prometheus-community 3.1.0

Enterprise-grade malware analysis engine - Windows/Linux/Android support with YARA generation and IOC export

🔥 Prometheus Community Edition v3.1.0

Enterprise-Grade Malware Analysis Engine

Professional malware analysis with 16 integrated components, ~95% academic coverage, and zero external dependencies. Analyze Windows PE, Linux ELF, and Android DEX files with forensic-grade accuracy.

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🎯 What's New in v3.1.0

Major Refactoring: Version-Agnostic Architecture

v3.1.0 introduces a complete architectural refactoring removing all version-numbered modules and classes for a stable, future-proof codebase.

Breaking Changes for API Users:

• PrometheusEngineV3 → PrometheusEngine
• models_v3.py → models.py
• engine_v3_0_0.py → engine.py
• behavioral_detector_v3.py → behavioral_detector.py

Benefits:

• ✅ No more import breakage with version updates
• ✅ Cleaner, more intuitive API
• ✅ Professional Python packaging standards
• ✅ Future-proof architecture

CLI users: No changes needed - commands work identically!

Previous: v3.0.0 - Revolutionary Upgrade

v2.0.0: 6-layer detection engine
v3.0.0: 16-component system with 5.3x coverage increase

Major Features

✅ Complete Platform Coverage

• Windows PE executable analysis
• Linux ELF binary analysis
• Android DEX/APK analysis

✅ Intelligence Automation

• Auto-generate YARA detection rules
• Export IOCs in JSON, CSV, STIX 2.1
• Professional HTML & Markdown reports

✅ Advanced Detection

• Steganography detection (EOF append, LSB, embedded files)
• Shellcode identification (NOP sleds, GetPC, syscalls)
• XOR/encoding analysis (256 keys + Base64/Hex)
• Packer detection (UPX, ASPack, Themida, 15+ signatures)
• Anti-analysis techniques (anti-debug, anti-VM, obfuscation)
• Cryptographic constants (AES, MD5, SHA, DES, RSA)
• Network artifact detection (C2 domains, suspicious ports)

✅ Enterprise Ready

• 100% offline capable
• No external dependencies (Python stdlib only)
• Commercial-use friendly licensing
• Air-gapped deployment ready
• Production-grade error handling

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📊 Key Statistics

Metric	v2.0.0	v3.1.0	Improvement
Coverage	~18%	~95%	5.3x increase
Components	6 layers	16 components	2.7x more
Code	~1,500 lines	9,223 lines	6.1x larger
Platforms	Windows	Win/Linux/Android	3 platforms
Detection Patterns	~100	400+	4x more
Export Formats	JSON	JSON/CSV/STIX/YARA/HTML/MD	6 formats

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🔍 16 Integrated Components

Block 1: Foundation (35% coverage)

1. File Type Validator - 31 format signatures, polyglot detection
2. Behavioral Detector - Context-aware pattern matching
3. Output Formatter - 3-tier forensic presentation

Block 2: Advanced Detection (+20% = 55% coverage)

4. Steganography Detector - EOF append, embedded files, LSB analysis
5. Shellcode Detector - NOP sleds, GetPC, syscall patterns
6. XOR/Encoding Detector - 256-key brute force, Base64, hex
7. Nested File Detector - 31 embedded signature scan

Block 3: Executable Deep Dive (+15% = 70% coverage)

8. PE Analyzer - Windows executables, 15 packer signatures
9. Anti-Analysis Detector - Anti-debug, anti-VM, obfuscation
10. Cryptographic Detector - AES, MD5, SHA, DES, RSA constants

Block 4: Cross-Platform & Network (+15% = 85% coverage)

11. ELF Analyzer - Linux binaries, dynamic linking, interpreters
12. String Analyzer - URLs, IPs, paths, commands, registry keys
13. Network Artifact Detector - C2 domains, suspicious ports, DGA

Block 5: Intelligence Automation (+10% = 95% coverage)

14. YARA Rule Generator - Auto-generate detection rules
15. IOC Exporter - JSON, CSV, STIX 2.1 export
16. Android Analyzer - DEX files, dynamic loading, obfuscation
17. Report Generator - Professional HTML & Markdown reports

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📦 Installation

Via pip (Recommended)

pip install prometheus-community

From Source

git clone https://github.com/0x44616D69616E/prometheus-community
cd prometheus-community
pip install -e .

Verify Installation

prometheus version
# Output: Prometheus Community Edition v3.1.0

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🚀 Quick Start

Basic Analysis

prometheus analyze malware.exe

Export IOCs to All Formats

prometheus analyze malware.exe --export-iocs results
# Creates: results.json, results.csv, results.stix

Generate YARA Rules

prometheus analyze malware.exe --generate-yara malware.yar

Generate HTML Report

prometheus analyze malware.exe --report report.html

Analyze Android APK

prometheus analyze app.apk --android

Complete Workflow

prometheus analyze malware.exe \
  --export-iocs indicators \
  --generate-yara detection.yar \
  --report analysis.html \
  --output results.json

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⚠️ Migration from v3.0.x

CLI Users: No changes needed! All commands work identically.

API Users: Update your imports:

# Before (v3.0.x)
from prometheus import PrometheusEngineV3
from prometheus.models_v3 import Severity

# After (v3.1.0+)
from prometheus import PrometheusEngine
from prometheus.models import Severity

See REFACTORING_v3_1_0.md for complete migration guide.

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📖 CLI Reference

Command: prometheus analyze

prometheus analyze [OPTIONS] FILE

Core Options

Option	Type	Description	Default
FILE	Path	File to analyze (required)	-
--output, -o	Path	Save JSON results	None
--quiet, -q	Flag	Suppress console output	False
--intel	Path	Custom intelligence database	Built-in

Export Options

Option	Type	Description
--export-iocs	Path	Export IOCs (JSON/CSV/STIX)
--generate-yara	Path	Generate YARA rule file
--report	Path	Generate HTML report
--report-md	Path	Generate Markdown report

Platform Options

Option	Type	Description
--android	Flag	Analyze Android APK/DEX
--pe	Flag	Force PE analysis
--elf	Flag	Force ELF analysis

Detection Options

Option	Type	Description	Default
--enable-stego	Flag	Enable steganography detection	True
--enable-shellcode	Flag	Enable shellcode detection	True
--enable-crypto	Flag	Enable crypto detection	True
--enable-network	Flag	Enable network detection	True

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💡 Usage Examples

Windows Malware Analysis

# Full analysis with all exports
prometheus analyze ransomware.exe \
  --export-iocs iocs/ransomware \
  --generate-yara rules/ransomware.yar \
  --report reports/ransomware.html \
  --output json/ransomware.json

# Results:
# - iocs/ransomware.json (structured IOCs)
# - iocs/ransomware.csv (spreadsheet format)
# - iocs/ransomware.stix (threat intel platform)
# - rules/ransomware.yar (YARA detection rule)
# - reports/ransomware.html (analyst report)
# - json/ransomware.json (complete analysis)

Linux Binary Analysis

# Analyze suspicious Linux binary
prometheus analyze suspicious_binary --elf --report analysis.html

# Detection includes:
# - ELF structure parsing
# - RWX segment detection
# - UPX packer identification
# - Suspicious interpreter paths
# - String extraction (URLs, IPs, commands)

Android APK Analysis

# Analyze Android application
prometheus analyze app.apk --android --export-iocs app_iocs

# Detection includes:
# - DEX file analysis
# - Dynamic code loading (DexClassLoader)
# - Reflection usage
# - Obfuscation detection (ProGuard/R8)
# - Suspicious permissions

Quick Triage

# Fast check with IOC export
prometheus analyze unknown.exe --quiet --export-iocs quick_check

# Review:
# - quick_check.json (automated analysis)
# - quick_check.csv (spreadsheet import)
# - quick_check.stix (SIEM integration)

Batch Analysis with Automation

# Analyze directory of samples
for file in samples/*.exe; do
  name=$(basename "$file" .exe)
  prometheus analyze "$file" \
    --quiet \
    --export-iocs "iocs/$name" \
    --generate-yara "rules/$name.yar" \
    --output "results/$name.json"
done

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🎯 Real-World Scenarios

SOC Analyst Workflow

# 1. Quick analysis
prometheus analyze alert_binary.exe

# 2. If suspicious, export IOCs for blocking
prometheus analyze alert_binary.exe --export-iocs blocking/alert

# 3. Generate detection rule
prometheus analyze alert_binary.exe --generate-yara detection.yar

# 4. Create report for team
prometheus analyze alert_binary.exe --report incident_report.html

Malware Researcher Workflow

# 1. Comprehensive analysis
prometheus analyze sample.exe --output analysis.json

# 2. Generate YARA rule for detection
prometheus analyze sample.exe --generate-yara family_detection.yar

# 3. Extract IOCs for threat intel
prometheus analyze sample.exe --export-iocs threat_intel

# 4. Create detailed report
prometheus analyze sample.exe --report research_notes.html

Automated Pipeline

#!/bin/bash
# Automated malware processing pipeline

SAMPLE=$1
NAME=$(basename "$SAMPLE")

# Analysis
prometheus analyze "$SAMPLE" \
  --quiet \
  --output "analysis/${NAME}.json" \
  --export-iocs "iocs/${NAME}" \
  --generate-yara "rules/${NAME}.yar" \
  --report "reports/${NAME}.html"

# Upload to threat intel platform
curl -X POST https://intel.company.com/api/stix \
  -H "Content-Type: application/json" \
  -d @"iocs/${NAME}.stix"

# Deploy YARA rule to endpoints
cp "rules/${NAME}.yar" /var/lib/yara/rules/

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📊 Example Output

Console Output (Enhanced in v3.0)

╔══════════════════════════════════════════════════════════╗
║   🔥 PROMETHEUS COMMUNITY EDITION v3.1.0                ║
║   Enterprise-Grade Malware Analysis                     ║
╚══════════════════════════════════════════════════════════╝

Analyzing: malware.exe
SHA256: a1b2c3d4...
Size: 524,288 bytes
Type: PE (Windows executable)

═══════════════════════════════════════════════════════════

📋 STATIC ANALYSIS

Entropy: 7.84 ⚠️  HIGH - Likely packed or encrypted
File Type: PE
Detected Type: PE
Match: ✓ Valid

═══════════════════════════════════════════════════════════

🔍 DETECTION RESULTS

[HIGH] PE Packer Detected
Packer: UPX
📊 Severity: HIGH | Confidence: 95%
📍 Location: Section .UPX0 at offset 0x1000
Context: Binary packed with UPX - common evasion technique
MITRE: T1027.002 - Software Packing

[HIGH] Anti-Debug API
API: IsDebuggerPresent
📊 Severity: HIGH | Confidence: 90%
📍 Location: Import table
Context: Checks for debugger presence to evade analysis
MITRE: T1622 - Debugger Evasion

[MEDIUM] Suspicious Network Indicator
URL: http://malicious-c2.tk/gate.php
📊 Severity: MEDIUM | Confidence: 95%
📍 Location: String at offset 0x3f20
Context: Suspicious domain with free TLD (.tk)
MITRE: T1071 - Application Layer Protocol

═══════════════════════════════════════════════════════════

📈 ANALYSIS SUMMARY

Total Findings: 12
 - Exact Matches: 0
 - Suspicious: 8 (HIGH: 3, MEDIUM: 5)
 - Informational: 4

IOCs Extracted: 5
 - URLs: 2
 - IP Addresses: 1
 - Domains: 2

TTPs Identified: 7
 - T1027.002 (Software Packing)
 - T1622 (Debugger Evasion)
 - T1071 (Application Layer Protocol)
 - T1059 (Command Execution)
 - T1055 (Process Injection)

Analysis Duration: 0.15 seconds

═══════════════════════════════════════════════════════════

✅ Analysis complete! Use --help for export options.

---

🛠️ Python API

Basic Usage

from prometheus import PrometheusEngine

# Initialize engine
engine = PrometheusEngine()

# Analyze file
result = engine.analyze_file("malware.exe")

# Access findings
print(f"Suspicious artifacts: {len(result.suspicious_artifacts)}")
print(f"IOCs extracted: {len(result.iocs)}")
print(f"TTPs identified: {result.ttps}")

Generate YARA Rules

from prometheus import PrometheusEngine
from prometheus.yara_generator import YARARuleGenerator

engine = PrometheusEngine()
result = engine.analyze_file("malware.exe")

# Generate YARA rule
generator = YARARuleGenerator()
yara_rule = generator.generate_ruleset(result, "malware_family")

# Save to file
with open("detection.yar", "w") as f:
    f.write(yara_rule)

Export IOCs

from prometheus import PrometheusEngine
from prometheus.ioc_exporter import IOCExporter

engine = PrometheusEngine()
result = engine.analyze_file("malware.exe")

# Export to all formats
exporter = IOCExporter()
exporter.save_exports(result, output_dir="iocs", base_name="malware")

# Creates:
# - iocs/malware.json
# - iocs/malware.csv
# - iocs/malware.stix

Generate Reports

from prometheus import PrometheusEngine
from prometheus.report_generator import ReportGenerator

engine = PrometheusEngine()
result = engine.analyze_file("malware.exe")

# Generate HTML report
generator = ReportGenerator()
html = generator.generate_html(result)

with open("report.html", "w") as f:
    f.write(html)

# Generate Markdown report
md = generator.generate_markdown(result)

with open("report.md", "w") as f:
    f.write(md)

---

🔬 Detection Capabilities

Windows PE Analysis

• ✅ PE structure parsing (DOS, NT, COFF, Optional headers)
• ✅ Section analysis (.text, .data, .rdata, .rsrc, etc.)
• ✅ Import/Export table analysis
• ✅ RWX section detection
• ✅ Packer identification (UPX, ASPack, Themida, 15+ signatures)
• ✅ Entry point anomalies
• ✅ Dangerous API detection (30+ APIs across 6 categories)
• ✅ Anti-debug techniques
• ✅ Anti-VM techniques

Linux ELF Analysis

• ✅ ELF header parsing (64/32-bit, endianness)
• ✅ Section analysis (.text, .data, .bss, .rodata, etc.)
• ✅ Program header analysis (LOAD, DYNAMIC, INTERP, etc.)
• ✅ RWX segment detection
• ✅ Interpreter analysis
• ✅ Dynamic linking analysis
• ✅ UPX packer detection
• ✅ Stripped binary detection

Android APK/DEX Analysis

• ✅ DEX file structure parsing
• ✅ Dynamic code loading detection (DexClassLoader)
• ✅ Reflection pattern analysis
• ✅ Obfuscation detection (ProGuard/R8)
• ✅ Suspicious class/method detection
• ✅ Asset/cache directory references

Cross-Platform Detection

• ✅ Steganography (EOF append, embedded files, LSB)
• ✅ Shellcode (NOP sleds, GetPC, syscalls)
• ✅ XOR/encoding (256 keys, Base64, hex)
• ✅ Nested files (31 signatures)
• ✅ Cryptography (AES, MD5, SHA, DES, RSA)
• ✅ String analysis (URLs, IPs, commands, paths)
• ✅ Network artifacts (C2 domains, ports, DGA)

---

📁 Project Structure

prometheus-community/
├── prometheus/
│   ├── __init__.py
│   ├── engine.py              # Main analysis engine
│   ├── models.py                  # Data models
│   ├── config.py                     # Configuration
│   ├── cli.py                        # CLI interface
│   │
│   ├── core/                         # Core components
│   │   ├── file_type_validator.py
│   │   ├── behavioral_detector.py
│   │   └── output_formatter.py
│   │
│   ├── detection/                    # Detection modules
│   │   ├── steganography_detector.py
│   │   ├── shellcode_detector.py
│   │   ├── xor_encoding_detector.py
│   │   ├── nested_file_detector.py
│   │   ├── pe_analyzer.py
│   │   ├── elf_analyzer.py
│   │   ├── anti_analysis_detector.py
│   │   ├── crypto_detector.py
│   │   ├── string_analyzer.py
│   │   └── network_detector.py
│   │
│   ├── automation/                   # Intelligence automation
│   │   ├── yara_generator.py
│   │   ├── ioc_exporter.py
│   │   ├── android_analyzer.py
│   │   └── report_generator.py
│   │
│   └── data/
│       └── intelligence.json
│
├── tests/
│   ├── test_complete_system.py
│   ├── validate_block1.py
│   ├── validate_block2.py
│   ├── validate_block3.py
│   ├── validate_block4.py
│   └── validate_block5.py
│
├── docs/
│   ├── BLOCK_1_IMPLEMENTATION.md
│   ├── BLOCK_2_IMPLEMENTATION.md
│   ├── BLOCK_3_IMPLEMENTATION.md
│   ├── BLOCK_4_IMPLEMENTATION.md
│   ├── BLOCK_5_IMPLEMENTATION.md
│   └── COMPREHENSIVE_TEST_REPORT.md
│
├── README.md
├── setup.py
├── CHANGELOG.md
├── LICENSE
└── requirements.txt (empty - no dependencies!)

---

🆚 Comparison

Feature	Prometheus v3.0	VirusTotal	YARA	Cuckoo
Offline Analysis	✅ Yes	❌ No	✅ Yes	✅ Yes
Windows PE	✅ Advanced	✅ Yes	⚠️ Basic	✅ Yes
Linux ELF	✅ Advanced	⚠️ Limited	⚠️ Basic	⚠️ Limited
Android APK	✅ Advanced	✅ Yes	⚠️ Basic	✅ Yes
YARA Generation	✅ Auto	❌ No	N/A	❌ No
IOC Export	✅ 3 formats	⚠️ Limited	❌ No	⚠️ Limited
Report Generation	✅ HTML/MD	❌ No	❌ No	✅ HTML
No Dependencies	✅ Yes	N/A	❌ No	❌ No
Open Source	✅ Yes	❌ No	✅ Yes	✅ Yes
Commercial Use	✅ Yes	💰 Paid	✅ Yes	✅ Yes

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📚 Documentation

• Installation Guide
• User Manual
• API Reference
• Block Implementation Guides
• Test Report

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🤝 Contributing

We welcome contributions! See CONTRIBUTING.md.

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📄 License

Prometheus Community Edition is released under the Prometheus Community License v1.0.

Key terms:

• ✅ Free for research, education, and non-profit use
• ✅ Source available - Review and modify code
• ✅ Commercial use allowed with attribution
• ✅ No external dependencies - Deploy anywhere

For enterprise licensing, contact: [e-mail]

See LICENSE for full terms.

---

🎓 Citation

@software{prometheus2026,
  author = {Donahue, Damian},
  title = {Prometheus Community Edition: Enterprise Malware Analysis},
  year = {2026},
  publisher = {GitHub},
  version = {3.1.0},
  url = {https://github.com/0x44616D69616E/prometheus-community},
  doi = {10.5281/zenodo.18123287}
}

---

🌟 What's Coming

v3.1.0 (Planned)

• Machine learning-based classification
• Behavioral pattern correlation
• Multi-file campaign analysis
• Interactive web interface

v3.2.0 (Planned)

• Real-time monitoring integration
• Cloud sandbox integration
• Threat intelligence feeds
• Automated playbooks

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💬 Community

• GitHub Issues - Bug reports and features
• Discussions - Questions and community
• Email - [e-mail]
• Documentation - Complete guides

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🙏 Acknowledgments

Built on foundational research:

• Binary Analysis Academic Reference v2.2
• MITRE ATT&CK Framework
• Open source security community

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🔥 Why Prometheus v3.0?

From transparency to enterprise capability

• v1.0: Basic detection with 6 layers
• v2.0: Explainable detection with location tracking
• v3.0: Enterprise-grade analysis with full automation

Complete solution:

• ✅ Analyze any platform (Windows/Linux/Android)
• ✅ Generate detection rules (YARA)
• ✅ Export indicators (JSON/CSV/STIX)
• ✅ Create reports (HTML/Markdown)
• ✅ Deploy anywhere (no dependencies)

Built for:

• 🏢 Enterprise SOC teams
• 🔬 Malware researchers
• 🎓 Security educators
• 🛡️ Incident responders

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Made with 🔥 by the security research community

Prometheus Community Edition v3.1.0 - Enterprise malware analysis for everyone