ML-Based DLL Hijacking Detection Integrated into SIEM
🛡️ Kaspersky developed a machine-learning model to detect DLL hijacking, a technique where attackers replace or sideload dynamic-link libraries so legitimate processes execute malicious code. The model inspects metadata such as file paths, renaming, size, structure and digital signatures, trained on internal analysis and anonymized KSN telemetry. Implemented in the Kaspersky Unified Monitoring and Analysis Platform, it flags suspicious loads and cross-checks cloud reputation to reduce false positives and support retrospective hunting.
