OPSWAT MetaDefender Sandbox is an AI-driven malware analysis platform that combines static analysis, threat intelligence, and emulation to detect sophisticated and evasive malware. The solution provides multi-layered threat detection capabilities designed to identify zero-day attacks and advanced threats that employ obfuscation, geofencing, and sandbox evasion techniques. The platform uses a three-stage analysis approach: reputation checks against known bad hashes and whitelists (milliseconds), deep static analysis that bypasses common obfuscation techniques (seconds), and dynamic fast-pass analysis using emulation within a lightweight virtualization layer (10 seconds average). This adaptive threat analysis methodology enables rapid scanning of thousands of files simultaneously with low resource requirements. MetaDefender Sandbox provides detailed threat reports with actionable indicators of compromise (IOCs), malware configuration extraction, and built-in threat hunting capabilities with similarity search functionality. The platform can detect various attack vectors including phishing, synthetic fabricated samples, geofencing malware, packed executables, obfuscated VBA macros, .NET reflection, shellcode, supply chain attacks, and ClickFix campaigns. The solution includes offline URL reputation analysis using machine learning models trained on hundreds of thousands of labeled URLs, making it suitable for air-gapped environments. Brand detection capabilities identify nearly 300 brands in phishing attempts. The platform offers flexible deployment options including cloud-native, on-premises, or hybrid environments.