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malware-check — Static and dynamic analysis tool for detecting malicious code, suspicious binaries, and privacy violations | Kitploit
Tools/GitHubGitHub/momenbasel/malware-check
Static AnalysisDynamic Analysis (Sandboxing)Code AnalysisReverse EngineeringMalware AnalysisDevSecOpsMobile SecurityPrivacyBinary AnalysisSupply Chain Security
GitHubmomenbasel/malware-check
638224 months agoReviewed by Kitploit

malware-check

Static and dynamic analysis tool for detecting malicious code, suspicious binaries, and privacy violations

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malware-check

Install - Usage - Dynamic Analysis - YARA Rules - CI/CD

PyPI Python License CI

Docs: English | Tiếng Việt


Static and dynamic analysis tool for detecting malicious code, suspicious binaries, and privacy violations. Analyzes source code, compiled executables (.exe, .dll, .elf), macOS bundles (.app, .dmg, .pkg), mobile apps (.apk, .ipa), and application packages with YARA rules, Docker behavioral sandboxing, MobSF mobile analysis, payload deobfuscation, and multi-format reporting (JSON, HTML, SARIF).

Features

Static Analysis

  • Source Code Scanner - Detects reverse shells, backdoors, web shells, obfuscated payloads, crypto miners, ransomware patterns, keyloggers, credential theft, supply chain attacks, and persistence mechanisms across 15+ languages
  • Binary Analyzer - PE (Windows), Mach-O (macOS), and ELF (Linux) analysis with entropy detection, import table inspection, string extraction, code signing verification, and RWX section detection
  • AI File Type Detection - Optional Magika integration for content-based detection of extensionless or disguised files
  • YARA Engine - Signature-based scanning with bundled rules for malware families, packers, and suspicious patterns. Supports custom rule directories
  • Privacy Analyzer - Detects tracking SDKs, PII field handling, invasive permissions (Android/iOS manifests), device fingerprinting, clipboard monitoring, and unauthorized data transmission

Dynamic Analysis (Docker Sandbox)

  • Runs suspicious binaries in an isolated Docker container with:
    • syscall tracing via strace (network, file, process calls)
    • network monitoring via tcpdump (DNS queries, HTTP requests, C2 connections)
    • filesystem monitoring (file creation, modification, deletion)
    • process monitoring (child process spawning, injection attempts)
  • Full isolation: no network (default), memory limits, dropped capabilities, read-only rootfs
  • Behavioral findings: C2 port detection, mass file modification (ransomware), sensitive file access, anti-debugging

Reporting

  • Console - Rich terminal output with severity-colored tables and detailed findings
  • JSON - Machine-readable findings for automation pipelines
  • HTML - Professional dark-themed dashboard with severity bars, finding details, and evidence
  • SARIF 2.1.0 - Direct integration with GitHub Code Scanning, Azure DevOps, and GitLab SAST

Coverage

CategoryDetection Examples
Reverse ShellsPython socket+subprocess, bash /dev/tcp, netcat, PowerShell TCPClient, socat
BackdoorsWeb shells (PHP/JSP/ASP.NET), command injection (Python/JS/Java/Ruby/Go/C), bind shells, hidden routes, remote code loading, user creation, SSTI, unsafe deserialization
ObfuscationBase64+eval chains, char code construction, hex payloads, dynamic imports
Crypto MinersStratum pool connections, mining APIs, wallet addresses (BTC/ETH/XMR)
RansomwareFile encryption walks, ransom messages, encrypt+rename patterns
Credential TheftHardcoded secrets, clipboard theft, environment harvesting, browser credential files
Supply ChainSuspicious npm/pip install hooks, dependency confusion, custom registries
PersistenceCron/schtasks creation, registry Run keys, LaunchAgent/Daemon, SUID manipulation
Privilege EscalationSUID bit manipulation, setuid(0), chown root
Anti-AnalysisDebugger detection, VM detection, TLS callbacks, ptrace usage
KeyloggersGetAsyncKeyState, SetWindowsHookEx, pynput, CGEventTapCreate
PrivacyTracking SDKs (40+), PII fields (SSN, credit cards, biometrics, health), invasive permissions, device fingerprinting
Binary IndicatorsPacked binaries (UPX, high entropy), RWX sections, suspicious imports, unsigned/tampered code

Installation

Prerequisites

  • Python 3.10+
  • pip or pipx

Quick Install (pip)

pip install malware-check

Quick Install (pipx) - recommended for CLI usage

pipx install malware-check

From Source

git clone https://github.com/momenbasel/malware-check.git
cd malware-check
pip install -e ".[dev]"

This installs the core CLI. Binary analysis via pefile/lief, AI-powered file detection via magika, and YARA scanning via yara-python are optional extras.

Full Install (all analyzers)

# Core + binary analysis + AI file detection + YARA
pip install malware-check[full]

# Or install only what you need
pip install malware-check[binary]
pip install malware-check[detect]
pip install malware-check[yara]

# Or install extras manually
pip install pefile lief magika yara-python

AI File Type Detection (Magika)

pip install malware-check[detect]

When installed, malware-check uses Magika to improve cross-platform file identification, enrich file_type metadata, and route extensionless or disguised files to the correct analyzer based on content instead of filename alone.

Dynamic Analysis (Docker Sandbox)

# Requires Docker - https://docs.docker.com/get-docker/
# Build the sandbox image (one-time setup)
malware-check build-sandbox

Verify Installation

malware-check info

The info command will show whether Magika-powered file detection is available.

Claude Code (Skill)

Install as a Claude Code skill so Claude can analyze files for you:

# Install the skill from GitHub
npx skills install momenbasel/malware-check --skill malware-check

# Or manually: copy skill/SKILL.md to your skills directory
cp -r skill/ ~/.claude/skills/malware-check/

Then in Claude Code, say: "scan this file for malware" or "is this binary safe?" and Claude will use malware-check automatically.

You also need the CLI tool installed:

pip install malware-check pefile lief yara-python

Codex CLI

Install the tool and add to your Codex agent instructions:

# 1. Install the CLI
pip install malware-check pefile lief yara-python

# 2. Add to your Codex instructions (codex.md or system prompt)
echo 'Use `malware-check scan <path> --verbose` to analyze files for malware.' >> AGENTS.md

# 3. Or install as a Codex skill
cp -r skill/ .codex/skills/malware-check/

OpenAI Codex / Other AI Agents

For any AI coding agent that supports tool use or custom instructions:

# 1. Install
pip install malware-check

# 2. Add to agent instructions:
# "When asked to check code/binaries for malware, use: malware-check scan <target> --verbose"
# "For reports: malware-check scan <target> --format html -o report.html"
# "For CI/CD: malware-check scan <target> --format sarif -o report.sarif --exit-code"

Usage

Scan a file

malware-check scan suspicious_file.py

Scan an extensionless or renamed file

# Best results when malware-check[detect] is installed
malware-check scan suspicious_payload --verbose
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