IT_Security

  The Risk That Wasn’t Patched: AI’s New Attack Surface In the rush to capture the productivity gains of  AI-powered development , many businesses overlooked a critical question:  Who is governing the AI itself? A recent, critical vulnerability in  GitHub Copilot Chat  provides a definitive and costly answer. This wasn’t a flaw in GitHub’s core servers; it was a clever exploitation of how the AI assistant interacted with user context—a vulnerability that enabled attackers to execute a  Remote Prompt Injection  attack. This exploit is the clearest signal yet to business leaders and CISOs that  Generative AI  is not just an efficiency tool; it is a fundamental expansion of your security perimeter.   The Anatomy of the Leak: What Really Happened? Security researchers detailed a flaw that allowed a malicious user to gain  full control  over Copilot Chat’s responses and exfiltrate highly sensitive data from the private repositories ...

Why AI Code Assistants Are Creating New Security Vulnerabilities The era of AI coding tools is here, promising unprecedented leaps in productivity. With nearly three-quarters of developers now using or planning to use AI assistants—primarily to increase efficiency and accelerate learning—the benefits are clear. However, this widespread adoption has created a massive, urgent security problem:  the AI governance gap. The core issue lies in trust and speed. Developers, often under immense pressure to deploy code faster, are increasingly copying and pasting code from Large Language Models (LLMs) directly into production. While this accelerates development, it bypasses traditional scrutiny, allowing potentially fatal flaws to slip into the codebase. The data is sobering: Even top LLMs can generate solutions that are incorrect or contain a vulnerability in up to  62% of cases . Among the  correct  solutions, nearly half are still insecure. This means AI coding assistants, ...