Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How to Manage Unauthorized AI Tool Usage in Your Business

In only a few years, artificial intelligence (AI) has changed almost every aspect of life, and especially so in business. Today, employees are using generative AI tools to draft emails, code software, and analyze data at lightning speed. However, there is a hidden side to this productivity boost: unauthorized AI use. Many employees are bypassing official IT channels and using shadow AI applications to get their work done.

New CrowdStrike Innovations Secure AI Agents and Govern Shadow AI Across Endpoints, SaaS, and Cloud

As organizations race to adopt new AI tools, deploy AI agents, and build AI-powered software, they create new attack surfaces that traditional security controls were never designed to protect. A key example is the prompt and agentic interaction layer, which faces novel threats like indirect prompt injection and agentic tool chain attacks.

AI vs AI: Securing the Expanding Cyber Attack Surface | Mr. Anirban Mukherji at ET Studios

In this exclusive interview byte at ET Studios, Our Founder & CEO Mr. Anirban Mukherji discusses how increasing enterprise connectivity through cloud applications, third-party integrations, and remote work is exploding the enterprise cyber attack surface making identity security and access control more critical than ever. He dives into key threats like traditional ransomware, zero-day supply chain attacks, hyper-personalized AI phishing, and systemic incidents.

Your AI Isn't Broken... Your Data Is #shorts #ai

Your AI works perfectly during testing… but suddenly fails in production. Why? The problem usually isn’t the model — it’s the data. Synthetic data looks clean and structured. But real-world data is messy: typos, missing values, broken formats, and unexpected edge cases. When AI models train only on synthetic datasets, they never learn how to handle real-world complexity. In this video, we explain why synthetic data can break AI systems and how using real production data safely can make AI more reliable.

Delivering the Agentic SOC as a Service: A Turnkey Approach to AI-Driven Cybersecurity

Every year at RSA Conference, I spend time with security leaders who are trying to solve the same fundamental challenge. They know what strong security operations should look like, but the path to building and sustaining that capability inside their own organization has become increasingly difficult. The market is shifting from buying tools to buying outcomes.

Where Cato Sits in the AI Economy

Every major technological shift reshapes the landscape, creating both winners and losers. AI will be no different. The key question is which companies are positioned to capture the value it generates, and which ones may fall behind as it unfolds. If you look at previous technology shifts, the winners were not always the companies building the most visible products. They were often the ones that enabled the shift to happen in the first place, or those that benefited from the structural changes it created.

The Complicating Factors of Deploying MCP in the Enterprise

Boris Kurktchiev is a Field CTO at Teleport, known for his expertise in Zero-Trust identity solutions for cloud and AI, and for his contributions to the CNCF's Cloud Native AI working group. Doyensec dropped a piece last week called The MCP AuthN/Z Nightmare, and I think anyone deploying MCP in production needs to read it.