Malware Detection: Techniques and Technologies

Malware Detection Techniques

Companies can use various techniques to detect and analyze malware in their systems. Some of the most common include:

• Signature Detection: Signature detection uses unique features of a malware variant to identify it, such as the file hash, the domains and IP addresses that it contacts, or strings within the executable. While signature detection has a low false-positive rate, it is unable to identify zero-day threats and new malware variants.
• Anomaly Detection: Anomaly detection applies AI to cybersecurity by developing a model of normal operation and looking for deviations from that model. Anomaly detection can identify novel threats, but it often has a high false positive rate.
• Behavioral Detection: Malware commonly engages in unusual behavior, such as opening and encrypting large numbers of files. Behavioral detection looks for these unusual activities to identify the presence of malware on a system.
• Static Analysis: Static analysis involves analyzing a suspicious or malicious executable without running it. This is a safe way to analyze malware and can provide insights into how the malware works and indicators of compromise (IoCs) that can be used for signature detection.
• Dynamic Analysis: Dynamic analysis tools run the malware and observe its behavior. This method is often faster than static analysis but must be performed in a secure environment to avoid infecting the analyst’s computer.
• Hybrid Analysis: Hybrid analysis combines static and dynamic malware analysis techniques. This provides a more comprehensive picture of the malware’s activities while reducing the overall time it takes to analyze it.
• Blocklisting: A blocklist specifies certain things that are not allowed on a system or in a network. Blocklists are commonly used to block certain file extensions or known malware from being installed on a computer.
• Allowlisting: An allowlist specifies the things that are permitted on a system, and everything not on the allowlist is blocked. An allowlist might be used for malware detection to specify permitted files on a system, and all other programs are assumed to be malicious.
• Honeypots: Honeypots are systems that are designed to look like enticing targets to an attacker or a piece of malware. If they are infected by the malware, security professionals can study it and design defenses against it for their real systems.

Malware Protection with Check Point

Malware detection is useful, but a detection-focused approach to managing the malware threat places the organization at risk. By the time an analyst sees an alert from an IDS and performs the necessary analysis, an attacker has already gained access to the target system and has a window to perform malicious actions on it.

A better approach to managing malware is to take a prevention-focused approach. IPSs, endpoint protection platforms (EPPs), and similar tools have the ability to identify and block malware before it reaches an organization’s systems, eliminating the threat that it poses to the business.

Check Point’s Harmony suite of solutions specializes in malware prevention and protection rather than malware detection. To learn more about how a prevention-focused strategy for endpoint security can help protect your organization, sign up for a free demo of Harmony Endpoint today.