Confusing Antimalware Neural Networks
Date: 2021-06-23
Affected: Kaspersky's Antimalware ML Model
Attack vector: adversarial-input
Category: research
Severity: High

Cloud storage and computations have become popular platforms for deploying ML malware detectors. In such cases, the features for models are built on users' systems and then sent to cybersecurity company servers. The Kaspersky ML research team explored this gray-box scenario and showed that feature knowledge is enough for an adversarial attack on ML models. They attacked one of Kaspersky's antimalware ML models without white-box access to it and successfully evaded detection for most of the adversarially modified malware files.


Mitigations:

Architectural layers (MAESTRO):