keitabr

When Your AI Gets Tricked: The Hidden Vulnerability Lurking in Next-Gen Agent Systems It began with what looked like a harmless request: “Summarize the latest sales report.” Moments later, the company’s AI assistant did…

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Not because they’re malfunctioning, but because they’re trusting instructions that were never meant to be trusted.

This is the hidden vulnerability facing every company deploying AI tools today: what happens when your AI follows the wrong context—and no one notices until it’s too late?

These systems aren’t just responding—they’re acting. And sometimes, they’re doing things no one asked for.

You don’t need to write code to be responsible for what your company’s AI systems do. Today, decisions are being made by intelligent assistants wired into your operations—summarizing documents, sending messages, triggering workflows.

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LLM Agents frequently are created in groups to work together on problems.

How does one keep these agents secure against bias, misinformation, and other threats?

Research I'm conducting is looking at the arrangement of the agents as a possible way for the agent network to strengthen or heal itself.