OWASP LLM Top 10

The OWASP LLM Top 10 is a community-maintained list of the ten most critical security risks in applications built on large language models. Published by the Gen AI Security Project at the Open Worldwide Application Security Project (OWASP), it covers LLM software the way the original OWASP Top 10 covers web applications.

The current 2026 revision, formally titled the OWASP Top 10 for LLM Applications 2026, names these risks in rank order:

• Prompt injection
• Sensitive information disclosure
• Excessive agency
• Supply chain
• Data and model poisoning
• Unbounded consumption
• Misinformation
• Hidden context exposure
• Vector and embedding weaknesses
• Improper output handling

Each entry documents the risk, its attack scenarios, and mitigations such as guardrails, least-privilege tool access, and output validation. Security teams use the list as a coverage checklist for threat modeling and red teaming.

First released in 2023, the list is revised as new risks surface. The 2025 edition dropped model theft and added system prompt leakage, along with vector and embedding weaknesses, a category covering RAG pipelines and vector database storage.

The 2026 edition kept all ten categories but reordered eight of them, renaming system prompt leakage to hidden context exposure so it covers any non-user-facing context an attacker can read back. Excessive agency climbed to third as applications handed models more tools to act with, while improper output handling fell to tenth.

A separate OWASP Top 10 for Agentic Applications, released in December 2025, covers autonomous agent systems under its own ASI01 through ASI10 numbering, addressing risks like goal hijacking and rogue agents that have no single-turn equivalent.

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Build an LLM RAG Chatbot With LangChain

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For additional information on related topics, take a look at the following resources:

• Pydantic AI: Build Type-Safe LLM Agents in Python (Tutorial)
• Building Type-Safe LLM Agents With Pydantic AI (Course)
• Connecting LLMs to Your Data With Python MCP Servers (Course)
• Prompt Engineering: A Practical Example (Tutorial)
• Hugging Face Transformers: Leverage Open-Source AI in Python (Tutorial)
• First Steps With LangChain (Course)
• Build an LLM RAG Chatbot With LangChain (Quiz)
• Pydantic AI: Build Type-Safe LLM Agents in Python (Quiz)
• Practical Prompt Engineering (Quiz)
• Hugging Face Transformers (Quiz)