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Analyzing Malware Sandbox Evasion Techniques

  • 286 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

Study how malware detects sandboxes and evades automated analysis so you can improve detection rules and IR playbooks.

About

Analyzing Malware Sandbox Evasion Techniques is an agent skill aimed at security-conscious solo builders and small teams who encounter suspicious executables, cracked dependencies, or post-incident samples and need a structured lens on how malware avoids automated sandboxes. Public SKILL.md body in the indexed package is thin relative to the license block, so tagging emphasizes the declared name and cybersecurity domain: understanding evasion patterns helps you interpret sandbox misses, tune dynamic analysis environments, and write clearer severity notes when an agent or CLI tool flags odd behavior. This is not a drop-in virus scanner; it guides analytical thinking during Ship-phase security reviews. Pair it with formal sandbox products and your own isolation policies. Advanced complexity reflects VM/sandbox literacy and safe handling expectations.

  • Focuses on malware techniques that fingerprint sandboxes and analysis VMs
  • Supports security reviewers assessing untrusted binaries or supply-chain risk
  • Aligns with digital-forensics and incident-analysis workflows in the cybersecurity skills pack
  • Intended for structured technique review rather than casual scanning
  • Apache-2.0 licensed material suitable for embedding in agent-assisted IR notes

Analyzing Malware Sandbox Evasion Techniques by the numbers

  • 286 all-time installs (skills.sh)
  • +17 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #645 of 2,203 Security skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-malware-sandbox-evasion-techniques

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Listed on Skillselion
Installs286
repo stars27.3k
Security audit3 / 3 scanners passed
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills

What it does

Study how malware detects sandboxes and evades automated analysis so you can improve detection rules and IR playbooks.

Files

SKILL.mdMarkdownGitHub ↗

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

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).

Related skills

FAQ

Is Analyzing Malware Sandbox Evasion Techniques safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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