A new attempt to influence AI-driven security scanners has been identified in a malicious npm package. The package, eslint-plugin-unicorn-ts-2 version 1.2.1, appeared to be a TypeScript variant of the ...

Threat actors are testing malware that incorporates large language models (LLMs) to create malware that can evade detection by security tools. In an analysis published earlier this month, Google's ...

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...

A new Android banking Trojan called Herodotus mimics human behavior, such as random keystroke delays, to evade detection tools. The malware employs device-takeover tactics, including the abuse of ...

A new Android malware family, Herodotus, uses random delay injection in its input routines to mimic human behavior on mobile devices and evade timing-based detection by security software. Herodotus, ...

Abstract: The rapid growth of malware and cyber threats demands intelligent methods for network traffic analysis. While machine learning (ML) techniques have shown high potential, their success is ...

Abstract: Feature representation is a key factor in machine learning-based malware detection, affecting the information expressed and used for detection, the choice of the classifier, and ...

A cybersecurity platform, under development for eight years at Sandia National Laboratories to detect and analyze advanced malware threats, is now publicly available, giving defenders in the public ...

As the proportion of encrypted traffic increases, it becomes increasingly challenging for network attacks to be discovered. Although existing methods combine unencrypted statistical features, e.g., ...

A new variant of the Konfety Android malware emerged with a malformed ZIP structure along with other obfuscation methods that allow it to evade analysis and detection. Konfety poses as a legitimate ...