BeNet is a working bilingual (Spanish–English) QR and URL verification platform designed to make trustworthy threat intelligence accessible to ordinary people while providing reusable defensive infrastructure for researchers and developers.

A public prototype is available at https://beoriginal.id, where anyone can verify QR codes and URLs directly from a mobile browser. This grant focuses on extending that platform into reusable public cybersecurity infrastructure.

AI has dramatically reduced the cost of creating convincing phishing websites, malicious QR codes (quishing), and brand impersonation campaigns. Meanwhile, existing threat intelligence tools are largely designed for enterprise security teams and technical users, leaving millions of people to rely almost entirely on their own judgment before opening a QR code or clicking a link.

BeNet combines international threat intelligence, transparent heuristics, explainable AI, and community reporting into a publicly accessible verification platform. Unlike traditional threat intelligence feeds, BeNet is designed to be understandable by non-technical users while remaining reusable for researchers and developers.

The platform is already deployed and publicly available. This project focuses on extending it into reusable public cybersecurity infrastructure through open defensive components, technical documentation, evaluation benchmarks, public APIs, and multilingual detection methodologies that other researchers, developers and organizations can build upon.

What are this project's goals? How will you achieve them?

Our goal is to reduce the cost of defending against phishing, malicious QR codes, and brand impersonation while contributing reusable defensive infrastructure to the broader cybersecurity ecosystem.

During this project we will:

• Develop AI-assisted multilingual brand impersonation detection.

• Build an explainable risk engine that clearly communicates why a QR code or URL is considered suspicious.

• Launch community-assisted threat reporting and validation.

• Publish multilingual evaluation benchmarks.

• Release technical documentation and reusable APIs.

• Publish reusable defensive methodologies under permissive open-source licenses whenever legally possible.

Rather than replacing existing threat intelligence providers, BeNet complements them by making threat intelligence easier to understand, more transparent, and more accessible to everyone.

How will this funding be used?

Funding will accelerate capabilities that are difficult to achieve using deterministic rules alone.

Resources will primarily support:

• AI API usage for multilingual threat analysis.

• Software engineering.

• Security testing.

• Infrastructure and hosting.

• Documentation.

• Benchmark and dataset creation.

• Community reporting infrastructure.

• Public release and maintenance of reusable open components.

With the minimum funding (USD $7,500) we will complete the explainable risk engine, publish the first multilingual evaluation benchmark, release technical documentation, and open the first reusable defensive components.

With the full funding goal (USD $30,000) we will additionally publish public APIs, expand multilingual detection capabilities, release community reporting infrastructure, publish reusable datasets and documentation, and significantly improve coverage for regional phishing campaigns across Spanish-speaking countries.

Who is on your team? What's your track record on similar projects?

The project is currently led by Juan Francisco Salcido, founder of BeOriginal.id.

For more than thirteen years I have developed technologies focused on authenticity, anti-counterfeiting, product verification, and digital trust. My work includes multiple patent families, commercial authentication technologies, and verification systems designed to reduce fraud across physical and digital environments.

BeNet builds upon an already operational verification platform and represents the evolution of that experience into reusable public cybersecurity infrastructure.

As the project grows, we expect to collaborate with additional open-source contributors, security researchers, and community volunteers.

What are the most likely causes and outcomes if this project fails?

The greatest risk is not technical.

The core verification platform already exists and is operational. The primary challenge is maximizing its public value through community participation, continuous reporting of emerging threats, and adoption of the reusable components we intend to publish.

Even if community adoption grows more slowly than expected, the project will still deliver valuable public resources including explainable detection methods, technical documentation, evaluation benchmarks, reusable APIs, multilingual datasets, and defensive methodologies that other cybersecurity initiatives can continue to build upon.

How much money have you raised in the last 12 months, and from where?

No external funding has been raised for BeNet during the last twelve months.

Development has been entirely founder-funded as part of the broader BeOriginal.id initiative.

Open Deliverables

This grant will produce reusable public resources, including:

• Explainable Risk Engine

• Multilingual Brand Impersonation Benchmark

• Public Evaluation Dataset

• Threat Intelligence API

• Community Reporting Framework

• Technical Documentation

• Open Detection Methodologies

• Multilingual Evaluation Benchmarks