and device information enable your analysts to piece together exactly what the malware does, replay the attack to confirm, and profile its behavior. This helps figure out how many other devices have been compromised, because you know what to look for.
  3. Determine the extent of the damage: The next step is to track malware proliferation. You can search the analysis platform to look for the malware profile you built in the last step. This might mean looking for communication with the external addresses you identified, identifying command and control patterns, or watching for the indicative configuration changes; but however you proceed, having all that data in one place facilitates identifying compromised devices.
  4. Watch for the same attack: You know the saying: “Fool me once, shame on you. Fool me twice, shame on me.” Shame on you if you let the same attack succeed on your network. Add rules to detect and block attacks you have seen for the future.

We have acknowledged repeatedly that security professionals get no credit for blocking attacks, but you certainly look like a fool if you get compromised repeatedly by the same attack. You are only as good as your handling of the latest attack. So learn from these attacks; the additional data collection capabilities of network security analysis platforms can give you an advantage, both for containing the damage and for ensuring it doesn’t happen again.

As we wrap up this Applied Network Security Analysis series early next week, we will examine the use case of confirming a breach actually happened, and then revisit the key points to solidify our case for capturing network traffic as a key facet of your detection capabilities.