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How we trained an ML model to detect DLL hijacking
DLL hijacking is a common technique in which attackers replace a library called by a legitimate process with a malicious one. It is used by both creators of mass-impact malware, like stealers and banking Trojans, and by APT and cybercrime groups behind targeted attacks. In recent years, the numbe...
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...
RLSA-2025:6993 Moderate: openssh security update
OpenSSH is an SSH protocol implementation supported by a number of Linux, UNIX, and similar operating systems. It includes the core files necessary for both the OpenSSH client and server. Security Fixes: openssh: Machine-in-the-middle attack if VerifyHostKeyDNS is enabled CVE-2025-26465 For more...
RLSA-2025:12187 Important: thunderbird security update
Mozilla Thunderbird is a standalone mail and newsgroup client. Security Fixes: firefox: thunderbird: Large branch table could lead to truncated instruction CVE-2025-8028 firefox: thunderbird: Memory safety bugs CVE-2025-8035 firefox: thunderbird: Incorrect URL stripping in CSP reports CVE-2025-80...
Pilot Contamination Attacks Detection with Machine Learning for Multi-User Massive MIMO
Massive multiple-input multiple-output MMIMO is essential to modern wireless communication systems, like 5G and 6G, but it is vulnerable to active eavesdropping attacks. One type of such attack is the pilot contamination attack PCA, where a malicious user copies pilot signals from an authentic us...
EUVD-2022-35030
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EUVD-2021-9684
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EUVD-2022-35029
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EUVD-2021-32230
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EUVD-2021-9300
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EUVD-2022-37166
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EUVD-2023-32624
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EUVD-2022-0312
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EUVD-2022-7351
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EUVD-2024-0079
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EUVD-2022-6864
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EUVD-2022-6943
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EUVD-2022-7354
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