- Add validated mitre_attack frontmatter to all 754 skills (286 distinct
techniques), verified against MITRE ATT&CK v19.1 via the official
mitreattack-python library: 0 revoked, deprecated, or invalid IDs
- Curate precise per-skill technique IDs for forensics, malware-analysis,
threat-intel, and red-team skills (e.g. DCSync -> T1003.006,
Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003)
- Reconcile v19.1 tactic restructuring: Defense Evasion split into
Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.*
family and T1070.001/.002 remapped to active equivalents (T1685.*)
- Normalize word-split tags across 35 skills (remove filename-derived
stopword tags, add semantic cybersecurity tags)
- Add api-reference.md for 3 skills that were missing it
- Update README ATT&CK section with accurate v19.1 tactic distribution
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
cybersecurity
malware-analysis
sandbox-evasion
malware-analysis
cuckoo
anyrun
mitre-attack
virtualization-detection
behavioral-analysis
1.0
mahipal
Apache-2.0
Platform Hardening
Restore Object
Process Analysis
System Call Filtering
Restore Software
DE.AE-02
RS.AN-03
ID.RA-01
DE.CM-01
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).
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