2025 Volume 11 Issue 1

ABSTRACT: The continuous evolution of malware represents a major challenge for modern cybersecurity. Attackers increasingly rely on obfuscation, encryption, and anti-analysis techniques to evade detection, rendering traditional signature-based defenses insufficient. In this context, malware analysis has become essential to understand threats, extract indicators of compromise, and support incident response. This manuscript provides a structured review of the main malware analysis techniques, organized into four complementary levels: triage, static analysis, dynamic analysis, and advanced reverse engineering. Each method is discussed in terms of methodology, tools, advantages, and limitations. The review highlights that static analysis provides rapid and safe insights but is ineffective against sophisticated obfuscation and packing methods. Dynamic analysis captures runtime behaviors and network communications, though it remains vulnerable to evasion strategies. Memory and network forensics enhance visibility by revealing hidden processes, fileless malware, and anomalous connections. Reverse engineering offers the most comprehensive understanding of malicious logic, yet it is highly time-consuming and requires specialized expertise. Overall, the findings confirm that no single method is sufficient; instead, hybrid approaches that integrate static, dynamic, and forensic techniques are required. The study also emphasizes the role of standardized frameworks and large-scale datasets in improving reproducibility and enabling automation in malware detection and analysis.