| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - AI Security Foundations and Your Lab | |||
| 1. Course Documents and How to Use Them.mp4 | 53.6 MB | ||
| 2 - Prompt Injection and Output Handling | |||
| 10. LLM05 Improper Output Handling.mp4 | 41.9 MB | ||
| 11. Lab From LLM Output to XSS and Command Injection.mp4 | 49.9 MB | ||
| 3 - Data Exposure and Secrets | |||
| 12. LLM02 Sensitive Information Disclosure.mp4 | 42.3 MB | ||
| 13. Lab Extracting Training Data and PII.mp4 | 44.7 MB | ||
| 14. LLM07 System Prompt Leakage.mp4 | 40.7 MB | ||
| 15. Lab Stealing the System Prompt.mp4 | 44.7 MB | ||
| 16. Defenses Data Minimization and Secrets Handling.mp4 | 44.1 MB | ||
| 4 - Supply Chain, Poisoning, and RAG | |||
| 17. LLM03 Supply Chain Risks in the AI Stack.mp4 | 44.5 MB | ||
| 18. LLM04 Data and Model Poisoning.mp4 | 52.7 MB | ||
| 19. LLM08 Vector and Embedding Weaknesses.mp4 | 49 MB | ||
| 20. Lab Poisoning a RAG Knowledge Base.mp4 | 56.7 MB | ||
| 21. Securing the AI Supply Chain and RAG Pipeline.mp4 | 53.2 MB | ||
| 5 - Agentic and Operational Risks | |||
| 22. LLM06 Excessive Agency in Agentic Apps.mp4 | 46.1 MB | ||
| 23. Lab Exploiting an Over-Privileged Agent.mp4 | 54.5 MB | ||
| 24. LLM10 Unbounded Consumption — DoS, Denial-of-Wallet, Model Extraction.mp4 | 49.7 MB | ||
| 25. LLM09 Misinformation and Overreliance.mp4 | 45.4 MB | ||
| 6 - Building a Defense-in-Depth Program | |||
| 26. Guardrails Input Filtering, Output Encoding, and Rate Limits.mp4 | 48.2 MB | ||
| 27. LLM Red Teaming and Continuous Security Testing.mp4 | 51.4 MB | ||
| 28. Monitoring, Logging, and Incident Response for LLM Apps.mp4 | 42.8 MB | ||
| 29. Course Wrap-Up Your LLM Security Checklist.mp4 | 29 MB | ||
| 7. LLM01 Prompt Injection Explained.mp4 | 38.8 MB | ||
| 8. Lab Direct and Indirect Prompt Injection Attacks.mp4 | 51 MB | ||
| 9. Defending Against Prompt Injection.mp4 | 47.4 MB | ||
| 2. Welcome Who This Course Is For.mp4 | 31.3 MB | ||
| 3. Why LLM Apps Break Differently Than Web Apps.mp4 | 40.8 MB | ||
| 4. The OWASP LLM Top 10 (2025) What's New and What Moved.mp4 | 44.1 MB | ||
| 5. Setting Up Your Hands-On Attack Lab.mp4 | 42.6 MB | ||
| 6. Thinking Like an Attacker LLM Threat Modeling.mp4 | 39.3 MB |
AI Security: Defend LLM Apps Against the OWASP LLM Top 10
https://WebToolTip.com
Published 6/2026
Created by NEXUS ACADEMY
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 29 Lectures ( 3h 13m ) | Size: 1.3 GB
Break and secure LLM apps with hands-on labs covering the OWASP Top 10 for LLM Applications (2025).
What you'll learn
⚡ Explain why LLM and GenAI apps break differently than traditional web apps, and threat-model them like an attacker.
⚡ Exploit and defend against prompt injection (LLM01) and improper output handling (LLM05) in a safe, sandboxed lab.
⚡ Prevent sensitive information disclosure (LLM02) and system prompt leakage (LLM07) with data minimization and secrets hygiene.
⚡ Harden the AI supply chain, RAG pipelines, and vector stores against poisoning and embedding attacks (LLM03, LLM04, LLM08).
⚡ Contain excessive agency (LLM06) and unbounded consumption (LLM10), and run a defense-in-depth program with guardrails and monitoring.
Requirements
❗ Working knowledge of web application security, APIs, and the ability to read code (Python or JavaScript).
❗ A computer that can run a local, sandboxed lab (Docker or a Python virtual environment). No prior AI/ML experience required.
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