mukul975/analyzing-malware-sandbox-evasion-techniques
skills/analyzing-malware-sandbox-evasion-techniques/SKILL.md
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.
$ install --global
skillsauthnpx skillsauth add mukul975/anthropic-cybersecurity-skills analyzing-malware-sandbox-evasion-techniquesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Aug 6, 2026, 2:37 AM95.9s3 files scanned
SKILL.md
- name:
- analyzing-malware-sandbox-evasion-techniques
- description:
- Detect sandbox and VM evasion techniques in malware samples by analyzing
- domain:
- cybersecurity
- subdomain:
- malware-analysis
- version:
- 1.0
- author:
- mahipal
- license:
- Apache-2.0
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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