KALSNET (KNet) CYBER DEFENSE APPLICATIONS PORTAL

Agentic-AI-Multi-Use-Case-Cyber-Defense-Platform

The KNet Agentic-AI Cyber Defense Platform is an advanced AI-powered cybersecurity analytics application designed to detect, analyze, and visualize enterprise security threats across multiple cyber defense use cases. Built using [Streamlit](https://streamlit.io?utm_source=chatgpt.com), Python, pandas, and Plotly, the platform generates detailed threat intelligence insights, risk interpretation, mitigation recommendations, and executive cybersecurity reports.

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Agentic-AI-Multi-Use-Case-Cyber-Defense-Platform1

The KNet Agentic-AI Cyber Defense Platform is an advanced AI-powered cybersecurity analytics application (Using LLMs Grouq & Gemini) designed to detect, analyze, and visualize enterprise security threats across multiple cyber defense use cases. Built using,Python, pandas, and Plotly, the platform generates detailed threat intelligence insights, risk interpretation, mitigation recommendations, and executive cybersecurity reports.

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Agentic-AI Cyber Range Advanced

The -Agentic AI Cyber Range Platform- is a web-based cybersecurity training and simulation environment designed to demonstrate how modern organizations detect, investigate, and respond to cyber threats. The application is developed using the Python framework Streamlit, which provides an interactive dashboard interface that allows users to simulate cyber-attack scenarios and defensive operations in real time. The platform contains a structured -attack library of common enterprise cyber threats-, including phishing, ransomware, SQL injection, insider threats, and cloud account compromise. Each attack scenario includes a clearly defined objective, target systems, entry method, and vulnerability, enabling the system to simulate how adversaries exploit weaknesses in enterprise environments.

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Agentic-AI Cyber Range Testing

This program is a Streamlit-based Enterprise Cyber Range SaaS simulation platform designed to emulate real-world Security Operations Center (SOC) environments in a safe, controlled setting. It allows users to generate synthetic cyberattack data using Faker, simulate multi-tenant SaaS environments, and analyze attack activity across different organizational roles (Admin, Instructor, Analyst). The system calculates dynamic risk scores based on severity, attack success, and response time, providing a realistic threat-scoring model. It integrates Scikit-learn’s Isolation Forest algorithm to perform AI-driven anomaly detection, identifying suspicious activity based on behavioral patterns.

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AI Threat Detection

Machine learning-based anomaly detection using Isolation Forest.

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Fraud Detection System

AI-powered financial fraud risk scoring and transaction monitoring.

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Cyber Threat Hunting Dashboard

Advanced threat hunting using behavioral analytics and MITRE ATT&CK mapping.

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API Security Analyzer Platform

Detect API vulnerabilities, risk scoring, and compliance validation.

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API Discovery And Risk Analytics Platform

API Discovery and Risk Analytics platform that automatically discovers APIs from traffic data, assesses their security risk, and produces executive-ready reports.

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API Runtime Posture Management Platform

API Runtime & Posture Management Platform is a comprehensive, enterprise-grade tool designed to simulate, analyze, and visualize API behavior using both synthetic and real F5 BIG-IP–style data & cybersecurity best practices.

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MCP Cybersecurity Framework

Comprehensive AI/ML-driven platform for monitoring, analyzing, and responding to cyber threats.

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DoD War Planning Platform

AI Controlled War Command Platform is an advanced AI-Driven Decision Support System designed to enable real-time operational awareness, intelligent threat evaluation, and optimized mission execution.

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Global Threat 6G Use Case

The AEGIS-6X application simulates a 6G-enabled, AI-driven threat intelligence platform that ingests real or synthetic threat data, applies machine-learning anomaly detection, and fuses edge and core risk signals into a unified risk score.

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Threat Hunting Studio - AI/ML Enterprise Platform

Threat Hunting Studio With MITRE ATT&CK Mapping & AI Remediation Playbooks.

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Defense-In-Depth Cybersecurity Strategy - AI/ML Enterprise Platform

The proposed Defense-in-Depth Cybersecurity Strategy Demo is a web-based, interactive platform designed to illustrate layered cybersecurity controls and operational risk management in accordance with DoD RMF and ATO readiness requirements.

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Compliance SOC Dashboard

Threat Monitoring & Fedramp/DoD Commercial SOC

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SIEM Enterprise Platform

The SIEM Enterprise Platform provides an integrated, defense-in-depth cybersecurity capability designed to enhance situational awareness, threat detection, and compliance across Department of Defense information systems.

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Supply Chain Risk Estimator

Analyzes SBOMs (Software Bill of Materials) for vulnerabilities, licensing, and trust risks.

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Stock Comparison Tool

Fetches historical stock data from Yahoo Finance, calculates P/E ratios, dividends, revenue, net margins, and one-year returns.

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Policy Developer AI Tool

This tool helps organizations rapidly generate compliance-ready policies aligned with standards like NIST, ISO, HIPAA, and GDPR, reducing manual drafting time from days to minutes. It is valuable for cybersecurity teams, compliance officers, auditors, and IT governance professionals who need consistent, auditable documentation. It also ensures standardization across enterprises, improves regulatory readiness, and reduces human error in policy creation.

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AI Drone Inspection & Risk Assessment Platform

This Streamlit-based application, --KNet SkyGuard AI™ – AI Drone Inspection & Risk Assessment Platform--, is an intelligent dashboard designed to process, analyze, and visualize drone inspection data while automatically calculating risk scores for inspected assets. The system allows users to either upload real-world inspection datasets (CSV, Excel, or JSON) or generate synthetic drone inspection data for testing and simulation purposes. At its core, the program applies a weighted risk formula that evaluates four key factors—severity of damage, weather conditions, battery level, and AI confidence—to compute a final risk score for each inspection. The platform is built using --Streamlit-- for the interactive web UI, --Pandas-- for data handling, --NumPy and Random-- for synthetic data generation, and --Plotly-- for real-time analytics visualizations such as histograms and scatter plots. It also integrates--ReportLab -- for PDF report generation and --python-docx-- for Word document exports, enabling professional reporting in multiple formats including JSON for system integration. Users can navigate through modules like dashboard analytics, synthetic data generation, data upload, and export tools via a sidebar interface. In real-world use, this system supports drone-based infrastructure inspections in industries such as energy, construction, defense, and utilities by helping teams quickly identify high-risk assets and prioritize maintenance. It improves operational efficiency by reducing manual inspection effort, enhances safety by detecting high-risk conditions early, and supports compliance reporting through automated documentation. Overall, it acts as a lightweight AI-assisted decision-support tool for risk assessment and asset monitoring using drone-collected data.

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