EUVD-2008-3541

Malware in sbrugna...

EUVD-2017-11280

Malware in sbrugna...

EUVD-2020-22346

Malware in sbrugna...

EUVD-2020-22315

Malware in sbrugna...

EUVD-2020-22634

Malware in sbrugna...

EUVD-2018-4547

Malware in sbrugna...

EUVD-2020-22724

Malware in sbrugna...

EUVD-2017-12486

Malware in sbrugna...

EUVD-2019-5044

Malware in sbrugna...

EUVD-2008-5067

Malware in sbrugna...

EUVD-2017-12483

Malware in sbrugna...

EUVD-2021-1691

Malware in sbrugna...

EUVD-2005-3845

Malware in sbrugna...

EUVD-2017-12484

Malware in sbrugna...

EUVD-2017-4186

Malware in sbrugna...

Detecting DLL hijacking with machine learning: real-world cases

Introduction Our colleagues from the AI expertise center recently developed a machine-learning model that detects DLL-hijacking attacks. We then integrated this model into the Kaspersky Unified Monitoring and Analysis Platform SIEM system. In a separate article, our colleagues shared how the mode...

MulVuln: Enhancing Pre-Trained LMs with Shared and Language-Specific Knowledge for Multilingual Vulnerability Detection

Software vulnerabilities SVs pose a critical threat to safety-critical systems, driving the adoption of AI-based approaches such as machine learning and deep learning for software vulnerability detection. Despite promising results, most existing methods are limited to a single programming languag...

EUVD-2024-2765

Malicious code in bioql PyPI...

EUVD-2024-21245

Malicious code in bioql PyPI...

EUVD-2024-45478

Malicious code in bioql PyPI...