Discussing IAM and AI Security
Understanding AI Hallucinations and How to Fix Them AI hallucinations occur when a model confidently produces information that is false, fabricated, or unsupported by real data. These errors can show up as invented facts, incorrect citations, or technical details that sound realistic but are not actually grounded in truth. Hallucinations happen because large language models […]
IDENTITY SENTINEL • AI SECURITY • APPSEC What Application Security Is and Why It’s Not Enough for AI Security Application Security (AppSec) is built to protect traditional software by securing the code, the build pipeline, and the runtime environment. It’s one of the most important disciplines in modern engineering and it should remain a non-negotiable […]
DSPM: The Backbone of AI Security, Cost Control, and Data Quality Identity Sentinel DSPM • AI Security • Data Governance DSPM: The Backbone of AI Security, Cost Control, and Data Quality AI is only as trustworthy as the data beneath it. DSPM is where security, quality, and operational reality finally converge so models and agents […]
AI PAM Part 3: Building a Complete Enterprise AI Security Ecosystem With CyberArk Secure AI Most organizations try to secure AI by focusing on one small corner of the problem: the model, the prompts, the data, the SaaS usage, or the policies. AI PAM forces a different realization. You cannot secure AI by chasing pieces. […]
AI Agents Are More Dangerous Than Human Admins The funny thing about AI in security is that most vendors talk about it like it is something magical, mysterious, or philosophical. CyberArk does the opposite. They treat AI like what it has already become: a wildly fast, extremely literal, and occasionally chaotic privileged user that desperately […]
Prompt leakage occurs when an AI system unintentionally reveals its internal instructions, policies, context, or sensitive information that should remain hidden. This includes system prompts, proprietary logic, model configuration, or private data. Leakage often happens when the model is not properly isolated from user input or when the system’s internal rules are not strongly protected […]
AI adoption is accelerating across every corner of the enterprise operations, guest experience, supply chain, marketing, revenue optimization, and beyond. But as organizations move from pilots to production, the conversation often defaults to guardrails on prompts or high-level model safety. In reality, enterprise AI requires something much broader: a roadmap for securing the entire ecosystem […]