Ransomware has become a major cybersecurity threat, and traditional signature-based detection methods are often ineffective against modern variants using advanced evasion techniques.This study proposes a behavior-based detection framework using entropy analysis, string pattern matching, file header inspection, MITRE ATT&CK mapping, and IOC detection within a sandbox environment to accurately identify ransomware threats.