“Malware authors are known for their ability to adapt and modify their skills and behaviors to take advantage of newer technologies. This has multiple benefits from the development cycle and inherent lack of coverage from protective products,” wrote Eric Milam, VP of Threat Research at BlackBerry, introducing the research.
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The researchers argue that they selected these particular four languages for analysis, not just because they are compatible with its detection methodologies, but also for their maturity level.
On their toes
Using the example of BazarLoader being rewritten in Nim, the researchers argue that when malware is authored in a new language, it has a greater chance of evading signature-based detection, which are tuned to identify its previous iteration.
The defenders will then have to create new signatures to detect these variants, either manually using human malware researchers or by using artificial intelligence (AI).
No surprise then that the researchers are tracking more loaders and droppers being written in rare languages, since it’s their job to bypass security measures before the real damaging malware can be deployed.
The researchers also believe that using more uncommon programming languages, helps the authors use the language itself as a layer of obfuscation, which not only helps bypass conventional security measures, but also hinder analysis efforts.
“Although wrappers and loaders are more cost-effective, some well-resourced threat actors are beginning to rewrite their existing malware using exotic languages,” note the researchers in their detailed analysis.
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