Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

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.

Samsung has introduced a groundbreaking bug bounty program offering up to $1,000,000 for discovering critical vulnerabilities in its mobile devices. This initiative, named the 'Important Scenario Vulnerability Program (ISVP),' underscores Samsung's commitment to bolstering the security of its Galaxy devices. The program focuses on vulnerabilities related to arbitrary code execution, device unlocking, data extraction, arbitrary application installation, and bypassing device protections.

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 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.

In today’s rapidly changing and evolving cloud-native environments, security and infrastructure teams face challenges ranging from managing complex deployments to ensuring capability across their entirety of their diverse infrastructure. EDR and XDR tools cannot provide comprehensive coverage of cloud workloads, making them fundamentally unsuited for cloud security.