We dive into the OWASP Top 10 for LLMs, a list of 10 practical ways to start securing your LLM based web applications.
🔑 What's Inside?
The rise of large language models and their potential security pitfalls.
An introduction to the OWASP-style guidelines for securing these models.
In-depth analysis and discussions of each guideline and its real-world implications.
Practical demos showcasing the vulnerabilities and how to mitigate them.
Expert insights and best practices to ensure AI safety.
How to secure tools like ChatGPT, OpenAI, and Google Bard
OWASP Top 10 for LLMs: owasp.org/www-project-top-10-...
Reach me @ latio.tech or / james-berthoty
📌 Chapters:
0:00 - Intro
0:16 - OWASP
0:48 - LLMs
1:42 - OWASP Top 10 for LLMs
2:37 - 1. Prompt Injection
4:45 - Preventing Prompt Injection
6:33 - 2. Insecure Output Handling
7:50 - Preventing Insecure Output Handling
8:26 - 3. Training Data Poisoning
9:18 - Preventing Training Data Poisoning
10:11 - 4. Model Denial of Service
10:58 - Preventing Model DoS
11:44 - 5. Supply Chain Vulnerabilities
12:32 - Preventing Supply Chain Vulns
13:15 - 6. Sensitive Information Disclosure
13:54 - Preventing Sensitive Information Disclosure
14:37 - 7. Insecure Plugin Design
15:17 - Preventing Insecure Plugin Design
15:50 - 8. Excessive Agency
16:47 - Preventing Excessive Agency
17:01 - Overreliance
17:30 - Glorbo!
18:02 - Preventing Overreliance
18:15 - 10. Model Theft
18:57 - Conclusion
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