In the rapidly evolving landscape of cybersecurity, the need for a robust and intelligent assistant capable of analyzing, summarizing, and reacting to events is paramount. This is why we designed Sysdig SageTM, our large language model (LLM)-based cloud security analyst, to be an expert in cloud detection and response (CDR). Sysdig Sage excels at summarizing complex events and providing clear explanations, which is crucial for identifying and promptly reacting to potential threats.

The pressure on security teams has never been greater. With an ever-evolving threat landscape, resource constraints, and now the rapid adoption of artificial intelligence (AI) technologies, Chief Information Security Officers (CISOs) are facing unprecedented challenges. This was one of the clear takeaways from our recent report CISO perspectives: separating the reality of AI from the hype, in which 53 CISOs shared their opinions and experiences of AI’s impact on their security operations.

Modern organizations have sprawling attacks surfaces of known and unknown assets that grow each day. This means understanding and managing your external attack surface is more crucial than ever. But with the vast number of digital assets that organizations need to monitor, accurately identifying every component of your attack surface can seem overwhelming – which is why many turn to External Attack Surface Management (EASM).

Welcome to the second part of our two-part special on Gartner’s “4 Ways Generative AI Will Impact CISOs and Their Teams” report! If you’ve missed the first part on model composition, you can read it here. Today, we will explore why security specialism matters in an AI security tool, particularly where AI quality is concerned.

Elastic Security 8.15 is now available, enhancing our mission to modernize security operations with AI-driven security analytics. Key features include the brand new Automatic Import to streamline data ingestion and onboarding, support for Google’s Gemini 1.5 Pro and Flash large language models (LLMs), a new set of APIs for the Elastic AI Assistant, on-demand file scans for the Elastic Defend integration, and a redesigned way of pivoting between different contexts.

Artificial Intelligence (AI) has the potential to revolutionize how businesses operate. But with this exciting advancement come new challenges that cannot be ignored. For proactive security and IT leaders, prioritizing security and privacy in AI can’t simply be a box-checking exercise; it's the key to unlocking the full potential of this wave of innovation.

The prevalence of APIs in today's digital environment is undeniable. They are crucial for modern applications, enabling seamless communication and data exchange between different software components. The rise of AI and machine learning has further accelerated API adoption, not only for accessing data and resources but also for rapid API development and deployment.

Snyk’s goal has always been to empower developers to build fast but safely. This is why we created the developer security category and why we were amongst the first advocates of “shifting left.” Now, AI has changed the equation. According to Gartner, over 80% of enterprises will have used generative AI APIs or models, or deployed their own AI model, by 2026.

The explosion of AI has ignited both excitement and apprehension across various industries. While AI is undeniably having a positive impact on engineering and customer service teams, cybersecurity and IT practitioners remain cautious. Concerns about data privacy, the inflexibility of disparate tools, and the sensitive nature of many mission-critical workflows—which, more often than not, require some level of human oversight—fuel a deep mistrust of LLMs by these teams.