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News & Research → OWASP’s 2026 LLM Security Work: Why AI Safety Needs Adversarial Testing
September 18, 2026

OWASP’s 2026 LLM Security Work: Why AI Safety Needs Adversarial Testing

Source: OWASP GenAI Security Project. Open OWASP Top 10 for LLM & GenAI.

OWASP’s GenAI Security Project maintains community-driven guidance on security risks affecting large-language-model and generative-AI applications. Its 2026 work continues to focus on practical risks in modern LLM applications and agentic systems.

Why it matters

AI governance is incomplete if it never meets hostile inputs, unsafe tool use, data exposure, permission mistakes or other adversarial conditions. Policies need executable tests and operational controls.

How Q10 uses the idea

Q10 Test Range, Gym and TSLP patterns are designed to connect documented controls to repeatable tests, simulations, patches and regression checks. OWASP is an independent security reference; it does not validate Q10.

Important boundary

A checklist pass is not a universal safety guarantee. Security evidence must match the actual system, tools, permissions, data and deployment environment.

Q10 learning content should distinguish sourced facts, interpretation, uncertainty and product claims. Check linked sources and dates before consequential use.