Analyzing Malware Sandbox Evasion Techniques

Overview

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.

Prerequisites

• Cuckoo Sandbox 2.0+ or AnyRun account for behavioral analysis reports
• Python 3.8+ with json library for report parsing
• Behavioral report exports in JSON format

Steps

1. Parse Cuckoo/AnyRun behavioral report JSON files
2. Extract API call sequences for timing-related functions
3. Identify VM artifact detection via registry queries and WMI calls
4. Detect sleep inflation by comparing requested vs actual sleep durations
5. Flag user interaction checks (GetCursorPos, GetAsyncKeyState patterns)
6. Score evasion sophistication based on technique count and diversity
7. Map detected techniques to MITRE ATT&CK T1497 sub-techniques

Expected Output

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).