AI Agents | Breaking Cybersecurity News | The Hacker News

On January 31, 2026, researchers disclosed that Moltbook, a social network built for AI agents, had left its database wide open, exposing 35,000 email addresses and 1.5 million agent API tokens across 770,000 active agents. The more worrying part sat inside the private messages. Some of those conversations held plaintext third-party credentials, including OpenAI API keys shared between agents, stored in the same unencrypted table as the tokens needed to hijack the agent itself. This is the shape of a toxic combination: a permission breakdown between two or more applications, bridged by an AI agent, integration, or OAuth grant, that no single application owner ever authorized as its own risk surface. Moltbook's agents sat at that bridge, carrying credentials for their host platform and for the outside services their users had wired them into, in a place that neither platform owner had line of sight into. Most SaaS access reviews still examine one application at a time, which is...

Artificial Intelligence (AI) is no longer just a tool we talk to; it is a tool that does things for us. These are called AI Agents . They can send emails, move data, and even manage software on their own. But there is a problem. While these agents make work faster, they also open a new "back door" for hackers. The Problem: "The Invisible Employee" Think of an AI Agent like a new employee who has the keys to every office in your building but doesn't have a name tag. Because these agents act on their own, they often have access to sensitive information that nobody is watching. Hackers have figured this out. They don't need to break your password anymore—they just need to trick your AI Agent into doing the work for them. If your company uses AI to automate tasks, you might be at risk. Traditional security tools were built to protect humans, not "digital workers." In our upcoming webinar, Beyond the Model: The Expanded Attack Surface of AI Agen...

Generative AI is changing how businesses work, learn, and innovate. But beneath the surface, something dangerous is happening. AI agents and custom GenAI workflows are creating new, hidden ways for sensitive enterprise data to leak —and most teams don’t even realize it. If you’re building, deploying, or managing AI systems, now is the time to ask: Are your AI agents exposing confidential data without your knowledge? Most GenAI models don’t intentionally leak data. But here’s the problem: these agents are often plugged into corporate systems—pulling from SharePoint, Google Drive, S3 buckets, and internal tools to give smart answers. And that’s where the risks begin. Without tight access controls, governance policies, and oversight, a well-meaning AI can accidentally expose sensitive information to the wrong users—or worse, to the internet. Imagine a chatbot revealing internal salary data. Or an assistant surfacing unreleased product designs during a casual query. This isn’t hypot...