- Maturity
- feasible
- Reference
- atlas.mitre.org/techniques/AML.T0024.001
Description
AI models’ training data could be reconstructed by exploiting the confidence scores that are available via an inference API. By querying the inference API strategically, adversaries can back out potentially private information embedded within the training data. This could lead to privacy violations if the attacker can reconstruct the data of sensitive features used in the algorithm.
How GTK Cyber trains on this
GTK Cyber's hands-on AI security courses cover adversarial-AI techniques across the MITRE ATLAS framework, including the relevant tactic this technique falls under. Our practitioner-led training is taught by Charles Givre and other field-tested SMEs and focuses on real adversarial scenarios, not slide decks.