Reverse Engineering AI Systems & LLMs for National Security Essentials Training by Tonex
This course offers a deep dive into the reverse engineering of AI systems and large language models (LLMs) in the context of national security. Participants will explore how AI systems can be manipulated, audited, and analyzed to uncover vulnerabilities and prevent misuse. The course covers key attack surfaces, jailbreaking techniques, and black-box auditing, with an emphasis on practical methods and national defense applications. A critical part of the training involves understanding how these methods intersect with cybersecurity, as reverse engineering exposes risks in AI deployments that can lead to data breaches, unauthorized access, and model exploitation if not properly secured.
Audience:
- Cybersecurity Professionals
- National Security Analysts
- Intelligence Community Personnel
- AI Researchers in Defense
- Government Cyber Policy Advisors
- Technical Risk Assessors and Auditors
Learning Objectives:
- Understand the fundamentals of AI model reverse engineering
- Identify common attack surfaces in AI systems
- Analyze jailbreaking techniques and model behavior
- Conduct black-box audits to assess vulnerabilities
- Explore implications of AI exploitation in national security
- Strengthen cybersecurity strategies for AI defense
Course Modules:
Module 1: Introduction to AI Reverse Engineering
- Overview of AI and LLM architecture
- Importance of reverse engineering in national defense
- Key terminology and concepts
- Threat vectors and national security concerns
- Reverse engineering vs. adversarial learning
- Legal and ethical considerations
Module 2: Attack Surfaces in AI Systems
- Model input manipulation points
- Data poisoning and integrity risks
- Infrastructure-level vulnerabilities
- Exploitable model outputs
- API and endpoint weaknesses
- Case studies on real-world breaches
Module 3: Jailbreaking AI and LLMs
- Understanding prompt injection methods
- Bypassing safety layers
- Generating unauthorized outputs
- Role of transfer learning in jailbreaks
- Evasion of content filters
- National security risks of jailbroken LLMs
Module 4: Black-Box Auditing Techniques
- Fundamentals of black-box AI testing
- Behavioral analysis through inputs/outputs
- Monitoring system responses under attack
- Inferencing model parameters
- Identifying hidden biases or leaks
- Reporting and mitigation procedures
Module 5: Reverse Engineering for Security Teams
- Integrating AI threat assessment
- Tools and frameworks for red-teaming AI
- Risk scoring AI models
- Collaboration with cybersecurity teams
- Proactive detection of jailbreak attempts
- Policy enforcement for secure model use
Module 6: National Security Implications
- Impact of AI exploitation on intelligence
- AI misinformation and psychological operations
- LLM misuse for cyber-espionage
- Threat modeling in military contexts
- Securing AI in classified environments
- Long-term strategy for AI model hardening
Join Tonex’s Reverse Engineering AI Systems & LLMs for National Security Essentials Training to equip yourself with the expertise needed to uncover and mitigate vulnerabilities in powerful AI systems. Enhance national defense readiness by learning to defend against AI threats before they become real-world risks. Enroll today to take a proactive role in AI cybersecurity.