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Analyzing Malware Sandbox Evasion Techniques

CommunityPopular
mukul975
analyzing-malware-sandbox-evasion-techniques

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.

Overview

Publishermukul975
RepositoryAnthropic-Cybersecurity-Skills
Skill nameanalyzing-malware-sandbox-evasion-techniques
Stars
32.9K
Forks
4K
Bundled files
2
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mukul975 on GitHub. Read the source before you install it.

Installation

Install the Analyzing Malware Sandbox Evasion Techniques AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills
mkdir -p .claude/skills
cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/analyzing-malware-sandbox-evasion-techniques .claude/skills/analyzing-malware-sandbox-evasion-techniques
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyzing Malware Sandbox Evasion Techniques in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyzing Malware Sandbox Evasion Techniques on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyzing Malware Sandbox Evasion Techniques is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyzing Malware Sandbox Evasion Techniques AI skill do?

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.

Why use Analyzing Malware Sandbox Evasion Techniques on TypingMind?

Because you install it once and use it with any model. Analyzing Malware Sandbox Evasion Techniques is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyzing Malware Sandbox Evasion Techniques in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-malware-sandbox-evasion-techniques. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyzing Malware Sandbox Evasion Techniques?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyzing Malware Sandbox Evasion Techniques?

As many as you like. As long as a model supports skills, you can use Analyzing Malware Sandbox Evasion Techniques with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyzing Malware Sandbox Evasion Techniques AI skill free?

Yes. It is published on GitHub by mukul975 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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