Prompt Injection: Exploiting Enterprise AI's Biggest Design Flaws

Prompt injection remains the most critical attack vector against LLM systems, exploiting their inability to separate instructions from data. OWASP ranks it as the top LLM vulnerability, and CrowdStrike's 2026 report documented over 90 organizations affected in 2025, with attackers stealing credentials and cryptocurrency. Real-world incidents include a Slack AI vulnerability that leaked private channel data and the EchoLeak zero-click exploit against Microsoft 365 Copilot. Attack techniques have evolved to target multi-agent systems, RAG pipelines, model routers, and long-term memory. Enterprises are advised to constrain model permissions, segment untrusted content, require human approval for high-impact actions, and treat LLMs as untrusted components.