New infosec products of the week: March 8, 2024
Here’s a look at the most interesting products from the past week, featuring releases from Check Point, Delinea, Pentera, and Sentra.
Delinea Privilege Control for Servers enforces least privilege principles on critical systems
In Privilege Control for Servers, session recording and auditing occur on the host, so data cannot be altered. As a shared capability, session, and audit data is unified and saved in the Delinea Platform, simplifying storage and access while taking advantage of Delinea’s AI-driven auditing (now in public preview) to reduce the time to identify potentially dangerous activities without manually reviewing hours of session recordings.
Pentera Cloud empowers security teams to reduce exposure to cloud-native attacks
Pentera Cloud introduces automated pentesting designed for the scale of modern attack surfaces and the speed of dynamic cloud environments. Emulating real threat actor tactics and techniques, Pentera Cloud challenges security controls to identify exploitable gaps across AWS and Azure environments.
Check Point introduces Harmony SaaS for automated threat prevention
Leveraging behavior-based machine learning and the most complete repository of SaaS-related threat indicators and attributes, Check Point Harmony SaaS proactively prevents data theft, account takeover, file poisoning, and other SaaS attack vectors. Harmony SaaS automatically stops anomalous activity, ensuring the security of sensitive data.
Sentra Jagger provides real-time security insights and AI-assisted remediation guidelines
Security teams can use Sentra Jagger to get insights and recommendations on specific security actions through an interactive, user-friendly interface. In addition, customizable dashboards can be easily created based on user roles and preferences to optimize visibility into an organization’s data.
RiskInDroid: Open-source risk analysis of Android apps
RiskInDroid (Risk Index for Android) is an open-source tool for quantitative risk analysis of Android applications based on machine learning techniques.
