Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

What is Agentic AI vs GenAI?

Everyone knows ChatGPT, but Agentic AI is where the real work happens. In this Agentic AI vs GenAI breakdown, we explain why Agentic AI is the next major leap, and what it means for your business and career. Here’s the difference: Generative AI (GenAI): Creates content. You ask, it writes, summarizes, or creates. Agentic AI: Does work. It is built on three core components: a brain (reasons), memory (context), and tools (the key that lets agents touch real systems like APIs and databases).

The Economic Argument: The Real Cost of Insecure APIs in the AI Era

When cybersecurity teams talk about risk, they usually speak in technical terms like vulnerabilities, exploits, and attack vectors. But when they walk into the boardroom, they need to speak a different language. They need to speak about cost. In the era of AI, the cost of insecure APIs has shifted from a potential liability to a tangible line item on the balance sheet. It is no longer just about the cost of a data breach.

Identity governance gaps: How AI profiles move security beyond the label

If your identity governance program feels like a relic from a simpler time, you’re not alone. Traditional identity governance and automation (IGA) was built for a world where job titles told the whole story. A software engineer was a software engineer; a sales rep was a sales rep. Assigning access was intended to be as simple as slotting people into predefined roles.

Introducing System Prompt Hardening: production-ready protection for system prompts

Today, we’re launching System Prompt Hardening, Mend.io’s new capability that defends the hidden instructions that control how your AI systems behave. Unlike user-facing prompts, system prompts live behind the scenes, and when attackers manipulate them, the result can be data leaks, policy bypasses, or unsafe model behavior. System prompt hardening stops those attacks at the source and gives security, engineering, and risk teams a practical, auditable way to secure AI in production.

Now Available: Cyberhaven's Free AI App Risk Checker

Most security teams are being asked to "enable AI" before they have any real sense of which tools are safe to use. That gap is costing them. Cyberhaven's research found that the majority of AI tools in active enterprise use today fall into high or critical risk categories, and more than 80% of enterprise data flowing into AI is going to those risky tools, not to platforms built with serious security in mind. To help security teams cut through the noise, we built the Cyberhaven AI App Risk Checker.

SOAR vs. AI SOC: The Category That Left SOAR Behind

If you’ve been in security operations for more than a few years, you’ve lived through the automation hype cycle at least twice. First, it was SIEM that was going to solve everything. Then SOAR was supposed to fix what SIEM couldn’t. Now, AI SOC platforms are delivering what SOAR always promised but never actually could.

What Frontier Models Can Actually Do in a SOC: Open-source Benchmark for Agentic SecOps Capabilities

Maxime Lamothe-Brassard, founder and CEO of LimaCharlie, sought answers on AI’s current capabilities in the SecOps space. Plenty of benchmarks exist to test AI's knowledge of cybersecurity, but none test whether a model actually does the work. There's a significant difference between an AI that can answer trivia questions about CVEs and one that can pick up an alert, investigate it, and produce an incident report.That gap matters more now than ever.