Large Language Models (LLMs) are becoming a core part of modern applications — from copilots and chatbots to AI agents connected to tools and internal systems. As adoption grows, so do the security risks. The OWASP Top 10 for LLM Applications (2025) highlights the most common security issues teams must address when building AI-powered systems. These risks go beyond traditional application security because LLMs interact with prompts, external data, tools, and autonomous workflows. In this post, we'll cover a practical overview of each risk and how teams can detect, prevent, and test for them. LLM01:2025 — Prompt Injection Prompt injection is when an attacker slips malicious instructions into user input or content the model reads, tricking it into doing something it shouldn't. Direct injection: A user directly tells the model to ignore its rules. Indirect injection: The model reads an external document or web page that secretly contains instructions and follows them without realizing it.…