Parseon
AI Security Assessment Tool
Automatically assess security gaps, vulnerabilities, and risks in your AI implementations using advanced LLM analysis and embedding-based validation.
Portfolio Project
Parseon is a portfolio project showcasing my expertise in AI security and full-stack development. It demonstrates a sophisticated approach to detecting security vulnerabilities in AI-integrated applications using a dual-layer analysis system.
This project was built to demonstrate practical implementation of emerging AI security patterns and best practices, with a focus on identifying issues like prompt injection vulnerabilities, insecure API usage, and improper input validation.
About Me
I'm a cybersecurity professional pivoting into AI security, with a focus on identifying and addressing vulnerabilities specific to AI implementations. I'm passionate about building secure AI systems that organizations can deploy with confidence.
My experience with large language models, RAG architecture, and security frameworks gives me a unique perspective on AI security challenges. Parseon represents my approach to systematically assessing and validating AI security posture across different implementation patterns.
Key Features
Advanced LLM Analysis
Utilizes large language models to detect complex AI security vulnerabilities with high precision
Embedding-Based Validation
Validates findings against known vulnerability patterns using semantic similarity for reduced false positives
Interactive Reporting
Provides comprehensive security reports with validated findings and actionable recommendations