Stenography and data obfuscation to avoid malware detection is a pretty well understood concept in cyber security. Red teams across the globe easily hide malware in all kinds of arbitrary places. And if you're deploying a payload of malware, it doesn't need to be contiguous.
BREAK llama 3 reply below about non-contiguous data and malware.
Yes, there have been several historic malware campaigns that leveraged non-contiguous data to deliver a payload and bypass detection. Here are a few examples:
Stuxnet (2010): Stuxnet was a highly sophisticated computer worm that targeted industrial control systems, particularly those used in Iran's nuclear program. It used a technique called "data hiding" to conceal its payload within non-contiguous areas of the hard drive, making it difficult to detect.
Duqu (2011): Duqu was a malware campaign that used a similar technique to Stuxnet, hiding its payload in non-contiguous areas of the hard drive. It also used a "dropper" file to load the malware into memory, making it harder to detect.
Flame (2012): Flame was a highly complex malware campaign that used a technique called "fragmented malware" to deliver its payload. It broke its payload into smaller, non-contiguous pieces and stored them in different locations on the infected system, making it difficult to detect.
Havex (2013): Havex was a malware campaign that targeted industrial control systems, particularly those used in the energy and manufacturing sectors. It used a technique called "data fragmentation" to break its payload into smaller, non-contiguous pieces and store them in different locations on the infected system.
BlackEnergy (2015): BlackEnergy was a malware campaign that targeted industrial control systems, particularly those used in the energy sector. It used a technique called "non-contiguous memory allocation" to load its payload into memory, making it harder to detect.
NotPetya (2017): NotPetya was a highly destructive malware campaign that used a technique called "kernel-mode rootkit" to hide its payload in non-contiguous areas of the hard drive. It also used a "dropper" file to load the malware into memory, making it harder to detect.
These malware campaigns demonstrate the use of non-contiguous data to deliver a payload and bypass detection. They often employed techniques such as:
Data hiding: Concealing the payload within non-contiguous areas of the hard drive or memory.
Data fragmentation: Breaking the payload into smaller, non-contiguous pieces and storing them in different locations.
Non-contiguous memory allocation: Loading the payload into non-contiguous areas of memory.
Dropper files: Using a separate file to load the malware into memory, making it harder to detect.
These techniques made it challenging for traditional signature-based detection methods to identify the malware, and highlighted the need for more advanced detection methods, such as behavioral analysis and anomaly detection.
