This post is also available in: עברית (Hebrew)
Malware is a significant threat in the cyber security field, and when unattended to, it can gain access to confidential information, private data, and can provide an entrance point for hackers to gain control of active systems or corrupt existing data. But how can you detect these malicious pieces of code?
By analyzing suspicious activity, we might be able to avoid such attacks. While known malware families are more predictable and can be detected more easily, unknown threats can take on a variety of forms, causing a bunch of challenges for their detection.
For example, malware authors may use a “low and slow” approach, which involves sending a small amount of malicious code across a network over a long time, which makes it harder to detect and block. This can be especially damaging in corporate networks, where the lack of visibility into the environment can lead to undetected malicious activity, according to thhackernews.com.
Often, malware will be encrypted, making it difficult to detect by signature based security applications. Additionally, some malware developers will use a concept known as polymorphism, making it possible to modify the malicious code to generate unique variants of the same malware.
When analyzing known malware families, researchers can take advantage of existing information about the malware, such as its behavior, payloads, and known vulnerabilities, in order to detect and respond to it, such as using reverse engineering to analyze the code of the malware to identify its purpose and malicious nature, or testing the malware in a sandbox isolated environment where you can observe its behavior without harming the system.
Prepared to dive into the world of futuristic technology? Attend INNOTECH 2023, the international convention and exhibition for innovation at Expo, Tel Aviv, on March 29th-30th
Interested in sponsoring / a display booth at the 2023 INNOTECH exhibition? Click here for details!