Originally published at kunalganglani.com — read it there for inline code, hero image, and live links.
Prompt injection is a class of attack where crafted inputs manipulate a large language model into ignoring its instructions, leaking data, or performing unauthorized actions. It has held the #1 position — LLM01 — on OWASP's Top 10 for LLM Applications across every published edition, from the original 2023/24 list through the 2025 update. No other LLM vulnerability has pulled that off. And now that agentic AI systems are handing models real-world tools, prompt injection in 2026 isn't an academic curiosity. It's an active enterprise threat.
I've spent the last two years building and reviewing systems that put LLMs in production. The pattern I keep running into is always the same: teams treat prompt injection as a prompt engineering problem. Write a better system prompt, add some guardrail language, ship it. But it's not a prompt problem. It's an architecture problem. And until more developers internalize that distinction, this vulnerability isn't going anywhere.
Why Prompt Injection Is Still OWASP's Number One LLM Vulnerability
The OWASP GenAI Security Project isn't a handful of people with an opinion. It's a global community of over 600 contributing security experts from more than 18 countries, with nearly 8,000 active members. When they rank prompt injection as LLM01 for the second consecutive list edition, that's about as close to consensus on AI security risks as we're going to get.
