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

Follow this real-life network attack simulation, covering 6 steps from Initial Access to Data Exfiltration. See how attackers remain undetected with the simplest tools and why you need multiple choke points in your defense strategy. Surprisingly, most network attacks are not exceptionally sophisticated, technologically advanced, or reliant on zero-day tools that exploit edge-case vulnerabilities. Instead, they often use commonly available tools and exploit multiple vulnerability points. By simulating a real-world network attack, security teams can test their detection systems, ensure they have multiple choke points in place, and demonstrate the value of networking security to leadership. In this article, we demonstrate a real-life attack that could easily occur in many systems. The attack simulation was developed based on the MITRE ATT&CK framework, Atomic Red Team,  Cato Networks ' experience in the field, and public threat intel. In the end, we explain why a holistic secur