Recommendation/Advice/Experience on SecAI+
- By Anthony Gui
- Certifications
- 8 Replies
OWASP Top 10 for Large Language Model Applications | OWASP Foundation
Aims to educate developers, designers, architects, managers, and organizations about the potential security risks when deploying and managing Large Language Models (LLMs)
Key Takeaways from OWASP Top 10 for LLM Applications
- Input manipulation: Attackers can trick LLMs with crafted prompts, leading to unauthorized access or bad decisions.
- Unvalidated outputs: If you trust LLM responses blindly, they can introduce vulnerabilities (e.g., unsafe code execution).
- Training data tampering: Poisoned datasets can corrupt models, affecting accuracy and ethics.
- Resource overload: Heavy queries can disrupt services or drive up costs.
- Sensitive data leaks: LLMs may accidentally reveal confidential information.
- Plugin risks: Poorly controlled plugins can open doors to exploits like remote code execution.
- Unchecked autonomy: Giving LLMs too much freedom can cause unintended, harmful actions.
