Abstract: This research describes how we implemented machine learning technology to help detect malicious participants on the Ethereum blockchain, including fake smart contracts and honeypots.

The secondary raw materials market is growing and the demand is real. The opportunities are massive, but growth without trust creates casualties. Blockchain and smart contracts do not eliminate risk; ...

This is a Streamlit-based web application that generates Ethereum smart contracts with customizable parameters. The application provides an intuitive interface for creating various types of smart ...

Smart contracts are the backbone of decentralized applications, decentralized finance (DeFi), and blockchain ecosystems. Unlike traditional software, once deployed, smart contracts are immutable, ...

CrossCurve’s ReceiverAxelar contract lacked validation checks, enabling attackers to spoof messages. The exploit drained approximately $3 million from PortalV2 across multiple blockchain networks.

A ransomware operation known as DeadLock has been observed abusing Polygon blockchain smart contracts to manage and rotate proxy server addresses. DeadLock first appeared in July 2025 and has ...

Learn how to build a perceptron from scratch in Python! This tutorial covers the theory, coding, and practical examples, helping you understand the foundations of neural networks and machine learning.

While the market watches the price of crypto, another indicator emerges. Ethereum recorded a record 8.7 million smart contracts deployed in the fourth quarter, according to Token Terminal. This peak ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...