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Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports
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Based on SOC occupation classification
| name | analyzing-malware-sandbox-evasion-techniques |
| description | Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports |
| domain | cybersecurity |
| subdomain | malware-analysis |
| tags | ["sandbox-evasion","malware-analysis","cuckoo","anyrun","mitre-attack","virtualization-detection","behavioral-analysis"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
| d3fend_techniques | ["Platform Hardening","Restore Object","Process Analysis","System Call Filtering","Restore Software"] |
| nist_csf | ["DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01"] |
Sandbox evasion (MITRE ATT&CK T1497) allows malware to detect analysis environments and alter behavior to avoid detection. This skill analyzes behavioral reports from Cuckoo Sandbox and AnyRun for evasion indicators including timing-based checks (GetTickCount, QueryPerformanceCounter, sleep inflation), VM artifact detection (registry keys, MAC address prefixes, process names like vmtoolsd.exe), user interaction checks (mouse movement, keyboard input), and environment fingerprinting (disk size, CPU count, RAM). Detection rules flag samples exhibiting these behaviors for deeper manual analysis.
JSON report listing detected evasion techniques with MITRE ATT&CK mapping, API call evidence, evasion sophistication score, and classification of evasion categories (timing, VM detection, user interaction, environment fingerprinting).
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