OWASP Top 10 for LLM Applications v2026

About this course

The New Language of Risk

The world of software has changed. We have moved from a world of rigid code to a world of fluid language. While Large Language Models (LLMs) like GPT-4, Claude, and Mistral are revolutionizing application architecture, they have introduced a shadow dimension of risk—vulnerabilities that traditional firewalls and scanners simply cannot see.

In this new reality, an "exploit" isn't a malicious script; it’s a carefully crafted sentence. An "injection" doesn't require a database flaw; it just requires a document with hidden intent. This course is your tactical guide to the 2026 OWASP Top 10 for LLM Applications, the definitive security framework for the Generative AI era.

Decoding the Failure Patterns of AI

This isn't a dry list of theoretical threats. It is a practical, narrative-driven autopsy of how modern AI systems actually break. We move beyond the hype to explore the high-impact vulnerabilities that are currently reshaping the threat landscape:

Prompt Injection (The New SQLi): You will witness how model behavior can be hijacked by "jailbreaks" and "indirect injections" hidden in third-party data.

Training Data Poisoning: Learn how an adversary can compromise a fine-tuning pipeline or a vector store to "program" your model with a secret backdoor.

Sensitive Information Disclosure: We explore how models "leak" data through prediction—not because of a bug, but because of how they were trained.

Insecure Output Handling: Discover what happens when a model is tricked into executing malicious code or calling sensitive APIs on behalf of an attacker.

Model Denial of Service: Learn how "heavy prompts" can bankrupt your token budget or crash your inference infrastructure.

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