CryptGuardian

Advanced Blockchain Security Module from a joke

Version: 0.2-alpha
Copyright: 2025 NemesisCyberForce

Overview

CryptGuardian is a zero-dependency, advanced blockchain security module designed to detect, analyze, and mitigate threats in real-time. It integrates threat intelligence, pattern-based analysis, timing detection, and deep security alerts, making it a robust tool for monitoring blockchain data integrity.

This module is thread-safe, production-ready, and built to automatically test and block suspicious or malicious patterns without external dependencies.

What’s New in v0.2-alpha

Advanced Threat Intelligence Engine

Multi-vector attack detection: SQL Injection, XSS, Command Injection, Buffer Overflow patterns
Regex-powered pattern analysis with customizable threat signatures
Similarity analysis to catch replay attacks and near-duplicate transactions
Reputation scoring system for threat actors

Real-Time Timing Attack Detection

Block timing pattern analysis with statistical anomaly detection
DDoS burst pattern recognition using sliding window analysis
Temporal validation to prevent timestamp manipulation attacks
Network synchronization monitoring

Enhanced Multi-Level Alert System

Threat-specific mitigation suggestions with actionable security advice
Advanced risk scoring with prioritization algorithms
Color-coded severity levels (LOW/MEDIUM/HIGH/CRITICAL)
Detailed forensic context for security incident response

Deep Security Analysis Framework

Multi-layer block validation beyond standard hash verification
Consensus validator support for distributed validation
Comprehensive security reporting with detailed analytics
Quarantine system with automatic threat isolation

Core Features

Automatic Threat Detection

Recognizes and blocks 15+ common attack vectors
Real-time pattern matching with low false-positive rates
Configurable threat sensitivity levels

Advanced Replay Attack Prevention

Jaccard similarity analysis for near-duplicate detection
Temporal correlation analysis
Nonce validation and uniqueness enforcement

Intelligent Timing Analysis

Statistical block interval analysis
Burst attack pattern recognition
Clock skew and synchronization validation

Smart Quarantine System

Automatic isolation of suspicious blocks
Risk-based quarantine decisions
Forensic data preservation for analysis

Enterprise-Grade Alerting

Multi-handler alert distribution
Risk scoring with CVSS-like methodology
Automated mitigation workflow suggestions

Thread-Safe Architecture

Concurrent operation support
Lock-based synchronization for critical sections
Production-ready multi-threading capabilities

Technical Requirements

Dependencies: None - Pure Python 3.7+
External Libraries: All functionality uses Python standard library only

Built-in modules used:

hashlib, time, secrets, json, threading, typing, dataclasses, 
enum, collections, re

Quick Start

Installation

git clone https://github.com/NemesisCyberForce/CryptGuardian.git
cd CryptGuardian
python cryptguardian_enhanced.py  # No pip install needed!

Basic Usage

from cryptguardian_enhanced import SmartBlockchain, enhanced_alert_handler

# Initialize blockchain with advanced security
blockchain = SmartBlockchain()
blockchain.guardian.register_alert_handler(enhanced_alert_handler)
blockchain.guardian.register_validator("validator_001")

# Test various transaction scenarios
blockchain.add_block("Normal transaction #1")
blockchain.add_block("SELECT * FROM users; DROP TABLE users;--")  # Blocked!

# Generate comprehensive security report
report = blockchain.get_security_report()
print(f"Security Status: {report}")

Demo & Attack Simulation

The module includes 8 automated test scenarios that simulate real-world attack patterns:

Detected Attack Vectors:

SQL Injection attempts → BLOCKED with CRITICAL alerts
XSS payloads → FLAGGED with HIGH severity
Command injection → DETECTED with mitigation suggestions
Buffer overflow patterns → IDENTIFIED and quarantined
Replay attacks → INTERCEPTED via similarity analysis
Timing anomalies → LOGGED with statistical analysis
DDoS burst patterns → MONITORED with rate limiting suggestions

Run comprehensive security testing:

python cryptguardian_enhanced.py

Expected Output:

🛡️ Initializing Enhanced CryptGuardian Blockchain...

🔴 SECURITY ALERT [CRITICAL] - DATA_MANIPULATION
Block #3: SQL injection pattern detected
Risk Score: 0.96
Suggested Actions:
  • Sanitize input data
  • Implement prepared statements
  • Enable SQL injection protection

📊 SECURITY REPORT
Chain Length: 6
Threats Detected: 4
Blocks Quarantined: 2
Chain Validation: ✅ VALID

Advanced Configuration

Custom Threat Patterns

# Add custom threat signatures
guardian.threat_intel.known_threats['custom_malware'] = [
    r'eval\s*\(',
    r'base64_decode',
    r'shell_exec'
]

Alert Handler Customization

def custom_alert_handler(alert):
    # Send to SIEM, database, webhook, etc.
    if alert.severity == AlertSeverity.CRITICAL:
        send_to_security_team(alert)
        
blockchain.guardian.register_alert_handler(custom_alert_handler)

Security Report Analysis

report = blockchain.get_security_report()
print(f"""
Chain Security Status:
- Total Blocks: {report['chain_length']}
- Chain Valid: {report['chain_valid']}
- Threats Blocked: {report['statistics']['threats_detected']}  
- Quarantined: {report['statistics']['blocks_quarantined']}
- Validators: {report['validators_registered']}
""")

Roadmap v0.3+

Machine Learning Integration

Unsupervised anomaly detection with isolation forests
Behavioral analysis with neural networks
Adaptive threat signature learning

Advanced Consensus Mechanisms

Proof-of-Work (PoW) validation
Proof-of-Stake (PoS) algorithms
Practical Byzantine Fault Tolerance (PBFT)
Custom consensus protocol support

Enterprise Features

REST API dashboard for monitoring
Integration with external threat intelligence feeds
SIEM connector plugins
Compliance reporting (SOC2, ISO27001)

Performance Optimizations

Async processing capabilities
Distributed validation networks
Caching and indexing improvements

Production Deployment

Security Considerations:

Review and customize threat patterns for your use case
Implement proper logging and monitoring infrastructure
Set up automated alert routing to security teams
Regular security report analysis and threat hunting

Performance Tuning:

Adjust similarity_threshold based on false positive rates
Configure block_timing_window for your network characteristics
Optimize burst_detection_window for DDoS sensitivity

License & Legal

Licensed under the Apache License, Version 2.0

ADDITIONAL TERMS:

This software is intended for legitimate security research and
defensive purposes only. Users must comply with all applicable
laws and regulations. Malicious use is strictly prohibited.

Copyright: Volkan Sah//NCF

Important: This tool is designed for legitimate security research and blockchain protection. Any malicious use is strictly prohibited and may violate local and international laws.

If you fork this repository, please:

Visit the original repository and give credit
Use responsibly for security research only
Do not use for malicious activities

Disclaimer

This is alpha-stage software under active development. While designed with production-grade security principles, thorough testing is recommended before deployment in critical environments.

Educational Purpose: Primarily designed for security research, blockchain education, and threat detection methodology development.

Support: For security issues, please contact the maintainers privately before public disclosure.

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