How indirect prompt injection attacks on AI work - and 6 ways to shut them down

The article outlines the emerging threat of indirect prompt injection attacks on large language models, where malicious instructions hidden in web pages or external content can cause LLMs to exfiltrate data, execute commands, or produce harmful outputs; it presents real-world examples (API key theft, system override, attribute hijacking, command injection), cites vendor advisories and CVE examples, and recommends defenses such as sanitization, least privilege, monitoring, and human oversight.