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Run by the team at orchestration, AI, and automation platform Tines, the Tines library contains pre-built workflows shared by real security practitioners from across the community, all of which are free to import and deploy via the Community Edition of the platform.  Their bi-annual "You Did What with Tines?!" competition highlights some of the most interesting workflows submitted by their users, many of which demonstrate practical applications of large language models (LLMs) to address complex challenges in security operations. One recent winner is a workflow designed to automate CrowdStrike RFM reporting. Developed by Tom Power, a security analyst at The University of British Columbia, it uses orchestration, AI and automation to reduce the time spent on manual reporting. Here, we'll share an overview of the workflow, plus a step-by-step guide for getting it up and running. The problem - time-consuming reporting The workflow's builder, Tom Power, explains, "The CrowdStrike ...

The lines between digital and physical realms increasingly blur. While this opens countless opportunities for businesses, it also brings numerous challenges. In our recent webinar, Shaping the Cyber-Physical Future: Trends, Challenges, and Opportunities for 2025 , we explored the different factors shaping the cyber-physical future. In an insightful conversation with industry experts, we discussed the most pressing security concerns of today and how to address them. Allison J. Taylor, the founder and CEO of Thought Marketing LLC, unveiled trends and recommended strategies businesses can employ to proactively bolster their security amidst evolving cyber challenges. Cesar Salazar, COO of Claro Enterprise Solutions, delved into innovative solutions that could propel business tech forward. He emphasized cyber-physical convergence, the use of emerging technologies, and responsive security operations. Below are the key takeaways from the webinar. These provide an overview of why businesses...

In recent years, artificial intelligence (AI) has begun revolutionizing Identity Access Management (IAM), reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that could signal a potential security breach. The focus has expanded beyond merely managing human identities — now, autonomous systems, APIs, and connected devices also fall within the realm of AI-driven IAM, creating a dynamic security ecosystem that adapts and evolves in response to sophisticated cyber threats. The Role of AI and Machine Learning in IAM AI and machine learning (ML) are creating a more robust, proactive IAM system that continuously learns from the environment to enhance security. Let's explore how AI impacts key IAM components: Intelligent Monitoring and Anomaly Detection AI enables continuous monitoring of both human and non-human identities , including APIs, service acc...