Multi-layer system that verifies GitHub repos via fingerprinting, AST checks, and AI embeddings.
ChatGPT said:
This project is a multi-layer intelligent code verification system designed to analyze GitHub repositories for authenticity and originality. It generates unique fingerprints for each repository, compares structural patterns using AST parsing, and applies AI-based semantic embeddings to detect duplicates or suspiciously similar code. By combining cryptographic hashing, structural analysis, and deep semantic comparison, it ensures accurate verification, helping maintain trust and transparency in code submissions or developer contributions.
This project is a comprehensive multi-layer code verification and similarity analysis system built to ensure authenticity, originality, and integrity of GitHub repositories. It operates through four distinct layers — fingerprinting, structural analysis, semantic understanding, and behavioral validation.
The system begins by generating cryptographic fingerprints using SHA-256 hashes and Merkle roots to uniquely identify each repository. It then performs AST (Abstract Syntax Tree) analysis to evaluate code structure and detect subtle pattern resemblances across projects. Next, AI-based semantic embeddings interpret the contextual meaning of code, enabling detection of logically similar but syntactically different implementations. Finally, it applies behavioral checks such as submission timing and user patterns to flag abnormal or suspicious activity.
This end-to-end approach blends cryptography, static code analysis, and machine learning to deliver a precise, scalable, and secure verification framework—ideal for developer platforms, hackathons, or open-source integrity validation systems.

