"Threat Classification" refers to the categorization of threats and risks into specific classes or categories in the cybersecurity realm. This classification is a framework used to better understand, identify, and address various types of threats. Categorizing threats helps determine what kind of measures should be taken against different types of attacks. For instance, known threats are typically identifiable through signatures or patterns, while unknown threats might be more complex or new, evading conventional detection methods. This classification aids cybersecurity experts in analyzing and combating threats more effectively.
Threat Classification
Known Threats
This category encompasses existing threats that can usually be matched with specific signatures or patterns.
Malware
Represents malicious software designed to harm computer users' devices or steal sensitive information. Viruses, worms, trojans, and ransomware are examples falling under this category.
Documented Exploits
Documented attacks are software, data, or command sequences attempting to infiltrate systems by exploiting existing security vulnerabilities. These threats exploit a specific weakness to perform unwanted actions.
Recycled Threats
This category includes automated scanning methods that assemble or modify pieces of existing exploit code to create new threats. These threats may often evade detection through static analysis.
Unknown Threats
Threats that cannot be identified using signature or pattern matching techniques fall into this category. These threats are often newly emerging or possess complex structures.
Zero-day Exploit
Used for exploits leveraging security vulnerabilities that are as yet unknown, often found in software or hardware. These vulnerabilities are typically unresolved and can quickly lead to significant issues.
Obfuscated Malware Code
Malicious code where the author attempts to obscure the code to hinder analysis. Techniques such as compression, encryption, or encoding are used to complicate analysis.
Behavior-based Detection
This type of threat detection method evaluates an object based on its intended actions before it actually performs them. It identifies distinct malicious behaviors of a particular software or file.
This classification covers a broad spectrum of recognized threat types in the cybersecurity domain, requiring different security measures and techniques to combat such threats.
Example,
Malware: As an example, the WannaCry ransomware attack infected numerous computers worldwide in 2017, encrypting users' files and demanding a ransom.
Documented Exploits: The Heartbleed vulnerability stemmed from a flaw in the OpenSSL library, allowing attackers to access sensitive information on target systems.
Recycled Threats: An anonymous group repurposed an old exploit code to create the new threat, Petya ransomware.
Unknown Threats: Stuxnet was one of the first complex threats targeting computer systems and often went unrecognized by signature-based detection methods, causing significant damage to computer systems.
Zero-day Exploit: CVE-2021-40444 was a zero-day vulnerability in Microsoft Word that allowed attackers to plant malicious software on targeted users' systems.
Obfuscated Malware Code: FinFisher is an example of spyware that employs encryption and compression techniques to obfuscate its malicious code, making analysis challenging.
Behavior-based Detection: An email attachment was scanned and flagged for exhibiting anomalous behaviors that could potentially harm system resources.
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