OWASP Top 10 for LLMs — How Hackers Exploit AI Models (Explained Simply)

AI models aren’t invincible — they can be hacked, manipulated, and exploited just like any web app.
The OWASP Top 10 for LLMs reveals the biggest AI-specific security risks and how attackers weaponize models like ChatGPT, Gemini, or Claude.

In this video, we’ll walk through real-world examples, prompt injection demos, and how to defend LLM-powered systems.

You’ll Learn:
✅ The OWASP Top 10 for Large Language Models (LLMs)
✅ Real examples of prompt injection, data exfiltration, and model poisoning
✅ How attackers manipulate AI memory and jailbreak protections
✅ How to secure AI pipelines, agents, and APIs
✅ The tools and frameworks for LLM red teaming and monitoring

Timestamps:
0:00 — What is OWASP Top 10 for LLMs?
0:45 — Prompt Injection Attacks
1:30 — Insecure Output Handling
2:15 — Training Data Poisoning
3:00 — Model Denial of Service
3:45 — Sensitive Information Disclosure
4:30 — Insecure Plugin Design
5:15 — Excessive Agency (autonomous model risks)
6:00 — Supply Chain Vulnerabilities in LLMs
7:00 — Overreliance on LLMs (blind trust flaws)
8:00 — Model Theft and Extraction Risks
9:00 — AI Defense Tools and Secure Design Patterns

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