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Network-Pinpointer

Semantic Network Diagnostic Tool using LJPW Framework

Network-Pinpointer applies the Love, Justice, Power, Wisdom (LJPW) semantic framework to network administration and diagnostics. It maps network operations, devices, and configurations to a four-dimensional semantic space, enabling unprecedented insights into network infrastructure.

Overview

This tool is built on experimental mathematical foundations that treat network operations as semantic primitives in LJPW space:

  • Love (L): Connectivity, communication, integration, service sharing
  • Justice (J): Rules, policies, validation, security, compliance
  • Power (P): Performance, control, execution, resource management
  • Wisdom (W): Information, monitoring, diagnostics, analysis

Every network operation can be mapped to coordinates (L, J, P, W) in this 4D space, allowing semantic analysis of network health, harmony, and architecture.

Features

Core Diagnostics

  • Semantic Ping: Test connectivity with LJPW coordinate analysis
  • Semantic Traceroute: Trace network paths with semantic interpretation
  • Semantic Port Scanning: Discover services mapped to semantic space
  • Network Interface Analysis: Analyze interfaces through LJPW lens

Advanced Analysis

  • Network Topology Mapping: Scan entire networks and cluster by semantic purpose
  • Architectural Smell Detection: Identify configuration anti-patterns
  • ICE Framework Analysis: Measure Intent-Context-Execution harmony
  • Network Optimization: Recommendations based on semantic disharmony

Visualizations

  • Semantic coordinate visualization
  • Network topology clusters
  • Harmony score analysis
  • JSON export for integration

Installation

Linux / macOS

# Clone the repository
git clone https://github.com/BruinGrowly/Network-Pinpointer.git
cd Network-Pinpointer

# Install dependencies (optional, for packet capture)
pip install scapy pyyaml

# Make the CLI executable
chmod +x pinpoint

# Run
./pinpoint --help

Windows

See Windows Installation Guide for complete instructions.

Quick start for Windows:

# Install dependencies
pip install scapy pyyaml

# Run with Python
python pinpoint --help

Requirements: Python 3.8+, Npcap (Windows only)

Quick Start

Basic Diagnostics

# Ping with semantic analysis
./pinpoint.py ping 8.8.8.8

# Traceroute with semantic path analysis
./pinpoint.py traceroute google.com

# Port scan with service classification
./pinpoint.py scan 192.168.1.1 -p 22,80,443,3389

# Scan port range
./pinpoint.py scan 192.168.1.100 -p 1-1024

Network Mapping

# Map entire subnet with semantic topology analysis
./pinpoint.py map 192.168.1.0/24

# Export topology to JSON
./pinpoint.py map 192.168.1.0/24 --export-json network_map.json

Semantic Analysis

# Analyze any network operation
./pinpoint.py analyze "configure firewall rules to block unauthorized access"

# ICE Framework: Analyze harmony between intent, context, and execution
./pinpoint.py ice \
  "establish secure connection to database server" \
  "network has firewall with strict outbound rules" \
  "open port 3306 and configure mysql connection"

Understanding LJPW Mapping

Network Operation Classification

Operation Love Justice Power Wisdom Classification
Ping High Low Low High Connectivity Test (Wisdom+Love)
Firewall Config Low High Med Low Security Policy (Justice)
Bandwidth Allocation Low Low High Low Performance Control (Power)
SNMP Monitoring Low Low Low High Information Gathering (Wisdom)
VPN Setup High Med Med Low Secure Communication (Love+Justice)
Load Balancing High Low High Low Service Distribution (Love+Power)

Example Semantic Coordinates

ping 8.8.8.8:
  L=0.35 (connectivity test)
  J=0.15 (validation)
  P=0.10 (minimal execution)
  W=0.40 (diagnostic/information)
  → Dominant: Wisdom (Monitoring/Diagnostics)

configure firewall deny all:
  L=0.05 (minimal connectivity)
  J=0.60 (policy enforcement)
  P=0.30 (execution/control)
  W=0.05 (minimal info)
  → Dominant: Justice (Security/Policy)

monitor network traffic:
  L=0.20 (observing communication)
  J=0.15 (checking rules)
  P=0.10 (passive action)
  W=0.55 (gathering information)
  → Dominant: Wisdom (Monitoring/Diagnostics)

ICE Framework for Networks

The Intent-Context-Execution (ICE) framework measures harmony between what you want to do, the current network state, and what actually happens.

Example:

./pinpoint.py ice \
  "provide fast reliable web service" \
  "limited bandwidth high latency network" \
  "deploy nginx with caching and compression"

Output:

  • ICE Coherence: How well intent aligns with execution
  • ICE Balance: How realistic the intent is given the context
  • Benevolence Score: Focus on connectivity/service (Love dimension)
  • Harmony Level: Overall assessment

High harmony = network operations are well-aligned Low harmony = mismatches that may cause issues

Network Topology Mapping

The map command scans a network range and clusters devices by semantic purpose:

./pinpoint.py map 192.168.1.0/24

Output includes:

  • Semantic clusters (Love, Justice, Power, Wisdom dominant devices)
  • Architectural smells (security issues, unclear purposes, high latency)
  • Optimization opportunities (service consolidation, security upgrades)
  • Cohesion scores (how well-defined each cluster is)

Example Clusters

Love Cluster (Connectivity-focused devices):

  • Web servers (HTTP/HTTPS)
  • VPN gateways
  • Load balancers
  • Communication hubs

Justice Cluster (Policy-focused devices):

  • Firewalls
  • Authentication servers
  • Security gateways
  • Access control systems

Power Cluster (Performance-focused devices):

  • Application servers
  • Database servers
  • Compute nodes
  • Control systems

Wisdom Cluster (Information-focused devices):

  • Monitoring systems
  • Log servers
  • SNMP agents
  • Diagnostic tools

Architecture

network_pinpointer/
├── semantic_engine.py      # Core LJPW semantic engine
├── diagnostics.py          # Network diagnostic tools
├── network_mapper.py       # Topology mapping and analysis
└── cli.py                  # Command-line interface

pinpoint.py                 # Main entry point

Key Components

NetworkSemanticEngine: Maps network operations to LJPW coordinates NetworkVocabularyManager: 300+ network terms mapped to dimensions NetworkDiagnostics: Traditional tools with semantic layer NetworkMapper: Full network scanning and topology analysis

Mathematical Foundation

Network-Pinpointer is based on proven mathematical frameworks:

  1. LJPW as Orthogonal Basis: Love, Justice, Power, Wisdom form a complete, minimal, orthogonal basis for semantic meaning
  2. Linear Mixing Formula: Concept coordinates = weighted average of component dimensions
  3. Distance Metrics: Euclidean distance measures semantic disharmony
  4. Anchor Point: (1,1,1,1) represents perfect harmony of all dimensions

For details, see the theoretical foundations in sister projects.

Use Cases

1. Network Troubleshooting

  • Identify semantic mismatches between intent and execution
  • Detect configuration drift from intended purpose
  • Find devices with unclear roles

2. Security Auditing

  • Discover exposed insecure services (Justice dimension)
  • Identify overly complex attack surfaces
  • Map security policy enforcement

3. Performance Analysis

  • Find Power-dominant bottlenecks
  • Optimize resource allocation
  • Balance load semantically

4. Documentation & Compliance

  • Verify network matches documented architecture
  • Generate semantic topology maps
  • Track configuration drift over time

5. Network Design

  • Plan new infrastructure using LJPW framework
  • Ensure semantic coherence across clusters
  • Design for harmony between components

Experimental Nature

⚠️ This is experimental research technology.

The LJPW semantic framework is under active development. While the mathematical foundations are sound, practical applications to network administration are still being explored.

Current Status:

  • ✅ Core semantic engine operational
  • ✅ Network vocabulary (300+ terms mapped)
  • ✅ Basic diagnostics with semantic layer
  • ✅ Topology mapping and clustering
  • 🚧 Historical trend analysis (planned)
  • 🚧 Predictive harmony modeling (planned)
  • 🚧 Integration with existing tools (planned)

Examples

Example 1: Ping Analysis

$ ./pinpoint.py ping 8.8.8.8

🔍 Pinging 8.8.8.8...
======================================================================

Host: 8.8.8.8
Status: ✓ Reachable
Packets: 4/4 received
Packet Loss: 0.0%
Average Latency: 14.2ms

📊 SEMANTIC ANALYSIS
Coordinates: Coordinates(L=0.286, J=0.143, P=0.000, W=0.571)
Analysis: Operation: Monitoring/Diagnostics (Wisdom-dominant) | Quality: excellent connectivity

Dimension Breakdown:
  Love (Connectivity):  ████████░░░░░░░░░░░░ 29%
  Justice (Validation): ████░░░░░░░░░░░░░░░░ 14%
  Power (Execution):    ░░░░░░░░░░░░░░░░░░░░ 0%
  Wisdom (Diagnostic):  ███████████░░░░░░░░░ 57%

Example 2: Network Map

$ ./pinpoint.py map 192.168.1.0/24

🔍 Scanning network: 192.168.1.0/24
======================================================================
✅ Scanned 254 hosts, 12 reachable
======================================================================

📊 OVERALL METRICS
   Total devices discovered: 12
   Average network latency: 3.4ms

🗺️  TOPOLOGY CLUSTERS

💛 Love Cluster (5 devices)
   Cohesion: 87%
   Avg Coordinates: Coordinates(L=0.654, J=0.123, P=0.112, W=0.111)
     • 192.168.1.10   - Web Service (Connectivity)
       Ports: 3 open | Latency: 2.1ms
     • 192.168.1.20   - Communication Hub (Love)
       Ports: 2 open | Latency: 1.8ms
     ... and 3 more devices

⚖️  Justice Cluster (3 devices)
   Cohesion: 92%
   Avg Coordinates: Coordinates(L=0.089, J=0.701, P=0.145, W=0.065)
     • 192.168.1.1    - Security Gateway (Justice)
       Ports: 2 open | Latency: 0.9ms
     ... and 2 more devices

🚨 NETWORK CONFIGURATION ISSUES (4 detected)
======================================================================

CRITICAL (2 issues):
  • Insecure Services: 192.168.1.50
    Dangerous ports exposed: [23, 21]
    → Disable insecure protocols. Use SSH/SFTP/encrypted alternatives.

HIGH (1 issues):
  • Excessive Open Ports: 192.168.1.100
    Device has 15 open ports (threshold: 10)
    → Review and close unnecessary ports. Apply principle of least privilege.

💡 OPTIMIZATION OPPORTUNITIES (Top 5)
======================================================================

1. 192.168.1.10 - Security Upgrade
   Potential improvement: 70%
   HTTP service without HTTPS
   Suggested actions:
     → Enable HTTPS/TLS encryption
     → Redirect HTTP to HTTPS
     → Obtain SSL certificate

Example 3: ICE Analysis

$ ./pinpoint.py ice \
    "secure fast database connection" \
    "firewalled network with limited bandwidth" \
    "open mysql port enable caching"

🔍 ICE HARMONY ANALYSIS
======================================================================

Intent:    secure fast database connection
Context:   firewalled network with limited bandwidth
Execution: open mysql port enable caching

📊 HARMONY METRICS
ICE Coherence:     68%
ICE Balance:       72%
Overall Harmony:   70%
Harmony Level:     GOOD_HARMONY
Benevolence Score: 35%
Intent-Execution Disharmony: 0.524

💡 RECOMMENDATIONS
✓ Moderate harmony - minor misalignment between components

Contributing

This is experimental research. Contributions, feedback, and discussion are welcome!

Areas of interest:

  • Expanding network vocabulary coverage
  • Validating semantic mappings empirically
  • Integration with existing network tools
  • Historical analysis and drift detection
  • Cross-network pattern recognition

License

See LICENSE file.

Related Projects

  • Python-Code-Harmonizer: Applies LJPW framework to code analysis
  • DIVE-V2 Engine: Core semantic substrate engine

Citation

If you use this work in research:

Network-Pinpointer: Semantic Network Diagnostic Tool
Using Love-Justice-Power-Wisdom (LJPW) Framework
2025

Built with the LJPW Semantic Framework Love • Justice • Power • Wisdom

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