artificial intelligence malware | Breaking Cybersecurity News | The Hacker News

Looking for an automated malware analysis software? Something like a 1-click solution that doesn't require any installation or configuration…a platform that can scale up your research time… technology that can provide data-driven explanations… well, your search is over! Israeli cybersecurity and malware researchers today at Black Hat conference launch a revolutionary machine learning and artificial intelligence-powered malware researcher platform that aims to help users identify unknown malware samples before they strike. Dubbed SNDBOX , the free online automated malware analysis system allows anyone to upload a file and access its static, dynamic and network analysis in an easy-to-understand graphical interface. The loss due to malware attacks is reported to be more than $10 billion every year, and it's increasing. Despite the significant improvement of cyber security mechanisms, malware is still a powerful and effective tool used by hackers to compromise systems because of

Artificial Intelligence (AI) has been seen as a potential solution for automatically detecting and combating malware, and stop cyber attacks before they affect any organization. However, the same technology can also be weaponized by threat actors to power a new generation of malware that can evade even the best cyber-security defenses and infects a computer network or launch an attack only when the target's face is detected by the camera. To demonstrate this scenario, security researchers at IBM Research came up with DeepLocker —a new breed of "highly targeted and evasive" attack tool powered by AI," which conceals its malicious intent until it reached a specific victim. According to the IBM researcher, DeepLocker flies under the radar without being detected and "unleashes its malicious action as soon as the AI model identifies the target through indicators like facial recognition, geolocation and voice recognition." Describing it as the "sp

Compromising the browser is a high-return target for adversaries. Browser extensions, which are small software modules that are added to the browser and can enhance browsing experiences, have become a popular browser attack vector. This is because they are widely adopted among users and can easily turn malicious through developer actions or attacks on legitimate extensions. Recent incidents like  DataSpii  and the  Nigelthorn  malware attack have exposed the extent of damage that malicious extensions can inflict. In both cases, users innocently installed extensions that compromised their privacy and security. The underlying issue lies in the permissions granted to extensions. These permissions, often excessive and lacking granularity, allow attackers to exploit them. What can organizations do to protect themselves from the risks of browser extensions without barring them from use altogether (an act that would be nearly impossible to enforce)?  A new report by LayerX, "Unveiling the