Detect sandbox and VM evasion techniques in malware samples by analyzing timing checks, VM/hypervisor artifact queries, user-interaction checks, and sleep-inflation patterns from Cuckoo or AnyRun behavioral reports. Use when a sample shows no or minimal activity in a sandbox, when a behavioral report needs review for evasion indicators, or when building detections for anti-analysis techniques.
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Use analyzing-malware-sandbox-evasion-techniques to analyze [Cuckoo or AnyRun behavioral-report JSON files] and produce a JSON report of sandbox-evasion indicators, API evidence, sophistication score, categories, and MITRE ATT&CK mappings.
Required inputs
[Cuckoo or AnyRun behavioral-report JSON files]
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SKILL.md
name: analyzing-malware-sandbox-evasion-techniquesdescription: Detect sandbox and VM evasion techniques in malware samples by analyzing timing checks, VM/hypervisor artifact queries, user-interaction checks, and sleep-inflation patterns from Cuckoo or AnyRun behavioral reports. Use when a sample shows no or minimal activity in a sandbox, when a behavioral report needs review for evasion indicators, or when building detections for anti-analysis techniques.domain: cybersecuritysubdomain: malware-analysistags: - sandbox-evasion- malware-analysis- cuckoo- anyrun- mitre-attack- virtualization-detection- behavioral-analysisversion: '1.0'author: mahipallicense: Apache-2.0d3fend_techniques: - Platform Hardening- Restore Object- Process Analysis- System Call Filtering- Restore Softwarenist_csf: - DE.AE-02- RS.AN-03- ID.RA-01- DE.CM-01mitre_attack: - T1497.001- T1497.003- T1480- T1027.002
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.
When to Use
When investigating security incidents that require analyzing malware sandbox evasion techniques
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques
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
Parse Cuckoo/AnyRun behavioral report JSON files
Extract API call sequences for timing-related functions
Identify VM artifact detection via registry queries and WMI calls
Detect sleep inflation by comparing requested vs actual sleep durations
Flag user interaction checks (GetCursorPos, GetAsyncKeyState patterns)
Score evasion sophistication based on technique count and diversity
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).