Polymorphic malware definition
Polymorphic malware is a wider term for malicious software that can change or mutate its code and appearance to avoid detection. Polymorphic malware may include polymorphic viruses, worms, trojans, bots, or keyloggers.
Polymorphic malware is designed to constantly modify its characteristics (like file signatures, encryption keys, or obfuscation techniques) while retaining its malicious functionality. It aims to appear different every time it infects a system or device, making it difficult for traditional security measures to detect and block it effectively.
See also: polymorphic virus
How polymorphic malware spreads
- Email attachments. Polymorphic malware can be disguised as an innocent-looking email attachment, such as a document or a compressed file. When a user opens or downloads the attachment, the malware infects the device.
- Malicious websites. Polymorphic malware can be distributed through compromised or malicious websites. Users may unknowingly download infected files or software from these websites, allowing the malware to enter and infect their systems.
- Network vulnerabilities. Polymorphic malware can exploit security vulnerabilities in network services, such as outdated software or weak passwords, to access systems and spread.
Detecting polymorphic malware
- Behavior-based analysis. This method involves monitoring how programs and files act when they're running. With behavior-based analysis, you can detect unexpected file modifications, privilege changes, file encryption, or code injections.
- Heuristics. Heuristic analysis involves examining the behavior and characteristics of files or code to detect potentially malicious patterns or activities. Heuristics focuses on identifying suspicious behaviors or code structures that are commonly associated with malware rather than relying solely on known signatures.
- Machine learning and AI. Machine learning algorithms could be trained to recognize patterns and characteristics of malware, including polymorphic variants. These algorithms could detect previously unseen polymorphic malware based on similarities to known malicious patterns by analyzing large amounts of data and learning from known malware samples.
