InfoWorld

How pairing SAST with AI dramatically reduces false positives in code security

In our study, a novel SAST-LLM mashup slashed false positives by 91% compared to a widely used standalone SAST tool.
The Hacker News

Tsundere Botnet Expands Using Game Lures and Ethereum-Based C2 on Windows

Tsundere botnet spreads via MSI and PowerShell installers, using Ethereum-based C2 rotation and game-themed lures to target ...
IEEE

Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection

Abstract: Code embedding represents code semantics in vector form. Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is ...
IEEE

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements

Abstract: This study examined code issue detection and revision automation by integrating Large Language Models (LLMs) such as OpenAI’s GPT-3.5 Turbo and GPT-4o into software development workflows. A ...

An incredibly popular JavaScript library might have some worrying malware issues

A widely-adopted JavaScript library has been found carrying a critical vulnerability which could allow threat actors to ...