The new resort for malware developers – Uncommon Languages

July 29, 2021
Uncommon Languages new resort malware developers golang dlang rust nim

For those who wonder how attackers are becoming so secretive yet efficient, the answer lies in their utilization of uncommon languages such as Go, Dlang, Rust, and Nim. These languages help them to elude detection in addition to making their development more proficient. Researchers have become curious about the increasing use of these languages for malware activities on the internet by attackers and malware developers.

 

Advantage of the new languages for malware developers

Malware developers make use of new languages to take advantage of internet users. There are many reasons why an attacker will adapt to a new language, including taking care of any existing vulnerability and boosting the general performance. It also might provide the developers with a simpler syntax along with enhanced memory management.

Since malware developers will be taking advantage of the benefits of these new languages, professionals, on the other hand, working against these attackers will face troubles. One of the primary reasons is that their tools to analyze malware might not efficiently detect these uncommon yet complex languages. Some professionals might not be even well educated on the newer languages and thus delay the analysis.

 

How were malware written in old languages decoded?

No longer are malware written in universally known languages, unlike the old days. Generally, the older malware and encryption using AES, RC4, or XOR are only used after the malware is stored in an encrypted file. Now that the newer ones are replacing the old malware written in previous traditional languages, the encrypted files can no longer be decoded. In addition, the binary can’t be loaded into the memory by introducing it in a running procedure. This allowed the malware developers to save a significant amount of their time. To conclude, malware written in newer and uncommon languages is difficult to detect.

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