Malware is the broad category name for harmful code used in cyberattacks that affect laptops, desktops, servers, mobile devices, and, more recently, IoT devices.
Let’s Define Malware
The list of malicious attacks that fall under the category of malware is extensive – and it keeps getting longer and longer. While the first samples of malware started as viruses, it now comprises major types such as worms, Trojan horses, spyware, adware, rootkits, botnets, and ransomware.
Many subtypes exists as well, while some samples of malware can be categorized under multiple classifications based on what it is designed to accomplish and how. The categories list above are helpful guides to discuss the topic of malware and provide a framework to discuss its capabilities and intent.
While there are many different types of malware, with unique characteristics and goals, there are seven key traits that are common to almost all malware:
As seen in these industry statistics, malware as a whole is pervasive and costly – and almost every company is a victim.1
$2.4 million spent, on average, defending against malware
50 days pass, on average, resolving a malware attack
250K new samples of malware are discovered every day
Carbon Black’s data found that malware was at the root of 48% of all cyberattacks in 2017. However, of all the malware in use today, ransomware is the one that is of the most concern for every security professional in companies large and small. Here’s why:
Cybercriminals are very successful at using malware to achieve their goals for the simple reason that most traditional antivirus tools use static analysis as a primary security tactic. However, these tools only can identify known samples – and today, with the rapid development of new malware every day, the majority of it now appears as unknown files. Attackers use various techniques like packing, or compressing, to change aspects of the malware so it looks different than known threats. As such, the attacks easily slip through antivirus defenses.
This is where next-generation endpoint security – and behavior analytics – comes in. The good news about malware is that how it operates within a system or device will eventually appear different than normal user behavior. Therefore, with big data and machine learning zeroing in on anomalies, potential malware can be identified as out-of-the-norm and potentially malicious.