Enterprise-grade malware analysis engine - Windows/Linux/Android support with YARA generation and IOC export
Project description
๐ฅ Prometheus Community Edition v3.0.0
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.
๐ฏ What's New in v3.0.0
Revolutionary Upgrade: 6 Layers โ 16 Components
v2.0.0: 6-layer detection engine with explainable findings
v3.0.0: 16-component analysis system with 5.3x coverage increase
Major Features
โ Complete Platform Coverage
- Windows PE executable analysis
- Linux ELF binary analysis
- Android DEX/APK analysis
โ Intelligence Automation
- Auto-generate YARA detection rules
- Export IOCs in JSON, CSV, STIX 2.1
- Professional HTML & Markdown reports
โ 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)
โ Enterprise Ready
- 100% offline capable
- No external dependencies (Python stdlib only)
- Commercial-use friendly licensing
- Air-gapped deployment ready
- Production-grade error handling
๐ Key Statistics
| Metric | v2.0.0 | v3.0.0 | 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 |
๐ 16 Integrated Components
Block 1: Foundation (35% coverage)
- File Type Validator - 31 format signatures, polyglot detection
- Behavioral Detector - Context-aware pattern matching
- Output Formatter - 3-tier forensic presentation
Block 2: Advanced Detection (+20% = 55% coverage)
- Steganography Detector - EOF append, embedded files, LSB analysis
- Shellcode Detector - NOP sleds, GetPC, syscall patterns
- XOR/Encoding Detector - 256-key brute force, Base64, hex
- Nested File Detector - 31 embedded signature scan
Block 3: Executable Deep Dive (+15% = 70% coverage)
- PE Analyzer - Windows executables, 15 packer signatures
- Anti-Analysis Detector - Anti-debug, anti-VM, obfuscation
- Cryptographic Detector - AES, MD5, SHA, DES, RSA constants
Block 4: Cross-Platform & Network (+15% = 85% coverage)
- ELF Analyzer - Linux binaries, dynamic linking, interpreters
- String Analyzer - URLs, IPs, paths, commands, registry keys
- Network Artifact Detector - C2 domains, suspicious ports, DGA
Block 5: Intelligence Automation (+10% = 95% coverage)
- YARA Rule Generator - Auto-generate detection rules
- IOC Exporter - JSON, CSV, STIX 2.1 export
- Android Analyzer - DEX files, dynamic loading, obfuscation
- Report Generator - Professional HTML & Markdown reports
๐ฆ 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 v3.0.0
๐ 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
๐ 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 (New in v3.0)
| 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 (New in v3.0)
| 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 |
๐ก 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
๐ฏ 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/
๐ Example Output
Console Output (Enhanced in v3.0)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ ๐ฅ PROMETHEUS COMMUNITY EDITION v3.0.0 โ
โ Enterprise-Grade Malware Analysis โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Analyzing: malware.exe
SHA256: a1b2c3d4...
Size: 524,288 bytes
Type: PE (Windows executable)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ STATIC ANALYSIS
Entropy: 7.84 โ ๏ธ HIGH - Likely packed or encrypted
File Type: PE
Detected Type: PE
Match: โ Valid
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ DETECTION RESULTS
[HIGH] PE Packer Detected
Packer: UPX
๐ Severity: HIGH | Confidence: 95%
๐ 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
๐ Severity: HIGH | Confidence: 90%
๐ 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
๐ Severity: MEDIUM | Confidence: 95%
๐ Location: String at offset 0x3f20
Context: Suspicious domain with free TLD (.tk)
MITRE: T1071 - Application Layer Protocol
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ 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
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ
Analysis complete! Use --help for export options.
๐ ๏ธ Python API
Basic Usage
from prometheus import PrometheusEngineV3
# Initialize engine
engine = PrometheusEngineV3()
# 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 PrometheusEngineV3
from prometheus.yara_generator import YARARuleGenerator
engine = PrometheusEngineV3()
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 PrometheusEngineV3
from prometheus.ioc_exporter import IOCExporter
engine = PrometheusEngineV3()
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 PrometheusEngineV3
from prometheus.report_generator import ReportGenerator
engine = PrometheusEngineV3()
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)
๐ฌ Detection Capabilities
Windows PE Analysis
- โ PE structure parsing (DOS, NT, COFF, Optional headers)
- โ Section analysis (.text, .data, .rdata, .rsrc, etc.)
- โ Import/Export table analysis
- โ RWX section detection
- โ Packer identification (UPX, ASPack, Themida, 15+ signatures)
- โ Entry point anomalies
- โ Dangerous API detection (30+ APIs across 6 categories)
- โ Anti-debug techniques
- โ Anti-VM techniques
Linux ELF Analysis
- โ ELF header parsing (64/32-bit, endianness)
- โ Section analysis (.text, .data, .bss, .rodata, etc.)
- โ Program header analysis (LOAD, DYNAMIC, INTERP, etc.)
- โ RWX segment detection
- โ Interpreter analysis
- โ Dynamic linking analysis
- โ UPX packer detection
- โ Stripped binary detection
Android APK/DEX Analysis
- โ DEX file structure parsing
- โ Dynamic code loading detection (DexClassLoader)
- โ Reflection pattern analysis
- โ Obfuscation detection (ProGuard/R8)
- โ Suspicious class/method detection
- โ Asset/cache directory references
Cross-Platform Detection
- โ Steganography (EOF append, embedded files, LSB)
- โ Shellcode (NOP sleds, GetPC, syscalls)
- โ XOR/encoding (256 keys, Base64, hex)
- โ Nested files (31 signatures)
- โ Cryptography (AES, MD5, SHA, DES, RSA)
- โ String analysis (URLs, IPs, commands, paths)
- โ Network artifacts (C2 domains, ports, DGA)
๐ Project Structure
prometheus-community/
โโโ prometheus/
โ โโโ __init__.py
โ โโโ engine_v3_0_0.py # Main analysis engine
โ โโโ models_v3.py # Data models
โ โโโ config.py # Configuration
โ โโโ cli.py # CLI interface
โ โ
โ โโโ core/ # Core components
โ โ โโโ file_type_validator.py
โ โ โโโ behavioral_detector_v3.py
โ โ โโโ output_formatter.py
โ โ
โ โโโ detection/ # Detection modules
โ โ โโโ steganography_detector.py
โ โ โโโ shellcode_detector.py
โ โ โโโ xor_encoding_detector.py
โ โ โโโ nested_file_detector.py
โ โ โโโ pe_analyzer.py
โ โ โโโ elf_analyzer.py
โ โ โโโ anti_analysis_detector.py
โ โ โโโ crypto_detector.py
โ โ โโโ string_analyzer.py
โ โ โโโ network_detector.py
โ โ
โ โโโ automation/ # Intelligence automation
โ โ โโโ yara_generator.py
โ โ โโโ ioc_exporter.py
โ โ โโโ android_analyzer.py
โ โ โโโ report_generator.py
โ โ
โ โโโ data/
โ โโโ intelligence_v2_1_cleaned.json
โ
โโโ tests/
โ โโโ test_complete_system.py
โ โโโ validate_block1.py
โ โโโ validate_block2.py
โ โโโ validate_block3.py
โ โโโ validate_block4.py
โ โโโ validate_block5.py
โ
โโโ docs/
โ โโโ BLOCK_1_IMPLEMENTATION.md
โ โโโ BLOCK_2_IMPLEMENTATION.md
โ โโโ BLOCK_3_IMPLEMENTATION.md
โ โโโ BLOCK_4_IMPLEMENTATION.md
โ โโโ BLOCK_5_IMPLEMENTATION.md
โ โโโ COMPREHENSIVE_TEST_REPORT.md
โ
โโโ README.md
โโโ setup.py
โโโ CHANGELOG.md
โโโ LICENSE
โโโ requirements.txt (empty - no dependencies!)
๐ Comparison
| Feature | Prometheus v3.0 | VirusTotal | YARA | Cuckoo |
|---|---|---|---|---|
| Offline Analysis | โ Yes | โ No | โ Yes | โ Yes |
| Windows PE | โ Advanced | โ Yes | โ ๏ธ Basic | โ Yes |
| Linux ELF | โ Advanced | โ ๏ธ Limited | โ ๏ธ Basic | โ ๏ธ Limited |
| Android APK | โ Advanced | โ Yes | โ ๏ธ Basic | โ Yes |
| YARA Generation | โ Auto | โ No | N/A | โ No |
| IOC Export | โ 3 formats | โ ๏ธ Limited | โ No | โ ๏ธ Limited |
| Report Generation | โ HTML/MD | โ No | โ No | โ HTML |
| No Dependencies | โ Yes | N/A | โ No | โ No |
| Open Source | โ Yes | โ No | โ Yes | โ Yes |
| Commercial Use | โ Yes | ๐ฐ Paid | โ Yes | โ Yes |
๐ Documentation
๐ค Contributing
We welcome contributions! See CONTRIBUTING.md.
๐ License
Prometheus Community Edition is released under the Prometheus Community License v1.0.
Key terms:
- โ Free for research, education, and non-profit use
- โ Source available - Review and modify code
- โ Commercial use allowed with attribution
- โ No external dependencies - Deploy anywhere
For enterprise licensing, contact: contact@asnspy.com
See LICENSE for full terms.
๐ Citation
@software{prometheus2026,
author = {Donahue, Damian},
title = {Prometheus Community Edition: Enterprise Malware Analysis},
year = {2026},
publisher = {GitHub},
version = {3.0.0},
url = {https://github.com/0x44616D69616E/prometheus-community},
doi = {10.5281/zenodo.18123287}
}
๐ 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
๐ฌ Community
- GitHub Issues - Bug reports and features
- Discussions - Questions and community
- Email - contact@asnspy.com
- Documentation - Complete guides
๐ Acknowledgments
Built on foundational research:
- Binary Analysis Academic Reference v2.2
- MITRE ATT&CK Framework
- Open source security community
๐ฅ 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:
- โ Analyze any platform (Windows/Linux/Android)
- โ Generate detection rules (YARA)
- โ Export indicators (JSON/CSV/STIX)
- โ Create reports (HTML/Markdown)
- โ Deploy anywhere (no dependencies)
Built for:
- ๐ข Enterprise SOC teams
- ๐ฌ Malware researchers
- ๐ Security educators
- ๐ก๏ธ Incident responders
Made with ๐ฅ by the security research community
Prometheus Community Edition v3.0.0 - Enterprise malware analysis for everyone
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github-hosted -
Publication workflow:
python-publish.yml@84b1d582a2283b36c5e919a1d486fca61e34d949 -
Trigger Event:
release
-
Statement type: