Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

Moonshot AI governance breakdown: Lessons from the Cursor/Kimi K2.5 incident

What happens when a $29 billion company forgets to rename a model ID, and what it means for every organization using open-source AI. On March 19, 2025, Cursor, the AI-powered coding tool valued at $29 billion and generating an estimated $2 billion in annual recurring revenue, launched Composer 2, its newest and most powerful coding model.

Why NER models fail at PII detection in LLM workflows - 7 critical gaps

In AI systems, PII detection is the first step. Not the most glamorous step. But the one that, when it fails, takes everything else down with it. Identifying sensitive data (names, Social Security numbers, financial records, health information) has to happen before any of it reaches an LLM. Get this wrong, and you’re looking at one of two bad outcomes: Traditional DLP systems could afford to be aggressive with detection. LLMs can’t. They depend on full context to generate correct outputs.