On this episode of Pentesters Chat, our team explores the distinct security vulnerabilities that arise when testing AI/ML systems compared to traditional systems.
- Adversarial Attacks: Understand how adversarial inputs can manipulate machine learning models, and how pentesters can exploit this weakness.
- Model Inference: Discuss techniques for reverse-engineering AI models and extracting sensitive data, including training datasets.
- Defense Strategies: Share insights on strengthening AI/ML systems against common attack vectors and building more resilient models.
On this episode from the Sprocket Team:
