Security operations centers (SOCs) play a vital role in detection, containment and mitigation of today’s advanced cyber attacks. SoC teams are also responsible for proactively hunting for threats, and improving the organization’s overall security posture. Modern SOC analysts struggle with alert fatigue.

AI has undoubtedly revolutionized various industries, enhancing both efficiency and innovation through low-code and no-code platforms. Yet, this ease of development brings with it an increased burden of security. As business users and developers rapidly build applications, automations, and bots using AI, the complexity and volume of these creations amplify potential security vulnerabilities.

Cloud computing offers indisputable benefits, but with the caveat that it can quickly become a disorganized jumble unless adequately managed. It’s common for the average organization to use dozens of cloud instances, solutions, and resources scattered across multiple platforms. Such off-premises services quickly accumulate to accommodate the company’s ever-growing needs. This uncurbed growth, known as cloud sprawl, creates significant economic and security challenges.

Application Programming Interfaces (APIs) allow your applications to talk to one another, like an application-to-application iMessage or Signal. If you’ve ever texted a message to the wrong group chat, you’ve created a situation that mimics what broken function level authentication does between users and applications.

The use of artificial intelligence (AI) for defense allows for the better scanning of networks for vulnerabilities, automation, and attack detection based on existing datasets. However this is all in defense against an unknown attacker, who can have varying offensive tools all designed to overcome the most sophisticated defense. Is the biggest challenge for defensive AI that there is an offensive AI operator with unknown capabilities? And has offensive AI lowered the barrier of entry for bot attackers?

Mobile devices are now an integral part of the way we work, and because of that, mobile security has become a necessity when it comes to protecting an organization’s data. Yet with many IT and security teams already stretched to the limit, the task of incorporating mobile security into their existing operations may seem like an impossible task.

With the rapid adoption of AI-enabled services into production applications, it’s important that organizations are able to secure the AI/ML components coming into their software supply chain. The good news is that even if you don’t have a tool specifically for scanning models themselves, you can still apply the same DevSecOps best practices to securing model development.

Cybersecurity has become a battlefield where defenders and attackers engage in a constant struggle, mirroring the dynamics of traditional warfare. In this modern cyber conflict, the emergence of artificial intelligence (AI) has revolutionized the capabilities of traditionally asymmetric cyber attackers and threats, enabling them to pose challenges akin to those posed by near-peer adversaries.