AI systems have become essential in various applications but are increasingly targeted by sophisticated attacks such as data poisoning, model extraction, and prompt injections. Implementing structured AI penetration testing, leveraging frameworks like MITRE ATLAS and IBM ART, is critical for organizations to identify vulnerabilities and build resilient AI models. #MITREATLAS #IBMART
Keypoints
- AI systems are attractive targets due to their growing complexity and importance.
- Threat landscapes involve attacks on training data, model logic, and output interpretation.
- Frameworks like MITRE ATLAS and NIST taxonomy help in threat modeling and attack classification.
- Effective AI penetration testing includes custom, open-source, SaaS, and on-premise deployment strategies.
- Tools such as IBM ART and Counterfit enable simulated attacks and defenses for robust AI security.