  With the advance in malware technology, attackers create new ways to hide
their malicious code from antivirus services. One way to obfuscate an attack is
to use common files as cover to hide the malicious scripts, so the malware will
look like a legitimate file. Although cutting-edge Artificial Intelligence and
content signature exist, evasive malware successfully bypasses next-generation
malware detection using advanced methods like steganography. Some of the files
commonly used to hide malware are image files (e.g., JPEG). In addition, some
malware use steganography to hide malicious scripts or sensitive data in
images. Steganography in images is difficult to detect even with specialized
tools. Image-based attacks try to attack the user's device using malicious
payloads or utilize image steganography to hide sensitive data inside
legitimate images and leak it outside the user's device. Therefore in this
paper, we present a novel Image Content Disarm and Reconstruction (ICDR). Our
ICDR system removes potential malware, with a zero trust approach, while
maintaining high image quality and file usability. By extracting the image
data, removing it from the rest of the file, and manipulating the image pixels,
it is possible to disable or remove the hidden malware inside the file.
