Indirect prompt injection is the most widespread and serious vulnerability in AI agents today, not just a theoretical risk.
Research shows attacks can transfer across models and behaviors, revealing a fundamental weakness in how agents interpret context. More capable models aren’t safer, high performance often comes with equally high vulnerability.
Attacks are especially dangerous because they remain hidden, producing normal-looking outputs while executing harmful actions.
With no reliable defenses yet, securing agents requires architectural safeguards, not just better prompts.
