ReversibleAI - Advanced Static & Dynamic Analysis Framework for Malware Analysis and Reverse Engineering

A modern, modular Python framework for binary analysis that bridges the gap between traditional reverse engineering tools and contemporary analysis techniques.

⚠️ Development Status: This project is currently in Alpha stage. Some features may be incomplete or experimental. We recommend installing from source for the latest updates.

• Python 3.11 or higher
• pip and setuptools

Since ReversibleAI is currently in active development, installation from source is recommended:

# Clone the repository
git clone https://github.com/hexria/ReversibleAI.git
cd ReversibleAI

# Install in development mode
pip install -e .

# Or install with all optional dependencies
pip install -e ".[dev]"

For specific features, you can install optional dependencies:

# For IDA Pro integration
pip install -e ".[ida]"

# For Ghidra integration
pip install -e ".[ghidra]"

# For Radare2 integration
pip install -e ".[radare2]"

# For development tools
pip install -e ".[dev]"

Analyze a binary file:

reversibleai analyze malware.exe --output report.html

Extract strings:

reversibleai strings malware.exe --min-length 8 --suspicious

Get binary information:

reversibleai info malware.exe

Scan with hash patterns:

reversibleai hash-scan malware.exe --signatures signatures.db

Interactive mode:

reversibleai interactive

Basic Analysis:

from reversibleai.core.static_analyzer.analyzer import StaticAnalyzer
from pathlib import Path

# Initialize analyzer
analyzer = StaticAnalyzer(Path("malware.exe"))

# Perform analysis
result = analyzer.analyze()

print(f"Found {len(result.functions)} functions")
print(f"Found {len(result.strings)} strings")
print(f"Found {len(result.imports)} imports")

String Extraction:

from reversibleai.core.string_extractor.extractor import StringExtractor
from pathlib import Path

extractor = StringExtractor(Path("malware.exe"))
strings = extractor.extract_strings(min_length=8)

for string_info in strings:
    print(f"{string_info.value} @ {hex(string_info.address)}")

Generate Report:

from reversibleai.core.static_analyzer.analyzer import StaticAnalyzer
from reversibleai.core.reports.generator import ReportGenerator
from pathlib import Path

analyzer = StaticAnalyzer(Path("malware.exe"))
result = analyzer.analyze()

report_gen = ReportGenerator()
report_gen.generate_analysis_report(
    analysis_result=result.__dict__,
    output_path=Path("report.html"),
    format="html"
)

Binary Information:

from reversibleai.core.loader.factory import LoaderFactory
from pathlib import Path

loader = LoaderFactory.create_loader(Path("malware.exe"))
binary_info = loader.info

print(f"File type: {binary_info.file_type.value}")
print(f"Architecture: {binary_info.architecture} {binary_info.bits}-bit")
print(f"Entry point: {hex(binary_info.entry_point)}")
print(f"SHA256: {binary_info.sha256}")

• Multi-format Support: PE, ELF, Mach-O binary loading and parsing
• Static Analysis:
  • Function detection and analysis
  • Control flow graph (CFG) construction
  • Data flow analysis
  • String extraction with multiple encodings (ASCII, UTF-8, UTF-16)
  • Disassembly with Capstone engine
• String Analysis:
  • Entropy calculation
  • Suspicious string detection
  • URL, IP address, registry key, and file path extraction
• Hash Pattern Matching: File, function, string, and import hash matching
• Report Generation: HTML, JSON, XML formats (PDF support is experimental)
• Runtime Emulation: Basic emulation support with Unicorn engine (experimental)

• Plugin architecture for extending functionality
• Integration support for IDA Pro, Ghidra, and Radare2 (requires optional dependencies)

• x86, x86_64
• ARM, ARM64
• MIPS, MIPS64
• PowerPC, PowerPC64
• RISC-V, RISC-V64
• SPARC, SPARC64

• Python 3.11 or higher
• Core dependencies (automatically installed):
  • LIEF (binary parsing)
  • Capstone (disassembly)
  • NetworkX (graph analysis)
  • Rich (terminal UI)
  • Loguru (logging)
  • And more (see requirements.txt)

• PDF Report Generation: Currently experimental/placeholder implementation
• YARA Integration: Hash-based pattern matching is implemented, full YARA integration is planned
• Dynamic Analysis: Emulation features are in early development
• Plugin Integrations: IDA, Ghidra, and Radare2 plugins require the respective tools to be installed

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

MIT License - see LICENSE file for details

• Issues: GitHub Issues
• Email: pentestdatabase@gmail.com

This project is in Alpha stage (v0.1.0). The core functionality is implemented and tested, but some advanced features may be incomplete or experimental. We're actively working on improving stability and adding new features.

For the latest updates and bug fixes, please install from source and check the CHANGELOG.md.