Compromising LLMs - The Advent of AI Malware

Overview

Explore the security risks of AI integration, focusing on prompt injections and potential malware in language models. Learn about future challenges and consequences for AI assistants.

Syllabus

• Introduction to AI and Language Models
Overview of AI systems and their integration
Introduction to Large Language Models (LLMs)
• Understanding AI Security Risks
Definition and significance of AI security
Common vulnerabilities in AI systems
• Prompt Injection Attacks
What is a prompt injection?
Real-world examples of prompt injection in LLMs
Techniques to detect and mitigate prompt injection attacks
• Potential AI Malware
Definition and characteristics of AI malware
How AI malware can be created and deployed
Case studies of potential AI-driven malware
• Future Challenges in AI Security
AI and the evolution of cybersecurity threats
The role of AI in securing versus attacking systems
Upcoming trends and anticipated challenges
• Consequences for AI Assistants
Impact on individuals and businesses
Guidelines for developing secure AI assistants
Ethical considerations in AI security
• Strategies for Mitigating AI Security Risks
Best practices in AI security
Regulatory and compliance issues
Importance of continuous monitoring and adaptation
• Conclusion
Summary of key lessons
Future outlook for AI and security
• Additional Resources
Recommended readings
Relevant tools and technologies for AI security
Ongoing research topics and initiatives

Subjects

Conference Talks